Say goodbye to Excel scheduling and gut-feel decisions by supervisors. The SBK APS engine simultaneously weighs six constraints — equipment capacity, operator skills, material readiness, tooling & fixtures, operation priority and customer due dates — generating executable schedules in seconds, lifting capacity utilization by 20% and on-time delivery by 15%.
A hybrid scheduling approach combining CSP constraint programming + heuristic algorithms + a rules engine
Weighted across multiple objectives — due-date attainment / equipment utilization / changeover loss / WIP inventory / overtime hours — with switchable strategies such as "rush-delivery mode" or "efficiency-boost mode"
A VIP rush order triggers an incremental APS reschedule that minimizes disruption to the existing plan, with affected work orders automatically flagged to the scheduler
Three Gantt perspectives — equipment, work order and operation; supports drag-and-drop manual fine-tuning with instant constraint-conflict validation
Generate N scheduling scenarios from the same batch of work orders, compare them on a KPI radar chart, and release the optimal one to the shop floor in one click
A dozen-plus rules such as EDD (earliest due date first), SPT (shortest processing time first), Critical Ratio and customer priority can be combined and configured
Automatic rescheduling on a daily / shift cadence, dynamically adjusting future plans based on the latest reporting progress, material arrivals and equipment status
Constraint dimensions
A real factory's capacity isn't a simple number. A CNC machine produces entirely different output depending on whether it's staffed, whether tooling is available, and whether the previous job has just finished or is still in changeover. APS models all these dynamic constraints.
The engine's plan is a recommendation; the scheduler's on-floor experience remains invaluable. The Gantt chart lets you drag operations to different machines, adjust start times and pin the sequence of critical work orders, with instant constraint-conflict validation after each change.
Scenario B key KPIs
Facing a batch of work orders, "which to run first, which to run later" has different optimal answers. APS lets you generate N scenarios (rush delivery, preserve efficiency, preserve quality, preserve cash flow), then choose and release one after an intuitive KPI radar-chart comparison.
With OEM daily rolling demand + a 2-hour delivery window, APS back-schedules to the minute to guarantee 100% on-time delivery
10 injection machines, 80 molds, 30 customers — APS automatically schedules by mold occupancy and minimized changeover time
30 models/day — APS schedules by placement-program reuse, cutting changeovers from 30 down to 12
Scheduled by "line-clearing difficulty," running similar recipes consecutively to minimize cleanup loss
APS is the brain of MES — work order, process, material and equipment data all converge here
Work orders are APS inputs; rush orders trigger an incremental reschedule
MRP material-calculation results drive APS material-readiness constraints
Process routing + standard hours are the logical foundation of scheduling
APS scheduling results directly generate operation dispatch cards
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