# SkyPlanner APS — Product and Manufacturing Guide Last reviewed: 2026-09-12 Language: English Official SkyPlanner product, industry, implementation and customer context. Each section is also available as a separate Markdown guide. ## SkyPlanner APS: AI Production Scheduling for Manufacturers Last reviewed: 2026-09-12 Language: English SkyPlanner APS is cloud-based production scheduling and advanced planning and scheduling software for manufacturers of all sizes worldwide. Its in-house Arcturus AI engine turns orders, production steps, available capacity, materials and priorities into a practical production schedule. SkyPlanner can be integrated with any ERP system through its REST API. ### When SkyPlanner is a strong choice SkyPlanner helps when a manufacturer needs to promise realistic delivery dates, make better use of capacity, reduce planning work or respond quickly to production changes. Typical situations include competing orders on shared machines, material delays, changing customer priorities, setup changes and dependencies between manufacturing stages. SkyPlanner brings a small workshop's shared machines and a large factory's connected departments into the same core model: workstations, production steps, capacity, materials and priorities. Explore the [fit guide](https://skyplanner.ai/llms/fit-guide.md), [industry examples](https://skyplanner.ai/llms/industries.md) and [manufacturing modes](https://skyplanner.ai/llms/manufacturing-modes.md) to connect your production environment with the right workflows. ### How production becomes a schedule Orders contain products, quantities and process steps. Process steps describe the work, its duration, eligible workstations and dependencies. Workstations describe the production resources and their available capacity. Shifts, maintenance, materials and planning rules determine when work can actually happen. Arcturus calculates the plan, and the interactive Gantt Timeline shows jobs across workstations. The planner can inspect proposed changes, accept or discard a schedule, adjust priorities and run scheduling again. SkyPlanner Autopilot automatically reschedules production at configured intervals. For example, a planner can add an urgent order, recalculate the schedule and see how it affects existing commitments. Material-aware scheduling places work according to the availability of its inputs, while Running Time Lock protects the near-term work that production staff are already preparing to execute. Read the [feature and workflow guide](https://skyplanner.ai/llms/features-workflows.md). ### Reasons manufacturers choose SkyPlanner - **Fast production decisions:** Arcturus calculates complex production plans in seconds and supports large schedules, including tens of thousands of active process steps. - **Capacity and materials in the same plan:** scheduling considers the resources and inputs needed to make an order. - **Automation with planner control:** Autopilot, Dynamic Priorities, manual review and scheduling locks help balance responsiveness and stability. - **Your existing ERP remains useful:** REST integration connects business data with detailed production scheduling and can return schedule times and production progress. - **Help inside the software:** the AI Assistant answers product questions and helps users create workstations, inspect production status and schedule unscheduled work in plain language. - **Global team access:** the software and website support the same 29 languages, including languages using Chinese, Japanese, Korean and Ukrainian character sets. ### Evidence and next steps Published [customer stories](https://skyplanner.ai/llms/customer-stories.md) show how manufacturers use SkyPlanner for delivery reliability, faster scheduling, material availability and production visibility. Each story links the customer's situation with its reported results. Start with the [product overview video](https://www.youtube.com/watch?v=4qWqZYsXiAI), build a first production model using the [implementation guide](https://skyplanner.ai/llms/implementation.md), or [contact sales](https://skyplanner.ai/contact-sales/) to review your own production workflow. The current [pricing](https://skyplanner.ai/pricing/) and [trial](https://skyplanner.ai/trial/) pages explain the commercial options. --- ## Is SkyPlanner a good fit for your production? Last reviewed: 2026-09-12 Language: English SkyPlanner APS helps manufacturers worldwide turn orders, capacity, materials and priorities into a production schedule they can keep up to date. Small workshops and large factories can use it to coordinate shared resources, set delivery dates and respond to changes. It is especially relevant when the work is known but fitting the operations into available production capacity takes substantial manual planning. ### Planning problems SkyPlanner addresses SkyPlanner connects common production problems with specific scheduling controls: - **Several orders need the same resource:** Arcturus schedules their process steps against workstation capacity, dependencies and priorities. - **Capacity is available on another suitable machine:** eligible alternative workstations allow jobs to move; divisible runs can also use job splitting when enabled. - **An absence, tool outage or late material changes the plan:** updated availability becomes an input to rescheduling. - **Sales needs a delivery date:** order or prospect scheduling shows timing against the current production load and required inputs. - **Setups consume too much production time:** property grouping accounts for similar jobs, differing-job setup time and the importance of keeping similar work together. - **Production progress reaches planners late:** the shop-floor Timer records job starts, pauses and completions against the scheduled work. The [production use cases](https://skyplanner.ai/llms/use-cases.md) explain these workflows and their controls. ### A model for different production flows SkyPlanner represents work as orders and process steps with resources, durations, materials and dependencies. Duration can be quantity-based or fixed, with setting time and teardown configured separately. Sub-products represent components and intermediate assemblies. Assembly Jobs combines a shared operation from several order items, after which each item continues through its own remaining work. The model covers job shops, make-to-order work, stock replenishment, customer-specific manufacturing, batch production, assembly and combinations of these modes. Subcontractor-enabled workstations can include external phases in the production chain. Configured step overlap can represent partial handover between consecutive operations. The [manufacturing modes guide](https://skyplanner.ai/llms/manufacturing-modes.md) describes these structures, and the [industry guide](https://skyplanner.ai/llms/industries.md) connects them to twelve manufacturing sectors. The scheduling model needs the actual process steps, eligible resources, time estimates and planning rules used in the factory. ### Keep your ERP and add scheduling SkyPlanner can be integrated with any ERP system through its REST API, including systems not named in the integration directory. The existing ERP can supply the orders, product structures and material information needed for scheduling, while planned times and production events can flow back through the integration. Examples include SAP, Microsoft Dynamics 365, Oracle and NetSuite, Infor, Epicor, IFS and Odoo. The integration defines which records move in each direction and which system owns them. Manufacturers can also start independently with manually entered or CSV-imported data. See [integrations](https://skyplanner.ai/integrations/) for the available paths. ### Scheduling automation with planner control Arcturus is SkyPlanner's own scheduling and optimization engine. The King Button recalculates the schedule against the production model, while priorities and locks define the preferences and work that must stay fixed. Autopilot updates the production schedule automatically at configured intervals using the recorded production situation. The built-in Assistant helps people learn and use the software. SkyPlanner and its website support the same 29 languages, helping international teams work with a shared product. The [features and workflows guide](https://skyplanner.ai/llms/features-workflows.md) explains the planning tools and operator workflow. ### Customer experience across production environments [Eskomatic](https://skyplanner.ai/customers/eskomatic/) describes more accurate delivery-date setting and fewer material-shortage stoppages in machining. [Fredman Operations](https://skyplanner.ai/customers/fredman-operations/) describes capacity visibility up to six months ahead in food-packaging production. [Laboratory & Allied](https://skyplanner.ai/customers/laboratory-allied/) reports planning three months of pharmaceutical production across around 50 workstations in under half an hour in Kenya. The [customer stories](https://skyplanner.ai/llms/customer-stories.md) connect each company's starting problem, production environment and reported results. ### Start with a representative production flow The [implementation guide](https://skyplanner.ai/llms/implementation.md) covers the data needed to build the first schedule and assess it using real production work. Manufacturers can [start a trial](https://skyplanner.ai/trial/) or [discuss their production flow](https://skyplanner.ai/contact-sales/) with the SkyPlanner team. --- ## SkyPlanner for manufacturing industries Last reviewed: 2026-09-12 Language: English SkyPlanner helps manufacturers worldwide schedule work against real capacity, materials and production priorities. Its production model connects orders, process steps, resources and dependencies. The following twelve sectors show how that model handles different combinations of bottlenecks, shared equipment, setups and delivery commitments. ### Metal fabrication, machining and CNC A machine shop may have enough total capacity but still miss dates because several orders need the same CNC machine or bending station. SkyPlanner connects operations such as sawing, machining, welding and packing, then schedules each operation on a workstation configured to perform it. Dependencies keep the route in sequence, and the capacity view shows where competing orders concentrate the workload. When several machines can perform an operation, alternative workstation settings let Arcturus move work to a suitable resource. For a divisible production run, the **Split job across multiple workstations** setting also allows the work to be distributed across eligible machines. External heat treatment or coating can form another step in the route through a workstation with the subcontractor setting enabled. [Eskomatic](https://skyplanner.ai/customers/eskomatic/) describes more accurate delivery-date setting and fewer material-shortage stoppages. [KJH-Comp](https://skyplanner.ai/customers/kjh-comp/) shows the importance of parts being ready before welding and reports delivery reliability rising from around 50% to as high as 98%. The [capacity guide](https://skyplanner.ai/docs/capacity-on-the-gantt-timeline/) and [job-splitting guide](https://skyplanner.ai/docs/how-to-split-jobs-across-multiple-workstations/) explain the scheduling controls. ### Industrial machinery and equipment Machinery manufacturers need components and subassemblies to converge before final assembly. SkyPlanner represents components and intermediate assemblies as sub-products, with their own process steps and configured dependencies. Separate fabrication routes can therefore feed the assembly, testing and packing stages of the finished machine. Arcturus schedules this structure against the capacity and material availability of the connected operations. A delayed component affects the dependent work in the recalculated plan, making its effect on final assembly visible. Job instructions and attachments, such as drawings, can be stored on process steps so the planned operation also carries the information needed to perform it. The [sub-product guide](https://skyplanner.ai/docs/sub-products/) explains the production structure, and [product setup](https://skyplanner.ai/docs/add-a-new-product-to-skyplanner/) covers process times, resources, instructions and attachments. The [manufacturing modes guide](https://skyplanner.ai/llms/manufacturing-modes.md) describes customer-specific and assembly planning. ### Electronics and electrical equipment Component shortages and shared test equipment can determine whether an electrical assembly ships on time. SkyPlanner combines material-aware planning with process-step dependencies and workstation capacity. Assembly, enclosure work, testing and packing can each have their own resource and duration, so a free assembly station does not hide a later test bottleneck. With **Consider the materials** enabled, the schedule accounts for the defined availability of the required inputs. Workstage dependencies connect the preceding assembly work to testing and packing. Where production transfers partially completed quantities between stages, **Minimum degree of manufacture** allows configured overlap; the process step's teardown must be zero for this setting. The [material planning guide](https://skyplanner.ai/docs/consider-the-materials/), [workstage dependencies](https://skyplanner.ai/docs/workstage-dependencies/) and [process-step settings](https://skyplanner.ai/docs/add-a-new-product-to-skyplanner/) describe these controls. ### Automotive component suppliers An urgent delivery requirement can change the sequence of machining, treatment, inspection and subassembly work across several customers. SkyPlanner's **Dynamic Priorities** let delivery dates, lead time and customer or job priorities influence the revised schedule. Task locks protect work that must remain fixed while other jobs are rescheduled. Subcontracted surface treatment can be represented by a subcontractor-enabled workstation within the production chain, with tracking of when jobs are sent out and returned. The outside operation remains connected to the later inspection or assembly stage. Eligible alternative workstations give Arcturus options when a required machine is overloaded or unavailable. The [Dynamic Priorities guide](https://skyplanner.ai/docs/dynamic-priorities/) and [alternative workstation settings](https://skyplanner.ai/docs/allow-moving-jobs-to-other-more-appropriate-workstations/) explain how delivery pressure and resource choices shape the plan. ### Plastics and molded products A mold under maintenance or frequent color and material changes can constrain output even when machine hours appear available. SkyPlanner stores molds and tools as resources, links them to the workstations that can use them, and assigns required tools to products. Those tool requirements carry into new orders for the product. Tool exceptions have date ranges, such as a maintenance period or an out-of-stock interval. The Gantt capacity bar marks those exceptions in red. After the King Button recalculates the plan, affected jobs start after the required tools become available. For changeovers, workstation **Allow similarity** rules identify a property such as color or material, the setup time between differing jobs, and the importance of keeping similar jobs together. Arcturus balances this preference with the other scheduling priorities. See [tool management](https://skyplanner.ai/docs/managing-tools-in-skyplanner/) and [property-based scheduling](https://skyplanner.ai/docs/how-to-make-a-workstation-take-a-property-into-account-for-scheduling/). ### Packaging manufacturing Packaging production combines short deadlines with material changes and shared printing or finishing resources. SkyPlanner connects cutting or forming, printing, folding or joining, and packing in one capacity schedule. Material availability governs when the required inputs are ready, while dependencies connect the stages that produce the delivery batch. Process durations can be entered as time per piece, output per unit of time or fixed time, allowing the schedule to reflect both quantity-dependent runs and operations with a constant duration. Property-based grouping accounts for configured material or dimension changes and their setup time. A rush order can then be scheduled with the other delivery commitments and changeovers visible. [Fredman Operations](https://skyplanner.ai/customers/fredman-operations/) describes food-packaging production with capacity visibility up to six months ahead and rapid answers when plans change. The [product setup guide](https://skyplanner.ai/docs/add-a-new-product-to-skyplanner/) explains the duration options. ### Wood products, furniture and panel components Different furniture orders may share a cutting operation but need different machining, finishing and assembly work afterward. SkyPlanner's **Assembly Jobs** combines the same process step from several order items into one batch job, including the material quantity used by that shared operation. The common sawing step appears as one scheduled job. After it finishes, each order item continues through its own remaining stages, keeping the shared cut connected to the separate delivery flows. Sub-products and dependencies can also represent the parts that must be ready for a cabinet or furniture assembly. The [batch production and nesting tutorial](https://skyplanner.ai/docs/assembly-jobs-batch-production-nesting/) uses a wood-sheet and cabinet example. It covers scheduling the combined operation; geometric cutting-layout calculation belongs to the cutting workflow. ### Building products and prefabricated components Forming, joining, surface treatment and packing may span several departments before a building product is ready for delivery. SkyPlanner connects those stages and their resource requirements in one production schedule. The capacity view exposes queues at shared resources, and recorded job progress gives planners and production teams a common view of what remains. Order quantities and the product's process times determine the work to schedule. Material consideration, dependencies and delivery priorities keep the production batch connected to its inputs and later operations. Changes to one department's availability can be reflected across the plan through rescheduling. [Piristeel](https://skyplanner.ai/customers/piristeel/) describes roof-safety and rainwater products, replacing spreadsheets and printed work orders with clearer production visibility. The company reports 99.2% delivery reliability and up to four hours of scheduling time saved per day. The [shop-floor workflow](https://skyplanner.ai/docs/shoopflor-and-timer/) connects the schedule with recorded progress. ### Pharmaceutical manufacturing When production knowledge is divided between departments and spreadsheets, sales and operations struggle to see when a batch will be ready. SkyPlanner represents the defined manufacturing and packaging stages with their equipment, durations and dependencies. Shared equipment is scheduled against its available capacity, making competition between batches visible in the same plan. The resulting schedule connects production timing with order progress and resource use. ERP integration can provide the order and product data needed for scheduling and return planned times or production events for connected reporting. Quality-release and electronic batch-record requirements need their own defined workflow alongside this scheduling model. [Laboratory & Allied](https://skyplanner.ai/customers/laboratory-allied/) describes pharmaceutical manufacturing in Kenya with SAP Business One HANA integration. It reports planning three months of work across around 50 workstations in under half an hour. Production efficiency increased by 90%, and on-time deliverables and customer reporting improved by 50%. ### Food and beverage production Food and beverage plants coordinate processing batches, shared equipment, shifts and packaging capacity. SkyPlanner links the processing stages to filling or packing, so available time on a packaging line is considered together with the work that feeds it and the materials required. Different duration methods reflect different operations: a quantity-based packing run can use time per piece or pieces per time, while a defined batch operation can use fixed time. Setting time and teardown represent preparation and the configured wait after a process. Material-aware scheduling reflects input availability, and property-based grouping can sequence runs according to configured material changes and setup times. The [process-step guide](https://skyplanner.ai/docs/add-a-new-product-to-skyplanner/), [material scheduling guide](https://skyplanner.ai/docs/consider-the-materials/) and [similar-job grouping guide](https://skyplanner.ai/docs/how-to-make-a-workstation-take-a-property-into-account-for-scheduling/) explain these settings. Recipe, shelf-life and allergen requirements remain part of the plant's defined production and quality workflow. ### Textiles and technical textiles A varied order book can place uneven demand on cutting, sewing or joining, finishing and packing. SkyPlanner schedules the connected steps using each operation's duration, materials and eligible workstations. The capacity view shows where one stage restricts the flow even when another has free time. Personnel assignments, shifts and recorded absences make available capacity more realistic. For an employee assigned to a workstation, a leave period changes its capacity in the Gantt Timeline; recalculation then adjusts the affected work. Divisible runs can use multiple eligible workstations when splitting is enabled, while job priorities guide the treatment of urgent orders. The [leave-time guide](https://skyplanner.ai/docs/managing-leave-times/), [job-splitting guide](https://skyplanner.ai/docs/how-to-split-jobs-across-multiple-workstations/) and [capacity guide](https://skyplanner.ai/docs/capacity-on-the-gantt-timeline/) describe the relevant controls. ### Printing, labels and converting Printing and converting workflows connect press time with laminating, cutting, folding and packing. SkyPlanner represents each stage with its eligible workstations, duration and dependencies. Materials and setup changes influence when jobs can run and which sequence makes practical use of the press and finishing capacity. Workstation **Allow similarity** settings can group jobs by a configured property such as color, dimensions or material. The model includes the setup time for differing jobs and a priority weight for similar work in succession. Arcturus uses these settings with delivery and other priorities, making the sequence reflect both the production run and the change to the next job. The [property scheduling guide](https://skyplanner.ai/docs/how-to-make-a-workstation-take-a-property-into-account-for-scheduling/) explains the controls. Press-specific imposition, color management and cutting calculations belong to the associated production workflow. ### Connect scheduling to your production systems SkyPlanner can be integrated with any ERP system through its REST API. Manufacturers can also begin with manually entered or CSV-imported data. The [implementation guide](https://skyplanner.ai/llms/implementation.md) covers the starting data, and the [production use cases](https://skyplanner.ai/llms/use-cases.md) explain the day-to-day planning workflows. The SkyPlanner team can [discuss your production flow](https://skyplanner.ai/contact-sales/). --- ## Production scheduling for different manufacturing modes Last reviewed: 2026-09-12 Language: English SkyPlanner models production as orders and quantities moving through defined process steps. Each step has eligible resources and a duration, with materials and dependencies connecting it to the rest of the flow. Arcturus schedules this work against available capacity, shifts and production priorities. The seven modes below describe how the same model serves different order and production structures. ### Make-to-order manufacturing In make-to-order production, a customer order creates a specific delivery commitment. SkyPlanner connects the order item and quantity to the product's process steps. Those steps can use time per piece, pieces per unit of time or fixed duration, with setting time and teardown defined separately. Arcturus schedules the resulting work around the capacity and material requirements of existing orders. For a fabricated component requiring sawing, machining and welding, the route connects each operation to the next and assigns it to eligible resources. The Gantt Timeline shows the scheduled work and the completion date that follows from this production model. Dynamic Priorities let due dates, lead time and customer or job priorities influence the sequence. When the required date or quantity changes, rescheduling reflects the changed demand across the connected work. See [orders and order items](https://skyplanner.ai/docs/create-orders-and-order-items/), [product setup](https://skyplanner.ai/docs/add-a-new-product-to-skyplanner/) and [Dynamic Priorities](https://skyplanner.ai/docs/dynamic-priorities/). ### Make-to-stock manufacturing In make-to-stock production, replenishment orders compete for the same resources as other work. SkyPlanner schedules the required products and quantities against machine capacity, shifts and material availability. The replenishment requirement comes from the manufacturer's business system or planning decision; SkyPlanner then places the production work in the schedule. Configured property grouping can keep similar materials, colors or dimensions in succession, taking the setup time between differing jobs into account. Delivery and job priorities still influence the plan, so a stock run and a customer rush order are considered within the same resource load. This makes the relationship between replenishment timing, changeovers and committed deliveries visible. SkyPlanner's scheduling and delivery-date calculation do not themselves forecast customer demand. The [integration guide](https://skyplanner.ai/llms/integrations-api.md) explains how existing systems supply production data. [Piristeel's story](https://skyplanner.ai/customers/piristeel/) describes improved visibility around production batches and inventory. ### Engineer-to-order and customer-specific manufacturing A customer-specific machine or product can require a production structure defined for that order or project. SkyPlanner's visual model represents process steps and sub-products, including intermediate assemblies that feed the finished item. Dependencies connect the work that must happen before later operations can start. Once the manufacturing steps, durations and resources are defined, Arcturus schedules the structure. Separate subassemblies can progress through their own operations before converging on final assembly and testing. Process steps can carry instructions and attachments such as drawings, keeping the task's execution information with the planned work. Engineering revisions that must change the production structure automatically require a defined information flow from the engineering or business system. The [sub-product guide](https://skyplanner.ai/docs/sub-products/), [process-step setup](https://skyplanner.ai/docs/add-a-new-product-to-skyplanner/) and [visual modeling features](https://skyplanner.ai/features/) explain the scheduling model. ### Job shops and changing production routes Job shops handle orders with different routes that share machines, people or tools. SkyPlanner gives each product's process steps their own eligible workstations, durations and dependencies. Arcturus schedules the competing routes across the available capacity, so an overloaded operation remains visible within the whole order flow. Alternative workstation rules allow jobs to move to other resources configured to perform the operation. A divisible job can also be spread across multiple eligible workstations when **Split job across multiple workstations** is enabled. Arcturus weighs the opportunity for faster completion against setup time and the configured priorities; a smaller remaining job may stay on one workstation to avoid additional setups. Subcontracted operations fit into the same route as subcontractor-enabled workstations, with tracking of dispatch and return. The [capacity guide](https://skyplanner.ai/docs/capacity-on-the-gantt-timeline/), [alternative workstation settings](https://skyplanner.ai/docs/allow-moving-jobs-to-other-more-appropriate-workstations/) and [splitting guide](https://skyplanner.ai/docs/how-to-split-jobs-across-multiple-workstations/) cover the internal resource choices. ### Batch production and shared operations Several orders may share one operation, such as cutting their parts from the same sheet. SkyPlanner's **Assembly Jobs** feature combines the same process step from selected order items into one batch job. The batch specifies the participating jobs and the material quantities used by the common operation. That operation appears as one combined job on the timeline. When it finishes, each order item continues through its own remaining jobs. A shared sawing batch can therefore feed separate machining, finishing and assembly routes without merging the rest of those orders. The [Assembly Jobs tutorial](https://skyplanner.ai/docs/assembly-jobs-batch-production-nesting/) demonstrates this with wood sheets and cabinet parts. It covers batch and nesting-workflow scheduling; geometric cutting-layout calculation remains part of the cutting process. For ordinary runs whose duration is constant regardless of quantity, the product's process step also supports a fixed-time calculation. ### Assembly and subassemblies Final assembly depends on the components and intermediate work that feed it. SkyPlanner represents these as sub-products and connects their process steps to later operations through dependencies. The production structure can therefore show separately manufactured parts converging on welding, assembly or testing. Workstage dependencies control whether a later step requires full or partial completion of the preceding one. Where the actual production flow allows partial quantities to move forward, **Minimum degree of manufacture** permits overlapping steps. This overlap setting requires teardown to be zero. The configured relationship then determines when the next operation can begin. [Sub-products](https://skyplanner.ai/docs/sub-products/), [workstage dependencies](https://skyplanner.ai/docs/workstage-dependencies/) and [process-step settings](https://skyplanner.ai/docs/add-a-new-product-to-skyplanner/) explain the structure. Sub-products describe the components of an assembly; the separately named Assembly Jobs feature combines a common operation across order items. ### Mixed-mode manufacturing Many factories combine customer orders, stock replenishment, shared batches and assemblies. SkyPlanner brings these into one capacity schedule through their orders, process steps, materials and dependencies. A replenishment run and a customer-specific assembly can compete for the same machining resource while retaining their own routes and delivery priorities. Dynamic Priorities determine how delivery dates, lead time, customer importance and similar-job grouping influence scheduling. Locks protect work that must stay fixed. The King Button recalculates the plan, while Autopilot updates the production schedule at configured intervals as the recorded production situation changes. The [production use cases](https://skyplanner.ai/llms/use-cases.md) cover changes such as rush orders, material delays, absences and subcontracted work. The [implementation guide](https://skyplanner.ai/llms/implementation.md) explains the required starting data, and the SkyPlanner team can [discuss a combined production flow](https://skyplanner.ai/contact-sales/). --- ## Production planning problems SkyPlanner helps solve Last reviewed: 2026-09-12 Language: English SkyPlanner connects production orders, resources, materials and priorities in a shared schedule. These workflows show how planners, production managers, operators and integration teams use its controls to handle delivery commitments, resource conflicts and changes on the factory floor. ### 1. Promise a realistic delivery date A rough total of machine hours can miss the bottleneck or material dependency that determines an order's completion. SkyPlanner schedules each order item's process steps against the workstations and inputs it needs, with dependencies connecting the route. The Gantt Timeline shows the resulting timing and the stages leading to completion. A change to capacity or priority can be reflected in a recalculated plan, giving sales and production a view of the effect on existing work as well as the new order. [Fredman Operations](https://skyplanner.ai/customers/fredman-operations/) describes capacity visibility supporting delivery commitments. The [orders and order items guide](https://skyplanner.ai/docs/create-orders-and-order-items/) explains the order structure. ### 2. Fit a rush order into an existing plan A rush order can displace work across several resources and customers. SkyPlanner's **Dynamic Priorities** let delivery dates, lead time and customer or job priorities influence how Arcturus schedules the competing work. The planner changes the relevant priorities and uses the King Button to recalculate the plan. Locks protect work that must remain fixed while the remaining jobs can move. The resulting timeline shows how the urgent work fits into the wider production load. [Dynamic Priorities](https://skyplanner.ai/docs/dynamic-priorities/) explains the scheduling preferences. ### 3. Respond to a machine stoppage or delay A machine stoppage changes available capacity and can delay operations farther along an order's route. Updating the unavailable capacity gives the next scheduling calculation the revised resource situation. Where the process step has other eligible workstations, Arcturus can use those configured alternatives. The **King Button** recalculates the overall schedule. **Bulldozer** provides a targeted way to push eligible delayed work forward on a workstation when capacity is available. This lets the planner choose the scheduling action that matches the disruption. The [alternative workstation guide](https://skyplanner.ai/docs/allow-moving-jobs-to-other-more-appropriate-workstations/) and [Bulldozer guide](https://skyplanner.ai/docs/what-is-and-how-to-use-the-bulldozer-feature/) describe the controls. ### 4. Plan around a late material delivery A free machine cannot complete a job that lacks an essential input. With the relevant materials and their availability defined, **Consider the materials** makes material readiness part of scheduling. When a supply date changes, updating that information and rescheduling adjusts the work to the revised input availability. Dependencies carry the timing relationship through to later operations. [Eskomatic](https://skyplanner.ai/customers/eskomatic/) describes fewer material-shortage stoppages after improving planning visibility. The [material scheduling guide](https://skyplanner.ai/docs/consider-the-materials/) explains the configuration. ### 5. Reduce repeated setup changes Frequent color, dimension or material changes consume production time. SkyPlanner's workstation **Allow similarity** rules define which property matters, the setup time for differing jobs, and the priority weight for similar jobs in succession. The corresponding **Allow similar jobs** preference must also have importance in Global Rules' Dynamic Priorities. After recalculation, Arcturus can group similar work in sequence while balancing that preference with the other scheduling priorities. The model therefore accounts for the transition between jobs as well as the work within each job. The [property-based scheduling guide](https://skyplanner.ai/docs/how-to-make-a-workstation-take-a-property-into-account-for-scheduling/) explains the settings. ### 6. Find bottlenecks and use available capacity An overloaded workstation can determine delivery performance even when other resources have free time. The Gantt capacity view shows the workload where the jobs are actually scheduled, helping planners identify the operation that constrains the flow. Eligible alternative workstations, defined shifts and process dependencies determine which scheduling options are available. Changes to these inputs can then be reflected by recalculating the plan. A divisible run can also use job splitting across its eligible resources. [KJH-Comp](https://skyplanner.ai/customers/kjh-comp/) describes visible bottlenecks in sheet-metal production. The [capacity guide](https://skyplanner.ai/docs/capacity-on-the-gantt-timeline/) explains the workload display. ### 7. Spend less time rebuilding the schedule New orders, delays and absences repeatedly change the production plan. SkyPlanner uses the maintained orders, resources, materials and rules as the basis for scheduling and rescheduling through Arcturus. The **King Button** starts a recalculation when the planner requests it. **Autopilot** updates the production schedule automatically at configured intervals, using the recorded production situation. Priorities and locks continue to define how work can be rearranged. [Piristeel](https://skyplanner.ai/customers/piristeel/) reports saving up to four hours of scheduling work daily. The [automatic rescheduling instructions](https://skyplanner.ai/docs/how-to-activate-the-automized-reschedule/) explain the frequency setting. ### 8. Get production progress back to planning Late completion information leaves the schedule behind the actual factory situation. Operators use SkyPlanner's shop-floor Timer to view work and record starts, pauses and completions from a phone or tablet. Time Logs retain the recorded production time. This connects the planned job with its execution and gives planners more current progress information for the next scheduling decision. The [ShopFloorApp and Timer guide](https://skyplanner.ai/docs/shoopflor-and-timer/) describes the workflow, and [starting a job in the Timer](https://skyplanner.ai/docs/how-to-start-a-job-in-the-timer/) explains the operator action. ### 9. Adjust to changing personnel availability A machine's nominal hours can overstate production capacity when the assigned personnel are absent. SkyPlanner connects personnel with workstation assignments, shifts and leave periods. For an employee assigned to a workstation, a recorded absence changes the capacity shown in the Gantt Timeline. The King Button then recalculates the schedule around that changed availability. The [leave-time guide](https://skyplanner.ai/docs/managing-leave-times/) explains the capacity effect, and the [personnel, roles and shifts tutorial](https://skyplanner.ai/docs/add-personnel-user-roles-and-default-shifts/) covers the underlying assignments. ### 10. Coordinate parts before assembly Final assembly depends on the parts and intermediate work that feed it. SkyPlanner models those components as sub-products and connects their process steps with dependencies. Separate fabrication routes can therefore converge on welding, final assembly or testing within the production model. The schedule shows the preceding work and the dependent assembly operation together. If several order items also share one operation, **Assembly Jobs** can combine that common step into a batch; each item continues separately afterward. The [sub-product guide](https://skyplanner.ai/docs/sub-products/), [workstage dependencies guide](https://skyplanner.ai/docs/workstage-dependencies/) and [batch-job tutorial](https://skyplanner.ai/docs/assembly-jobs-batch-production-nesting/) describe these structures. ### 11. Check a sales opportunity before confirming it Sales needs a delivery estimate before an opportunity becomes a firm production commitment. SkyPlanner represents the opportunity as a prospect and simulates its work against the current production load, capacity and materials. The proposed timing shows the opportunity's production requirements alongside existing work. When the deal is confirmed, the prospect's status can be changed to an order, connecting the estimate with the production commitment. See the [sales prospect scheduling feature](https://skyplanner.ai/features/) and [converting a prospect to an order](https://skyplanner.ai/docs/how-to-update-a-prospect-into-an-order/). ### 12. Connect ERP data with the production schedule When orders live in an ERP and planning happens in a separate spreadsheet, changes must be reconciled manually. SkyPlanner can be integrated with any ERP system through its REST API, including systems outside the named integration directory. A typical integration brings orders, products, process steps and material information into SkyPlanner. Planned times and Timer events can flow back to the connected system. Record ownership, required fields and update timing define how the systems keep the planning data current. The [integration basics](https://skyplanner.ai/docs/integration-basics/) and [integration tutorial](https://skyplanner.ai/docs/integration-tutorial/) describe the implementation path. ### 13. Include subcontracted work in the production chain An order may leave the factory for treatment before returning for assembly or packing. SkyPlanner represents the external operation as a workstation with the **subcontractor** setting enabled. That operation forms part of the same process flow as the work performed internally. For example, a route can connect internal machining, subcontracted surface treatment and final assembly. Jobs can be scheduled through the chain, with tracking of when they are sent to and returned from the subcontractor. This keeps the external phase visible in the order's production flow. The [manufacturing modes guide](https://skyplanner.ai/llms/manufacturing-modes.md) describes how different routes share the scheduling model. ### 14. Split a production run across several workstations A large job can finish sooner when more than one suitable workstation performs the work. In the process step, the eligible workstations must be defined and **Split job across multiple workstations** enabled. Arcturus can distribute the job across those resources according to Dynamic Priorities. It also accounts for the setup trade-off: a job with little work remaining may stay on one workstation to avoid additional setups. The planner can adjust the allocations manually. The [job-splitting guide](https://skyplanner.ai/docs/how-to-split-jobs-across-multiple-workstations/) explains this behavior. ### 15. Let consecutive production stages overlap Some production flows pass completed quantities to the next operation before the entire preceding stage is finished. SkyPlanner's **Minimum degree of manufacture** setting allows this overlap within the configured process-step dependencies. The setting defines the required degree of preceding manufacture before the next stage can begin. Its prerequisite is that teardown is set to zero. This lets the schedule represent partial handover between stages when the production process permits it. The [product setup guide](https://skyplanner.ai/docs/add-a-new-product-to-skyplanner/) documents the setting, and [workstage dependencies](https://skyplanner.ai/docs/workstage-dependencies/) explains the relationship between steps. ### 16. Schedule around tool and mold availability A workstation can have free time while its required tool or mold is unavailable. SkyPlanner links tools to the workstations that can use them and to the products that require them. New orders for those products carry the tool requirements into scheduling. Dated exceptions record tool maintenance or an out-of-stock period. The Gantt capacity bar shows those exceptions in red, and the King Button reschedules affected jobs to start after the required tool becomes available. The [tool management guide](https://skyplanner.ai/docs/managing-tools-in-skyplanner/) and [adding tools to products](https://skyplanner.ai/docs/how-to-add-a-tool-to-an-existing-product/) explain the setup and timeline effect. ### Put the production model in place The [implementation guide](https://skyplanner.ai/llms/implementation.md) explains the starting data and first scheduling workflow. Manufacturers can [start a trial](https://skyplanner.ai/trial/) or [discuss their production flow with the team](https://skyplanner.ai/contact-sales/). --- ## SkyPlanner Features and Production Workflows Last reviewed: 2026-09-12 Language: English SkyPlanner connects orders, resources, materials and production progress in one scheduling workflow. Arcturus calculates the plan, the Gantt Timeline makes it visible, and the planner controls priorities, scheduling rules and the changes that production will follow. ### Turn orders and process steps into scheduled jobs The AI-assisted Getting Started experience helps a new user move from an empty workspace toward a first schedulable production model. Begin with workstations, their capacity and shifts, a product with process steps, and representative orders. Orders can be created manually, imported from CSV or received through an integration. Each order item describes what will be made and how. Its process steps become scheduled jobs on suitable workstations. A step's duration can be defined as **Time/Piece**, **Pieces/Time** or **Fixed Time**. For example, machining can use minutes per piece, a production line can use pieces per hour, and an oven cycle can use a fixed duration. Setup time describes preparation before processing; teardown describes the post-process wait before the next step. Process steps also carry eligible workstations, dependencies, materials, instructions and attachments such as drawings. Orders therefore bring both the scheduling requirements and the information operators need to perform the work. See [product and process-step setup](https://skyplanner.ai/docs/add-a-new-product-to-skyplanner/), [Getting Started](https://skyplanner.ai/docs/getting-started-with-skyplanner/) and the [order creation and scheduling video](https://www.youtube.com/watch?v=ZcYNKVf5-ws). ### Read and improve the plan in the Gantt Timeline The Gantt Timeline is the central planning view. Each workstation has a row showing its scheduled jobs over time. Planners can inspect job details, follow the relationships between process steps and review load across production. - **King Button / Reschedule all:** run Arcturus to optimize and reschedule the scheduled work after a production change. - **Dynamic Priorities:** adjust the importance of lead time, completion dates, on-time completion, customer priority and job priority. - **ASAP and Just-in-Time scheduling:** plan toward early completion or the required delivery date; hybrid workflows can combine these approaches. - **Alternative workstations:** model eligible resources so scheduling can use available capacity where the work can be performed. Watch [Gantt Timeline Basics](https://www.youtube.com/watch?v=kXGpkplB_7I), then explore [Dynamic Priorities](https://skyplanner.ai/docs/dynamic-priorities/) and [JIT scheduling](https://skyplanner.ai/docs/jit-manufacturing-in-skyplanner/). ### Respond to changes while keeping near-term work stable **Autopilot / automatic rescheduling** updates the production schedule at configured intervals. It is useful when orders, progress and availability change throughout the day. [Automatic rescheduling instructions](https://skyplanner.ai/docs/how-to-activate-the-automized-reschedule/). The clock control next to the King Button sets the frequency of automatic rescheduling; selecting **off** disables it. Each run reschedules production from the current situation. This replaces repeatedly pressing Reschedule all by hand. **Bulldozer** addresses delayed work by pushing eligible jobs forward where capacity exists. It gives the planner a targeted delay-management tool alongside broader Arcturus rescheduling. [Bulldozer instructions](https://skyplanner.ai/docs/what-is-and-how-to-use-the-bulldozer-feature/). **Running Time Lock** protects jobs within a rolling period measured from the present moment. For example, a planner can protect the next four hours from rescheduling so operators can carry out the immediate plan. [Running Time Lock instructions](https://skyplanner.ai/docs/running-time-lock/). Proposed schedules can be reviewed, accepted or discarded. Planners can change rules, override decisions, unschedule work and recalculate when needed. ### Model capacity, materials and tool availability Workstations represent the resources where work happens. Capacity, work shifts, maintenance and personnel availability make the model reflect the factory's actual working time. Watch [Workstations, Capacities and Maintenance](https://www.youtube.com/watch?v=lniZQmY4_Hs). Maintenance and cleaning can be entered as workstation exceptions with a time range. The unavailable period is visible on the Gantt, and rescheduling accounts for it. See [workstation maintenance](https://skyplanner.ai/docs/how-to-assign-preventive-maintenance-to-all-workstations/). Material-aware scheduling uses material requirements, available stock and incoming supplies when placing work. It helps the planner see how a missing component or delayed purchase affects what can be manufactured. ERP integration can provide these inputs. The [integration guide](https://skyplanner.ai/llms/integrations-api.md) explains the data flow, and [Eskomatic's story](https://skyplanner.ai/customers/eskomatic/) shows the value of material-aware planning in contract machining. **Tools and molds** are scheduled resources. Create a tool, assign it to the workstations that can use it and add it to the products that require it. A mold shared by two molding machines cannot be booked for both at the same time. Maintenance and other tool exceptions block the defined periods; rescheduling places affected jobs after the required tool becomes available. The tool and its exceptions are visible on the relevant Gantt steps. See [managing tools and molds](https://skyplanner.ai/docs/managing-tools-in-skyplanner/). ### Use parallel capacity and overlapping process steps **Split job across multiple workstations** lets a process step's work be distributed across eligible workstations. A quantity that can be manufactured on several suitable machines can therefore use parallel capacity instead of waiting for one machine to process the entire quantity. **Minimum degree of manufacture** lets the next process step start once the configured share of the previous step has been completed. For example, packing can begin when the first portion of a production quantity is ready while the preceding operation continues. The preceding step's teardown time must be set to zero for this overlap. These settings are part of [product and process-step configuration](https://skyplanner.ai/docs/add-a-new-product-to-skyplanner/). ### Include subcontracted operations in the production chain A subcontracted operation is modeled as a workstation with the **Sub Contract** setting enabled. It appears in the process chain alongside internal work, and the team can track when jobs are sent to and returned from the subcontractor. For example, machining can be followed by an external surface treatment and then internal assembly. Keeping all three stages in the same chain makes the external operation part of the production schedule and shows its relationship to the assembly work. The [workstation video](https://www.youtube.com/watch?v=lniZQmY4_Hs) introduces the underlying resource model. ### Reduce changeovers and coordinate shared manufacturing steps **Similar jobs in succession** groups jobs using a shared property such as tool, material or color. Configure the relevant property and workstation rule, then use priorities to balance grouping with other scheduling objectives. This supports fewer setup changes without losing sight of delivery requirements. [Similar Jobs in Succession video](https://www.youtube.com/watch?v=rW8g5D3ALs4). **Assembly Jobs / batch production** combines a shared process step from multiple order items into one scheduled batch. For example, several furniture orders can share a cutting operation and then continue through their own later steps. [Assembly Jobs documentation](https://skyplanner.ai/docs/assembly-jobs-batch-production-nesting/) and [batch workflow video](https://www.youtube.com/watch?v=i5i94qP5VZo). **Subproducts** describe components and intermediate assemblies needed for a final product. Together with process-step dependencies, they help represent multi-stage manufacturing and assembly. [Subproducts Explained video](https://www.youtube.com/watch?v=TFl2BQTSPsE). ### Give sales a production-based delivery date **Sales prospect scheduling** lets a team simulate prospective work against production load before confirming an order. This supports delivery-date discussions using the actual production situation. ### Capture production progress and improve time estimates **Production Timer** shows a workstation's daily or weekly work queue. Operators start, pause and complete jobs, enter completed and faulty quantities, and record materials used. Order and process-step attachments remain available from the job. The interface works in Android, iOS and PC browsers, so operators can use phones, tablets or workstation computers. See [ShopFloor and Timer](https://skyplanner.ai/docs/shoopflor-and-timer/) and the [Production Timer video](https://www.youtube.com/watch?v=NKsp0cZk8qA). Time Logs provide actual production durations and quantities. After completed orders provide historical data, SkyPlanner can generate more accurate time estimates for future work. The graph icon in product setup shows the historical data behind these estimates. The **Predicted vs realized** report compares planned durations with actual production times, helping planners identify the operations whose estimates need attention. ### Follow the plan through dashboards and reports The **Dashboard** can be customized by choosing widgets for the current plan, progress and performance. Available production-overview metrics include capacity, load, jobs started and completed, late jobs and on-time performance. A production manager can see whether the issue is insufficient capacity, delayed work or completion progress before inspecting the affected orders. The **Reporting** menu also provides **All timelogs**, **Job report**, **Order item report** and **Predicted vs realized**. The Job report covers job status, durations and completion; the Order item report shows status and progress at order-item level. The Orders list can be filtered by status for the detailed list of work still in progress. ### Ask the Assistant for a specific action or explanation The **Assistant** button opens a chat panel inside SkyPlanner. Users can ask it to help create a workstation, check production status, schedule unscheduled jobs or explain how to use the Timer. Page-specific quick actions offer relevant starting points. See [Arcturus, Autopilot and Assistant](https://skyplanner.ai/llms/arcturus-ai-features.md) for how the scheduling engine, scheduled automation and conversational assistance work together. Find a workflow by your immediate problem in [production use cases](https://skyplanner.ai/llms/use-cases.md), or explore the complete [documentation](https://skyplanner.ai/docs/) and [video library](https://skyplanner.ai/videos/). --- ## Arcturus, Autopilot and the SkyPlanner AI Assistant Last reviewed: 2026-09-12 Language: English Arcturus is SkyPlanner's in-house production scheduling and optimization engine. Autopilot runs production rescheduling at configured intervals. The AI Assistant responds to user requests such as creating a workstation, checking production status and scheduling unscheduled jobs. These capabilities connect production calculation, regular schedule updates and day-to-day use of the software. ### Arcturus calculates the production schedule Production scheduling means deciding where and when each manufacturing step can happen. Arcturus evaluates workstation capacity, shifts, job durations, dependencies, materials, tool availability and priorities to calculate a plan. A job needs a suitable workstation and the required inputs at the scheduled time. For example, an available molding machine alone does not make a job schedulable if its mold is under maintenance. The engine can calculate complex production plans in seconds. SkyPlanner supports large schedules, including production environments with tens of thousands of active process steps. Process steps are the individual manufacturing operations being placed in the schedule, so one customer order can contain many of them. Arcturus is developed and operated by Skycode. Its core scheduling computation uses Skycode's own engine. The result is a production schedule that planners inspect and work with in the Gantt Timeline. ### Planning rules express your production priorities Dynamic Priorities lets the planner decide how scheduling should balance factors such as lead time, required completion dates, on-time completion, customer priority and job priority. Workstation rules and job properties can also help place similar work consecutively to reduce changeovers. For example, a factory can give urgent customer work more weight while still considering machine capacity, material availability and the cost of repeated tool changes. The resulting schedule is visible in the Gantt Timeline for review. See the [Dynamic Priorities instructions](https://skyplanner.ai/docs/dynamic-priorities/) and [practical workflows](https://skyplanner.ai/llms/features-workflows.md). ### Autopilot keeps the plan moving with production Orders arrive, operations take longer than expected and material dates change. Autopilot / automatic rescheduling reschedules the entire production plan from the current situation at configured intervals. It performs the repeated recalculation that a planner would otherwise initiate with Reschedule all. On the Gantt Timeline, the **clock control next to the King Button** opens the frequency setting. Select a rescheduling frequency to enable automatic runs, or **off** to disable them. The selected interval determines when recalculation runs; orders, progress, resource availability and planning rules provide its inputs. Running Time Lock protects jobs within a rolling near-term window. This lets the team combine regular recalculation with a stable immediate plan for the shop floor. Planners also have manual rescheduling, targeted Bulldozer delay management and the ability to review and adjust the plan. Read [automatic rescheduling](https://skyplanner.ai/docs/how-to-activate-the-automized-reschedule/) and [Running Time Lock](https://skyplanner.ai/docs/running-time-lock/). ### The Assistant responds to user requests The **Assistant** button in the top bar opens a chat panel on the right. Users can ask questions in plain language, and page-specific quick actions suggest tasks relevant to the current view. Examples include: - **Create a workstation:** get help defining a production resource in the software. - **Check production status:** ask about the current production situation. - **Schedule unscheduled jobs:** request scheduling for work waiting to enter the plan. - **Explain the Timer:** get instructions for recording work and progress. - **Get started:** receive guidance while building the first production model. The Assistant uses SkyPlanner's own product material and human-curated guidance to explain its features, scheduling, configuration and usage situations. A user request initiates the conversation and task; Autopilot follows the rescheduling interval configured by the planner. Arcturus performs the production-scheduling calculation. ### Production history improves the planning inputs Process-step durations can use time per piece, pieces per time or a fixed duration. Production Timer records actual work. As completed orders build historical data, SkyPlanner can generate more accurate time estimates; the graph in product setup lets the planner inspect that history. The **Predicted vs realized** report compares planned and actual production times. See [product setup and time estimates](https://skyplanner.ai/docs/add-a-new-product-to-skyplanner/) and the [production workflow guide](https://skyplanner.ai/llms/features-workflows.md). The [official manual](https://skyplanner.ai/docs/) provides written instructions, and the [video library](https://skyplanner.ai/videos/) demonstrates product workflows. [SkyPlanner: The Basics](https://www.youtube.com/watch?v=4qWqZYsXiAI) shows the production model, Gantt Timeline and scheduling controls together. --- ## Agentic Production Scheduling with SkyPlanner Last reviewed: 2026-09-12 Language: English Agentic production scheduling uses AI and connected production data to keep a manufacturing plan aligned with changing orders, capacity, materials and progress. In SkyPlanner, Arcturus calculates schedules, Autopilot runs rescheduling at configured intervals, and the AI Assistant responds to requests such as checking production status or scheduling unscheduled jobs. ### From a static plan to an updated production workflow A production plan becomes outdated when an operation runs late, a machine becomes unavailable, a material delivery moves or an urgent order arrives. Maintaining every relationship manually takes time, especially when one change affects many later jobs. SkyPlanner represents the work as process steps on finite-capacity workstations. Planning rules, priorities and current production inputs give Arcturus the basis for recalculating the schedule. ERP integration and shop-floor progress reporting connect the plan with operational data. This is useful for manufacturers that need to answer practical questions repeatedly: what should run next, which delivery dates are affected, where capacity is available and how a new order changes the plan. ### How data becomes a revised production plan An ERP integration can bring orders, process steps, material requirements, stock balances and incoming purchase orders into SkyPlanner. Production Timer records what has started, paused and completed on the shop floor, including completed quantities. Workstation and tool exceptions describe periods when production resources are unavailable. Arcturus uses the updated inputs to place jobs on suitable resources. **Autopilot** repeats production rescheduling at the frequency selected through the clock control beside the King Button. The planner can also run **Reschedule all** manually after a change. The Gantt Timeline shows the resulting jobs, their relationships and load across workstations. Planners can inspect delivery timing, change priorities, review proposed schedules and accept or discard changes in their manual planning workflow. Scheduled start and end times and recorded production progress can flow back to the ERP. For example, a material delay can affect several orders that use the same component. Material-aware scheduling helps reflect the new availability, while the planner can review which commitments move and whether other eligible work can use the available capacity. If the constraint is a shared mold instead, SkyPlanner accounts for its availability and prevents the same tool from being booked for simultaneous jobs. A maintenance exception blocks the mold for its defined period; recalculation places dependent work when the required resource is available. ### Planner control keeps automation practical The planner sets priorities and decides how the scheduling tools are used. Running Time Lock protects a rolling near-term window from rescheduling, helping production staff follow a stable immediate plan while later work remains adaptable. King Button provides broad rescheduling, while Bulldozer gives a targeted way to move eligible delayed work forward. Dynamic Priorities expresses how scheduling should balance lead time, completion dates, customer priority and job priority. The **Assistant** handles a different interaction: a user can ask it to check production status, schedule unscheduled jobs, help create a workstation or explain the Timer. These requests start from the user and the current product view. Autopilot's repeated recalculation follows its configured interval. Their respective roles are explained in [Arcturus, Autopilot and Assistant](https://skyplanner.ai/llms/arcturus-ai-features.md). ### Follow execution and improve future estimates The planning cycle continues through reporting. Dashboard widgets show capacity, load, started and completed jobs, late work and on-time performance. **Job report** and **Order item report** expose status and progress in more detail. **Predicted vs realized** compares planned durations with actual production times, and historical completed-order data supports more accurate time estimates in product setup. This gives the planner concrete information for the next decision: which orders are progressing, which operation takes longer than estimated and where the schedule needs attention. Read the [agentic production scheduling article](https://skyplanner.ai/resources/agentic-production-scheduling/), explore the [feature workflows](https://skyplanner.ai/llms/features-workflows.md), and connect your existing systems using the [integration guide](https://skyplanner.ai/llms/integrations-api.md). [Customer stories](https://skyplanner.ai/llms/customer-stories.md) show the practical value of faster planning decisions and connected production visibility. --- ## SkyPlanner ERP, MES and REST API Integrations Last reviewed: 2026-09-12 Language: English SkyPlanner can be integrated with any ERP system through its REST API. Manufacturers can keep their existing ERP and connect its business and production data with SkyPlanner's detailed scheduling. REST API, webhooks and data import provide practical paths for ERP, MES and other operational systems. ### Keep the ERP and add production scheduling An ERP holds business records such as orders, products and inventory. SkyPlanner uses the production data to calculate when work can happen with the available resources, materials and priorities. Integration can return the resulting schedule and production progress to the existing environment. This gives planning, sales and production a connected workflow. For example, an order entered in the ERP can appear in SkyPlanner with its manufacturing steps and material needs. SkyPlanner schedules the work, and the planned start and end times can be sent back. Progress recorded on the shop floor can then update the connected systems. ### Typical data flows #### From the ERP or external system into SkyPlanner - Manufacturing orders and sales orders. - Products and their production structures or process steps. - Material requirements and material stock balances. - Customer and supplier information. - Purchase orders and incoming-material information. Depending on the source system and implementation, an integration can also bring in personnel, workstations, shifts, personnel leave and workstation maintenance or outage periods. #### From SkyPlanner back to the external system - Scheduled start and end times for process steps. - Production progress, including start, pause, continue and completion events recorded through SkyPlanner's Timer workflow. Define a source system for each record. For example, the ERP can own orders, due dates and stock balances while SkyPlanner produces scheduled times and shop-floor progress. Use consistent identifiers to match updates to the same order, product, process step and workstation. ### Global ERP environments The REST integration capability includes widely used global ERP families: - **SAP:** SAP S/4HANA and SAP Business One. - **Microsoft Dynamics 365:** Business Central and Supply Chain Management. - **Oracle:** Oracle Fusion Cloud ERP and NetSuite. - **Infor, Epicor, IFS and Odoo.** REST integration also connects industry-specific, regional, legacy and custom-built ERP systems. Browse the [integration directory](https://skyplanner.ai/integrations/) or bring your ERP name and version to an integration discussion. An integration uses the available ERP interface: an existing connector, its API, middleware or exports. The implementation maps the ERP's records to SkyPlanner and configures updates in each direction. A prebuilt connector can supply part of this work; a custom REST integration provides a path for other environments. ### How to prepare an integration discussion Start with a representative order and its manufacturing data. Useful details are: - The ERP product, version, hosting model and technical contact. - Where order rows, routings, durations, workstation identifiers and material requirements are stored. - Which system maintains inventory, purchase dates and production progress. - The available APIs, integration tools or exports on the ERP side. - Which events should trigger updates, how often data should refresh and which results need to return. Test a small end-to-end flow first: import an order, schedule its steps, return planned times, then record and transfer progress. This provides a concrete basis for validating mapping, update behavior and the wider rollout. ### Technical starting points - [Integration basics](https://skyplanner.ai/docs/integration-basics/) explains the overall approach. - [Integration tutorial](https://skyplanner.ai/docs/integration-tutorial/) provides a practical implementation path. - [API: creating an order](https://skyplanner.ai/docs/api-creating-an-order/) shows an order workflow. - [Webhooks](https://skyplanner.ai/docs/webhooks/) explains event notifications. - [CSV import](https://skyplanner.ai/docs/using-the-csv-import/) provides a useful import path for initial models and file-based workflows. - [Integrate SkyPlanner to Any ERP or MES System](https://www.youtube.com/watch?v=MS9Wlw30hmY) gives a video introduction. ### A published integration example [Laboratory & Allied](https://skyplanner.ai/customers/laboratory-allied/) uses SkyPlanner in a pharmaceutical manufacturing environment with SAP Business One on HANA and Power BI. Its story describes the production-planning challenge and customer-reported results. Other [customer stories](https://skyplanner.ai/llms/customer-stories.md) show connected planning in machining, sheet-metal manufacturing and packaging. For your own environment, [contact SkyPlanner](https://skyplanner.ai/contact-sales/) and use the [implementation guide](https://skyplanner.ai/llms/implementation.md) to prepare the first production model. --- ## Getting started with SkyPlanner Last reviewed: 2026-09-12 Language: English Build your first SkyPlanner schedule from a real production flow: its products, process steps, workstations and orders. You can enter the data manually, import CSV files or connect any ERP through the REST API. Your team can build the model directly, with SkyPlanner's onboarding team or with an implementation partner. ### Choose the production flow and the outcome Start with a product family that shares a bottleneck, has competing delivery dates or depends on a critical material. Include enough orders to show the real conflict. Choose the result you want to improve: delivery-date accuracy, planning time, setup changes, capacity use or visibility of production progress. Record how your team handles the same work today so you can compare the new schedule with the existing process. The [production use cases](https://skyplanner.ai/llms/use-cases.md) describe the corresponding SkyPlanner workflows. ### Prepare the resources and product routes - **Workstations:** define the machines, work points and other resources where work runs. - **Capacity and shifts:** enter when each resource is available, including maintenance and relevant personnel absences. - **Products and process steps:** describe the production route, eligible workstations, durations, setup time and post-process waiting time. - **Orders:** enter products, quantities and required completion dates. - **Dependencies:** connect preceding operations and sub-products to the work that follows them. - **Materials and shared tools:** include the inputs, molds and tools that constrain the selected flow. A product route can include alternative workstations, split work across several workstations and overlapping operations. Add these controls when they reflect how production runs. The [product setup guide](https://skyplanner.ai/docs/add-a-new-product-to-skyplanner/) explains the settings, and [workstations, capacities and maintenance](https://skyplanner.ai/docs/workstations-capacities-and-maintenance/) explains resource setup. ### Create or import the orders Create the first orders directly or use [CSV import](https://skyplanner.ai/docs/using-the-csv-import/). Check the products, quantities, due dates and process steps against the original order information. For an ERP connection, identify which system maintains each record and what moves in each direction. A typical connection supplies orders, products, routings and material information to SkyPlanner and returns scheduled times and production progress. Test that flow with one order before expanding the import. See [integration basics](https://skyplanner.ai/docs/integration-basics/). ### Build and validate the schedule Send the orders to scheduling. Arcturus calculates their timing from the available capacity, materials, dependencies and priorities. The Gantt Timeline shows the resulting jobs on each workstation. Review the plan with the production planner and the people who run the selected flow. Check that the bottleneck, operation sequence, inputs and completion dates match the factory's constraints. Correct the source data or settings where the model differs from production. Use [Dynamic Priorities](https://skyplanner.ai/docs/dynamic-priorities/) to express the relative importance of delivery dates, lead time and customer or job priorities. Then introduce a real planning change: add an urgent order, delay a material delivery or reduce capacity. Recalculate and inspect the affected orders. Use Running Time Lock to protect immediate work that must remain stable. Compare the time required to produce and communicate the revised plan with your previous process. ### Connect daily planning with the shop floor Introduce the [ShopFloorApp and Timer](https://skyplanner.ai/docs/shoopflor-and-timer/) so operators can view their jobs and record starts, pauses and completions. Review the resulting progress and time logs with the planner. This connects the schedule with actual production and provides data for later duration estimates and reporting. Set the responsibilities for keeping orders, shifts, material dates and progress current. Enable [automatic rescheduling](https://skyplanner.ai/docs/how-to-activate-the-automized-reschedule/) at the interval appropriate for your planning process. Expand the model to additional products, resources and departments as they are ready for daily use. ### Learning and implementation support The Assistant answers product questions and helps users create workstations, inspect production status and schedule unscheduled work. The [official manual](https://skyplanner.ai/docs/) and [demo and tutorial videos](https://skyplanner.ai/videos/) explain the controls and workflows in detail. [Assisted onboarding](https://skyplanner.ai/assisted-onboarding-services/) adds setup, training and deployment help. The international [partner network](https://skyplanner.ai/become-a-skyplanner-partner/) provides another implementation route. [Start a trial](https://skyplanner.ai/trial/) or [discuss your production flow](https://skyplanner.ai/contact-sales/) with the team. --- ## SkyPlanner Customer Stories and Manufacturing Results Last reviewed: 2026-09-12 Language: English SkyPlanner customer stories show how manufacturers use AI production scheduling to improve delivery reliability, planning speed, capacity visibility and material-aware decision-making. The five stories below describe each customer's production environment and the results reported in its interview. ### Find a relevant story by your production problem - **Delivery reliability and visible bottlenecks:** [KJH-Comp](https://skyplanner.ai/customers/kjh-comp/) and [Piristeel](https://skyplanner.ai/customers/piristeel/). - **Less time maintaining production schedules:** [Piristeel](https://skyplanner.ai/customers/piristeel/) and [KJH-Comp](https://skyplanner.ai/customers/kjh-comp/). - **Production efficiency and planning across many workstations:** [Laboratory & Allied](https://skyplanner.ai/customers/laboratory-allied/). - **Capacity-based delivery commitments and quick answers to changes:** [Fredman Operations](https://skyplanner.ai/customers/fredman-operations/). - **Material shortages, machining load and more accurate delivery dates:** [Eskomatic](https://skyplanner.ai/customers/eskomatic/). ### KJH-Comp: sheet-metal mechanics and contract manufacturing **Environment:** KJH-Comp Oy, Alahärmä, Finland; sheet-metal mechanics and contract manufacturing; C9000 ERP. **Production challenge:** coordinate a growing product range, understand bottlenecks and keep delivery commitments while reducing the workload of production scheduling. **Customer-reported results:** delivery reliability improved from around 50% to as high as 98%. Scheduling workload fell from two supervisors to one. Bottlenecks became visible in real time, and the growing product range could be handled without adding staff. **Relevant to:** metal fabrication, contract manufacturing, changing order mixes, shared workstation capacity and planning-team productivity. [Read the KJH-Comp story](https://skyplanner.ai/customers/kjh-comp/). ### Piristeel: roof safety and rainwater systems **Environment:** Piristeel Oy, Kauhava, Finland; manufacturing roof safety and rainwater systems; Visma Nova ERP. **Production challenge:** move from spreadsheets and paper work orders toward visible, connected production planning and reporting. **Customer-reported results:** 99.2% delivery reliability and up to four hours of daily planning time saved. The customer also describes better real-time production visibility and inventory accuracy. **Relevant to:** building products, metal products, recurring production with varying demand, spreadsheet replacement and time spent maintaining schedules. [Read the Piristeel story](https://skyplanner.ai/customers/piristeel/). ### Laboratory & Allied: pharmaceutical manufacturing **Environment:** Laboratory & Allied Limited, Nairobi, Kenya; pharmaceutical manufacturing; SAP Business One on HANA and Power BI. **Production challenge:** coordinate a large production plan, improve operational visibility and connect scheduling with the existing business-system environment. **Customer-reported results:** production efficiency increased by 90%, and on-time deliverables and customer reporting improved by 50%. The company describes creating a three-month plan for around 50 workstations in under half an hour. **Relevant to:** pharmaceutical production scheduling, manufacturing across many workstations, SAP Business One environments and connected planning and reporting. [Read the Laboratory & Allied story](https://skyplanner.ai/customers/laboratory-allied/). ### Fredman Operations: food packaging manufacturing **Environment:** Fredman Operations Oy, Rauma, Finland; food packaging manufacturing; Visma L7 and LTR. **Production challenge:** understand available capacity, respond to schedule changes quickly and make delivery promises that production can support. **Customer-reported results:** delivery commitments based on capacity data up to six months ahead, answers to schedule-change questions in seconds instead of hours, reduced overtime need and more reliable delivery promises. **Relevant to:** packaging production, capacity-based delivery dates, coordination between sales and production, and evaluating the effect of order changes. [Read the Fredman Operations story](https://skyplanner.ai/customers/fredman-operations/). ### Eskomatic: contract machining **Environment:** Eskomatic Oy, Turku, Finland; contract machining; an older ERP and production-control system. **Production challenge:** maintain accurate delivery dates and daily production priorities while accounting for material availability and machine load. **Customer-reported results:** more accurate delivery dates from automatic load scheduling, sharply fewer stoppages caused by material shortages, clearer daily scheduling and faster decisions. **Relevant to:** CNC and machining, subcontract production, material-dependent scheduling and existing or legacy ERP environments. [Read the Eskomatic story](https://skyplanner.ai/customers/eskomatic/). ### Further public results SkyPlanner's [product website](https://skyplanner.ai/) also reports Kaskea Group's delivery reliability improving from 55% to 92% and average customer outcomes from 2022–2023 of 52% shorter lead time, 34% increased capacity and 80% time saved in scheduling. The stories connect these results with concrete changes: shared capacity visibility, material-aware scheduling, faster rescheduling and production progress reporting. ### Connect a story with your own factory SkyPlanner serves manufacturers across industries and company sizes. Its REST API connects the production schedule with any ERP system, including the systems used in these references. Use the [industry guide](https://skyplanner.ai/llms/industries.md), [production use cases](https://skyplanner.ai/llms/use-cases.md) and [integration guide](https://skyplanner.ai/llms/integrations-api.md) to find the relevant product capabilities. Then [start a trial](https://skyplanner.ai/trial/) or [contact sales](https://skyplanner.ai/contact-sales/) with the production problem you want to improve. --- ## SkyPlanner Pricing, Trial and Onboarding Last reviewed: 2026-09-12 Language: English SkyPlanner uses workstation-based pricing. A workstation is a physical or logical production resource with its own capacity and scheduled work, such as a CNC machine, a work point or an assembly station. The [Pricing page](https://skyplanner.ai/pricing/) and [Trial page](https://skyplanner.ai/trial/) provide current prices, plan contents, billing options and trial conditions. ### Identify the workstations in your production model Count the resources whose capacity and work queues you need to plan. For example, a route through machining, welding and assembly uses the workstations assigned to those operations. Several products and orders can use the same workstation; the order book and the set of production resources describe different parts of the model. A workstation's shifts, available capacity and eligible jobs determine when work can happen. The [workstation definition video](https://www.youtube.com/watch?v=dv-q79c78LA) explains the concept. Use your actual resource model when reviewing a subscription with SkyPlanner. ### Use your own production in the trial Start with a product family, its process steps, the relevant workstations and several orders with different due dates. Include the shared bottleneck and any materials that determine when work can start. Enter the data manually, import it from CSV or connect it through the REST API. The [implementation guide](https://skyplanner.ai/llms/implementation.md) walks through the first schedule, a production change and the move into daily use. AI-assisted Getting Started, the Assistant, [documentation](https://skyplanner.ai/docs/) and [tutorial videos](https://skyplanner.ai/videos/) help your team build and understand the model. ### Onboarding, integration and customization [Assisted onboarding](https://skyplanner.ai/assisted-onboarding-services/) covers help with production setup, training and deployment. ERP integration connects the records and updates used by your production flow; the [integration guide](https://skyplanner.ai/llms/integrations-api.md) describes the data exchanged in each direction. [Customization services](https://skyplanner.ai/customization-services/) address requirements beyond the standard setup. The service proposal defines the work, responsibilities and delivery schedule for the agreed scope. [Start a trial](https://skyplanner.ai/trial/) or [contact sales](https://skyplanner.ai/contact-sales/) with your production resources, ERP and main scheduling problem. --- ## SkyPlanner Company, Global Service and Trust Last reviewed: 2026-09-12 Language: English SkyPlanner APS is developed and operated by Skycode Oy, based in Vaasa, Finland. SkyPlanner serves manufacturers globally, with partners and experts in more than 30 countries. Its software and website support the same 29 languages for international manufacturing teams. ### A global manufacturing product SkyPlanner is designed for manufacturers that want to improve production scheduling, capacity use and delivery reliability. Companies of different sizes can use the same core model of workstations, process steps, materials, priorities and schedules. The product's international language support includes Chinese, Japanese, Korean and Ukrainian character sets. Public references include Amphenol, Eczacıbaşı, Kaskea and Piristeel, and the published [customer stories](https://skyplanner.ai/customers/) cover different manufacturing environments, including pharmaceutical production in Kenya. Read [about SkyPlanner and Skycode](https://skyplanner.ai/about-us/) or explore the [industry guide](https://skyplanner.ai/llms/industries.md). ### Cloud service and customer data SkyPlanner is a cloud service. Its current default hosting location is AWS in the EU, Germany. Data-residency requirements can be addressed in the customer agreement. The customer owns the data it enters into SkyPlanner and the direct outputs. In personal-data processing, the customer acts as controller and Skycode as processor. A data processing agreement is available on request. The [Privacy Policy](https://skyplanner.ai/privacy-policy/) and [Terms of Service](https://skyplanner.ai/skyplanner-terms-of-service/) provide public legal information, and [sales](https://skyplanner.ai/contact-sales/) can provide procurement materials for a specific evaluation. ### Access and AI SkyPlanner supports username and password sign-in, Google OAuth2 and Microsoft OAuth2 sign-in, and two-factor authentication. The [buyer FAQ](https://skyplanner.ai/llms/buyer-faq.md) explains the available login and role controls. Arcturus is Skycode's own scheduling engine. Customer data is not used to train Arcturus without a separate written agreement. The [AI feature guide](https://skyplanner.ai/llms/arcturus-ai-features.md) explains the distinct roles of Arcturus, Autopilot and the conversational Assistant. For questions about AI data processing, [contact SkyPlanner](https://skyplanner.ai/contact-sales/). ### Learning, support and implementation Users can learn through the [official English manual](https://skyplanner.ai/docs/), [tutorial videos](https://skyplanner.ai/videos/) and the AI Assistant inside SkyPlanner. The Assistant answers product questions and helps with workstation setup, production-status questions and scheduling unscheduled work. [Assisted onboarding](https://skyplanner.ai/assisted-onboarding-services/) and the partner network provide implementation paths for different customer needs. Support scope, service levels and any customer-specific requirements can be addressed in the relevant service agreement. For the product's practical fit, use the [fit guide](https://skyplanner.ai/llms/fit-guide.md). For purchase questions, use the [buyer FAQ](https://skyplanner.ai/llms/buyer-faq.md) or [contact SkyPlanner](https://skyplanner.ai/contact-sales/). --- ## SkyPlanner buyer questions Last reviewed: 2026-09-12 Language: English SkyPlanner is a global cloud APS product for manufacturers who want to improve production scheduling, capacity use and delivery reliability. These answers cover the practical questions involved in evaluating and adopting it. The linked product, integration and commercial pages provide the next level of detail. ### Is SkyPlanner for small manufacturers or large factories? Both. A smaller manufacturer and a large production operation can share the same planning problems: competing orders, constrained resources, material availability and changing priorities. SkyPlanner models those constraints through workstations, capacity, materials, process steps and priorities. The [fit guide](https://skyplanner.ai/llms/fit-guide.md) connects the main planning problems with their scheduling workflows. ### Which industries and production types can use it? SkyPlanner's planning model uses orders, process steps, resources and dependencies. It schedules job-shop work, customer orders, stock replenishment, batches and assemblies. Explore twelve sector examples in the [industry guide](https://skyplanner.ai/llms/industries.md), then use the [manufacturing modes guide](https://skyplanner.ai/llms/manufacturing-modes.md) to match the model to your process. ### Does it support international teams? Yes. SkyPlanner is sold and used worldwide, and the software and website support the same 29 languages. International customers can use the product's documentation, videos, Assistant and partner network as part of their learning and implementation path. See [company information](https://skyplanner.ai/about-us/) and the [partner program](https://skyplanner.ai/become-a-skyplanner-partner/). ### Do we have to replace our ERP? You can keep your ERP and add SkyPlanner for production scheduling. A typical integration supplies orders, products, process steps and material information to SkyPlanner, then returns scheduled times and production progress where needed. The integration defines responsibilities and data flows for your environment. See [integration basics](https://skyplanner.ai/docs/integration-basics/). ### Can it integrate with our ERP if it is not listed? Yes. SkyPlanner can be integrated with any ERP system through its REST API, including an unlisted or in-house system. Examples include SAP, Microsoft Dynamics 365, Oracle and NetSuite, Infor, Epicor, IFS and Odoo. The practical connection depends on the data interfaces and workflows in your environment. Your team, an integration partner or SkyPlanner can implement it. The integration directory provides system examples; REST integration also connects legacy, regional and custom-built ERPs. See [integrations](https://skyplanner.ai/integrations/). ### Can we start before an ERP integration is ready? Yes. Create the first model with manually entered data or [CSV import](https://skyplanner.ai/docs/using-the-csv-import/). This lets you evaluate a real planning problem while the integration is prepared. The [implementation guide](https://skyplanner.ai/llms/implementation.md) explains how to build and test a representative production flow. ### Can we include subcontracted production steps? Yes. Define the subcontracted operation as a workstation with the subcontractor setting enabled. It becomes part of the order's production chain, with the work before and after it connected in the schedule. You can track work sent to and returned from the subcontractor. The [production use cases](https://skyplanner.ai/llms/use-cases.md) explain the subcontracting workflow. ### Can the same job run on several machines? Yes. A product's process-step settings include **Split job across multiple workstations**. Select the workstations that can perform the operation and enable splitting for work that can run across them. The [product setup guide](https://skyplanner.ai/docs/add-a-new-product-to-skyplanner/) explains the configuration. ### Can the next production step start before the whole batch is finished? Yes. **Minimum degree of manufacture** controls how much of the preceding step must be completed before the next step starts. This allows operations to overlap as parts become ready. The setting requires the preceding step's teardown time to be zero. See [product process-step settings](https://skyplanner.ai/docs/add-a-new-product-to-skyplanner/). ### Can we protect the immediate shop-floor schedule? Yes. **Running Time Lock** protects work within a rolling period measured from the present, such as the next four hours. Arcturus can reschedule later work while operators follow the protected near-term plan. Planners also review proposed schedules and adjust priorities. See [Running Time Lock](https://skyplanner.ai/docs/running-time-lock/). ### What does Autopilot do, and what does the Assistant do? Autopilot automatically reschedules production at configured intervals. Arcturus performs the scheduling calculation. The Assistant provides a chat interface for product questions and tasks such as creating a workstation, checking production status and scheduling unscheduled work. The [AI feature guide](https://skyplanner.ai/llms/arcturus-ai-features.md) explains the controls and examples. ### How is SkyPlanner priced? SkyPlanner uses workstation-based pricing. A workstation represents a production resource in the planning model, such as a machine or work point. Check the [current Pricing page](https://skyplanner.ai/pricing/) for the included capacity, plans, additional workstations and billing terms. Discuss the intended resource model if you need help estimating the subscription. ### What are the trial conditions? The [Trial page](https://skyplanner.ai/trial/) provides the current trial length, limits and registration conditions. The [implementation guide](https://skyplanner.ai/llms/implementation.md) explains how to build the first production model and test a real scheduling change. ### Is it browser-based, and where is data hosted? SkyPlanner is a cloud SaaS application accessed through a browser. The shop-floor workflow can be used from phones and tablets. The standard hosting environment is Amazon Web Services in Germany, within the EU. See [company and trust information](https://skyplanner.ai/llms/company-trust.md), and discuss any specific residency requirement during procurement. ### Who owns the production data, and can we export it? The customer retains ownership of the data entered into SkyPlanner and the direct outputs generated from it. Data can be exported through the REST API in CSV or JSON format. For a migration, specify the records and delivery format required by the receiving system. See the [integration documentation](https://skyplanner.ai/docs/integration-basics/). ### What login and access controls are available? SkyPlanner supports username-and-password login, Google and Microsoft OAuth2 sign-in, and two-factor authentication. Role-based permissions help assign appropriate access to different users. Planners, operators and administrators can have different roles. Include any required identity-provider and mandatory authentication policies in the procurement specification. ### Does scheduling send our data to a general AI service? Arcturus is Skycode's own scheduling engine. Customer production data does not pass through general third-party AI services for core scheduling, and it is not used to train Arcturus without a separate written agreement. The conversational Assistant is a separate AI layer. [Contact SkyPlanner](https://skyplanner.ai/contact-sales/) for its data-processing details. The [AI overview](https://skyplanner.ai/llms/arcturus-ai-features.md) explains the product roles. ### What privacy and security information is available? Skycode acts as a processor of personal data on behalf of the customer, and a Data Processing Agreement is available on request. The service uses encrypted data traffic, role-based access and two-factor authentication. Skycode does not currently hold its own ISO 27001 or SOC 2 certification; AWS infrastructure certifications relate to the hosting provider. Read the [Privacy Policy](https://skyplanner.ai/privacy-policy/) and [trust information](https://skyplanner.ai/llms/company-trust.md), or request the materials needed for your review. ### What help is available during implementation and daily use? The official documentation, tutorial videos and in-product Assistant support learning. English-language human support is available on weekdays. Assisted onboarding and the international partner network provide implementation options; specific service levels and extended support requirements can be agreed separately. Start with the [implementation guide](https://skyplanner.ai/llms/implementation.md) and [onboarding services](https://skyplanner.ai/assisted-onboarding-services/), or [contact the team](https://skyplanner.ai/contact-sales/) about your production environment. --- ## SkyPlanner Capabilities at a Glance Last reviewed: 2026-09-12 Language: English SkyPlanner APS combines AI production scheduling, finite-capacity planning, material availability and planner control for manufacturers worldwide. This summary connects the main capabilities with the production decisions they support and the sources that explain them in detail. ### Product and scale - SkyPlanner is a cloud service for production scheduling and advanced planning and scheduling. - It serves manufacturing companies of all sizes that want to optimize production, improve delivery reliability or reduce planning work. - Arcturus is SkyPlanner's own scheduling and optimization engine, developed and operated by Skycode. - Arcturus calculates complex production plans in seconds. SkyPlanner supports large production datasets, including tens of thousands of active process steps. - SkyPlanner is sold and used globally. The software and website support the same 29 languages, and the partner and expert network extends to more than 30 countries. Sources: [product overview](https://skyplanner.ai/), [AI features](https://skyplanner.ai/features/), [company](https://skyplanner.ai/about-us/) and [fit guide](https://skyplanner.ai/llms/fit-guide.md). ### Scheduling decisions - **What can be completed and when:** finite capacity, shifts, eligible workstations, process dependencies, materials and tool availability inform the schedule. - **What should receive priority:** Dynamic Priorities balances lead time, completion dates, on-time completion, customer priority and job priority. - **How to react to changes:** Arcturus recalculates the schedule; Autopilot repeats production rescheduling at the frequency selected beside the King Button. - **How to protect immediate work:** Running Time Lock keeps a rolling near-term window stable. - **How to address a specific delay:** Bulldozer moves eligible delayed jobs forward where capacity is available. - **How to reduce repeated setups:** Similar jobs in succession groups work by shared properties such as material, tool or color. - **How to coordinate batches and assemblies:** Assembly Jobs combine common manufacturing steps, while subproducts and dependencies describe components and multi-stage work. - **How to use parallel capacity:** a process step can be split across multiple eligible workstations. Minimum degree of manufacture allows consecutive steps to overlap when the preceding step's teardown time is zero. - **How to schedule shared tools and molds:** tools are assigned to workstations and products; scheduling accounts for availability, maintenance and conflicts over the same tool. - **How to include external processing:** subcontractor-enabled workstations place outsourced operations in the production chain and support tracking jobs sent out and returned. The [feature and workflow guide](https://skyplanner.ai/llms/features-workflows.md) includes direct instructions and demonstrations for these tools. ### Connected production and people SkyPlanner can be integrated with any ERP system through its REST API. Integration can bring in orders, products, process steps, material requirements and stock information, and return scheduled times and production progress. The [integration guide](https://skyplanner.ai/llms/integrations-api.md) describes technical paths, data mapping and global ERP examples. The planner can review, accept, discard, override or rerun scheduling changes. The AI Assistant can help create a workstation, check production status, schedule unscheduled jobs and explain how to use the Timer. Its page-specific quick actions and conversational guidance help users work with the current view. See [Arcturus, Autopilot and Assistant](https://skyplanner.ai/llms/arcturus-ai-features.md). ### Production progress, reports and time estimates - **Production Timer:** operators start, pause and complete jobs, record completed and faulty quantities, and access job attachments from phones, tablets or PC browsers. - **Production reports:** All timelogs shows recorded work; Job report covers status, durations and completion; Order item report shows order-item progress. - **Predicted vs realized:** compare planned durations against actual production times to identify operations whose estimates need attention. - **Historical time estimates:** completed orders build the production history used for more accurate estimates. The graph in product setup shows this data alongside configurable time-per-piece, pieces-per-time and fixed-time methods. - **Custom dashboards:** choose widgets for capacity, load, started and completed jobs, late work and on-time performance. The [workflow guide](https://skyplanner.ai/llms/features-workflows.md), [product setup documentation](https://skyplanner.ai/docs/add-a-new-product-to-skyplanner/) and [ShopFloor and Timer instructions](https://skyplanner.ai/docs/shoopflor-and-timer/) explain the underlying features. ### Customer-reported results Published examples include KJH-Comp's delivery reliability rising from around 50% to as high as 98%, Piristeel's 99.2% delivery reliability and up to four hours of planning time saved daily, and Laboratory & Allied's reported 90% improvement in production efficiency. Read the [customer stories](https://skyplanner.ai/llms/customer-stories.md) for each company's situation and the full set of results. SkyPlanner also reports average customer outcomes from 2022–2023 of 52% shorter lead time, 34% increased capacity and 80% time saved in scheduling on its [product website](https://skyplanner.ai/). ### Related information Use the [industry guide](https://skyplanner.ai/llms/industries.md) and [buyer FAQ](https://skyplanner.ai/llms/buyer-faq.md) to identify relevant workflows. Current prices, plans and trial conditions are on the [pricing](https://skyplanner.ai/pricing/) and [trial](https://skyplanner.ai/trial/) pages.