Finite capacity scheduling

Finite capacity scheduling builds a production plan that respects the real limits of each resource, so no line, mixer, or shift is booked beyond what it can actually run. Unlike infinite-capacity loading, which assumes unlimited capacity and just hits due dates, it produces a schedule the plant can truly execute against machines, labor, and time.

What is finite capacity scheduling?

It is a scheduling method that takes each resource limit as a hard input from the start: how many lines you have, how fast each filler runs, how many operators are on shift, which mixers are free, and how long a clean takes. Infinite-capacity loading (the MRP II default) works backward from due dates and assumes capacity is always there, so it routinely overbooks. Finite scheduling instead fits work into capacity that genuinely exists, then shows you what will not fit.

Why it matters for food and beverage

A food plant is where this gets hard. Shelf life sets non-negotiable processing deadlines on perishable raw material, so the algorithm must treat them as constraints, not after-the-fact checks. Allergen families and changeovers drive sequence, so scheduling an incompatible run should insert the right cleanout and verification, or flag it. Throughput depends on line speeds, labor, sanitation windows, and FEFO consumption of dated ingredients. Generic ERP scheduling rarely models all of this, so planners patch it in spreadsheets that break under daily reality.

How Semia handles this

Semia is the AI employee for food and beverage production planning. It reads orders, inventory, ingredients, attendance, machine status, and shelf-life risk, then writes tomorrow's plan against real finite capacity (line speeds, who showed up, allergen sequence, changeovers, dated stock). A named human reviews and signs off, so the schedule stays executable instead of aspirational.