Match Near-Expiry Ingredients to Suitable Production Orders—with Less Manual Checking

If your planners cross-check expiry lists against quality records and production orders every morning, start by automating the preparation of that decision. A focused ingredient-matching workflow can assemble eligible combinations for review, with the aim of reducing manual lookups while leaving material use and scheduling with production planning and quality assurance.

An ingredient-matching workflow is a process that connects material lots to production requirements and prepares eligible combinations for review. Software assembles the evidence and applies agreed rules; your team decides what to use. FAIS would build the business ontology—the shared definitions and relationships—and connect workflow automation to your existing records. The practical benefit is a review queue that brings the relevant evidence together instead of requiring planners to reconstruct it for each lot.

Replace repeated lookups with a reviewable match

Consider an illustrative Taiwan food manufacturer using a short-life fruit preparation in several products. A planner sees a lot approaching expiry, opens the stock export, checks its quality release, looks up the relevant formula and searches pending production orders. Before proposing its use, the planner must also establish whether the quantity is already reserved.

With a connected workflow, the planner would open a queue showing candidate orders alongside the lot's available quantity, expiry, quality status and applicable formula version. Each field should link to its source record and show when it was retrieved. The work shifts from gathering those records to reviewing whether the match is suitable.

Taiwan's SME e-learning platform provides relevant manufacturing context. Its food-manufacturing course, listed on 17 January 2025, covers raw-material management, expiry management and production scheduling—the connected concerns behind this proposed workflow. Official course page

Connect the records without confusing their roles

The shared business model should relate the ingredient to its lots, each production order to its applicable formula, and each lot to its quality record. Those objects remain distinct: a formula specifies requirements, while a lot represents particular stock that may or may not meet them.

FAIS would model those relationships and connect workflow automation to the records behind them. Suitable connectors and consistent identifiers are still necessary. The aim is to make matching rules reusable across the selected orders rather than ask a language model to reconstruct the relationships each time.

The same foundation can reduce repeated integration work later. FAIS can connect future workflows and agents to the mapped business relationships and approved rules, reusing suitable connectors instead of recreating each integration. You build on existing software while giving subsequent automations a consistent business context.

An unreleased lot should appear as an exception for quality review, not as usable stock. An order requiring a different ingredient should be excluded unless an authorized substitution process resolves it. If eligible orders compete for the same quantity, the queue should expose that conflict rather than recommend the stock twice.

Why not just use the earliest-expiring lot?

Expiry is a priority, not the whole eligibility decision. Microsoft's shelf-life planning documentation considers availability and demand timing alongside first-expire, first-out priorities. Its batch-disposition documentation separately describes controls governing availability for planning and production-related operations. Shelf-life planning · Batch availability

Formula selection also needs an explicit check. In Dynamics 365, formula versions can depend on effective dates and quantities, and formulas and versions require approval before planning and production use. These controls illustrate why matching should use the applicable approved version rather than an ingredient name alone. Formula versions

Quality assurance should define the relevant expiry checkpoint and conditions for opening, storage, substitution and finished-product shelf life. Encode those approved conditions before ranking candidates.

Give each step a clear owner

The workflow should separate evidence preparation from operational authority:

Stage	Responsibility
Connect records	Integration software imports lot, stock, quality, formula and order records using consistent identifiers.
Check eligibility	Rules evaluate the records and route missing or conflicting evidence to an exception queue.
Prepare recommendations	AI summarizes eligible matches, source references and unresolved questions.
Authorize action	Production planning and quality assurance approve use and scheduling within their respective responsibilities.

AI should explain rule results, not invent a release status or approve a substitute. Recheck stock and quality status before an approved recommendation becomes an operational instruction.

Can you start without replacing the ERP?

A bounded pilot can begin with exports if they contain sufficiently current, consistent records. Confirm identifiers, units, reservations, formula versions and quality-update frequency before selecting connectors. Use sample data to test the matching rules before committing to deeper integration.

Start with one short-life ingredient and its corresponding orders. Measure manual lookup time and record why reviewers change recommendations. Track expiry-related disposal alongside production volume and product mix, treating it as an outcome to investigate rather than an automatic measure of AI's contribution.

Your first decision is whether the available records can justify a suitable match. If the obstacle is connecting those records and making the rules consistent, that is a concrete reason to discuss FAIS's ontology and custom automation work: less repeated evidence gathering, with a reviewable basis for the planner's decision.