GlossaryScheduling Concepts

    Finite Capacity Scheduling

    Definition

    Finite capacity scheduling is the practice of sequencing manufacturing work orders against the actual, limited capacity of each resource — machines, operators, tooling, fixtures, and outside processing — rather than against an assumed unlimited capacity. Every operation is placed in a time slot only if the resource is genuinely available, so the resulting schedule reflects what the floor can actually run, not what the planner wishes it could run.

    Why it matters

    Most ERP schedules use infinite capacity and quietly overload bottleneck work centers by 20–40%. Operators then resequence by hand, planners chase status, and on-time delivery collapses below 70%. Finite capacity scheduling forces the planning system to confront the real constraint, which is the single biggest lever for moving OTD from the 60s into the 90s without buying new machines.

    Common failure mode

    A planner releases 80 hours of work to a work center that has 40 hours of capacity this week. The ERP accepts it. Operators silently pick whatever runs fastest. Hot jobs are missed, setups balloon, and Friday becomes a firefight. The schedule looks fine in the system and broken on the floor.

    How Skody approaches it

    Skody runs a finite capacity model that includes machine state, labor coverage, tooling, pallets, and outside processing. Any operation that cannot fit is surfaced as an at-risk job with the specific constraint named, so planners can act before the shortfall reaches the floor.

    Questions

    Infinite capacity scheduling assumes any work center can absorb any amount of work, so it just adds operations to the calendar. Finite capacity scheduling refuses to overload a resource: if the next free slot on a machine is Thursday, the operation is placed on Thursday, not today. Finite is the only model that produces a schedule the floor can actually execute.

    Most ERPs (NetSuite, Epicor, JobBOSS, Global Shop, E2, ProShop) ship with infinite capacity scheduling by default. Some have an optional APS module that adds finite capacity, but it usually runs once per shift on a static snapshot — meaning the schedule is already wrong by the time operators see it.

    For discrete manufacturers, plan at the work center or machine level, in increments no larger than the average operation length (typically 15–60 minutes). Bucketing by day hides the bottleneck. Bucketing by week makes the schedule useless for dispatching.

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