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APS Advanced Scheduling

APS Advanced Planning & Scheduling · Finite-Capacity Multi-Constraint Scheduling

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%.

Constraints Weighed Simultaneously

20%

Higher Capacity Utilization

<30s

Hundreds of Work Orders Scheduled in Seconds

Capabilities

Core Capabilities of the APS Engine

A hybrid scheduling approach combining CSP constraint programming + heuristic algorithms + a rules engine

🎯 Multi-Objective Optimization

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"

⚡ One-Click Reschedule for Insertions / Rush Orders

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

📊 Gantt Visualization

Three Gantt perspectives — equipment, work order and operation; supports drag-and-drop manual fine-tuning with instant constraint-conflict validation

🔍 What-If Scenario Comparison

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

📝 Configurable Scheduling Rules

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

🔄 Rolling Reschedule

Automatic rescheduling on a daily / shift cadence, dynamically adjusting future plans based on the latest reporting progress, material arrivals and equipment status

mes.shangbangke.com/aps/constraintEngine ready

APS Constraint Modeling

ValidateRun Schedule

38Machines

126Skill matrix

92%Material ready

54Tooling

Constraint dimensions

DimensionRuleStatus

EquipmentCapacity curve + changeover + calendarActive

PersonnelSkill matrix + shift + overtime capActive

MaterialReadiness + lead time + safety stockChecking

ToolingMold / fixture / jig conflict checkActive

Model Every "Dynamic Constraint" on the Floor into the Engine

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.

Equipment dimension: capacity curves, availability calendars, maintenance plans, changeover matrices
Personnel dimension: skill matrix, shift attendance, overtime caps, cross-workshop scheduling
Material dimension: readiness checks, procurement lead times, safety-stock policies
Tooling dimension: mold / fixture / jig occupancy, with conflict avoidance

mes.shangbangke.com/aps/ganttDrag to schedule

Equipment Gantt — Week 21

Day viewRelease plan

CNC-01

WO-2041 ×1200

WO-2055 ×640

CNC-02

WO-2043 ×900

Changeover

INJ-02

WO-2049 ×3000

WLD-01

Full-load 24h ⚠

ASM-01

WO-2060 ×500

Gantt-Chart Scheduling — Adjust with a Mouse Drag

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.

Equipment Gantt: which job each machine is running in each time slot
Work-order Gantt: the timeline of all operations for each work order
Bottleneck highlighting: red alert for machines running full-load for 24h straight
Drag to recompute: affected work orders auto-cascade after each adjustment

mes.shangbangke.com/aps/what-if3 scenarios

What-If Comparison

Re-simulateSelect & release

ScenarioOn-timeUtilizationOvertimePick

A Rush100%91%80hHigh cost

B Efficiency96%97%12hRecommended

C Cash88%84%0hDeferred

Scenario B key KPIs

96Due

97Util

88OTD

72WIP

64Stock

What-If: Decide by Comparing Scenarios

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.

Scenario A: scheduled by due date, 80 overtime hours
Scenario B: scheduled by efficiency, 2 work orders delayed by 1 day
Scenario C: preserve cash, prioritize key accounts, smaller customers delayed 3 days
KPI radar-chart comparison + management sign-off before release

Use Cases

APS in Action Across Different Manufacturing Modes

Auto-Parts JIT On-Time Scheduling

With OEM daily rolling demand + a 2-hour delivery window, APS back-schedules to the minute to guarantee 100% on-time delivery

Injection-Molding Tooling Schedule

10 injection machines, 80 molds, 30 customers — APS automatically schedules by mold occupancy and minimized changeover time

SMT High-Mix Low-Volume

30 models/day — APS schedules by placement-program reuse, cutting changeovers from 30 down to 12

Food Line Daily Batch Scheduling

Scheduled by "line-clearing difficulty," running similar recipes consecutively to minimize cleanup loss

Related Features

How APS Connects with These Capabilities

APS is the brain of MES — work order, process, material and equipment data all converge here