# AI for Epicor Mattec MES: Press Data, Scrap and Mold History in Plain English > Source: https://netray.co/erp-ai/epicor-mattec-mes-ai-integration > Publisher: Netray (netray.co), AI and integration engineering for ERP and manufacturing systems. > Section: AI for ERP ## Short answer AI for Epicor Mattec MES connects a private language model to the MES database so plant managers and process engineers can ask about press downtime, scrap by reason, cycle time drift and mold performance, with the query shown. Joined to ERP orders and costs, it runs on-prem next to the MES, which is often hosted on a plant SQL Server. ## Kind platform ## Erp Family mfg-systems ## Erp Products - Epicor Mattec MES ## Industries - Plastics - Injection Molding - Automotive - Medical Devices ## Region Global ## Persona Plant Manager ## Eyebrow Mattec MES + private AI ## Intro Mattec MES, now part of the Epicor portfolio, is widely used by injection molders and other process-oriented plants for press monitoring, downtime and scrap capture, production tracking, and mold and tool management. The data model is built around machines or presses, jobs, cycles, downtime events, scrap events and tooling. Plastics plants run on thin margins and long production runs, so small changes matter. A slow cycle on a high-volume mold, a recurring flash defect, or an unrecorded changeover compounds over thousands of shots. The monitoring data to detect these is already in the MES, but few people have the time to mine it. The built-in reports are good for known questions: efficiency by press, scrap by reason, downtime by code. The questions that cost money are different: why does this mold run slower on press 7 than press 3, which resin lots correlate with scrap, and what does the ERP say we should have made last week against what the MES recorded. This page covers how a private AI layer can sit next to Mattec MES and the ERP, which data it needs, how to keep it read-only, and where the standard Mattec reports and Epicor tools remain the better choice. ## Pain Points ### Scrap reasons are recorded but rarely analysed together **Detail:** Scrap codes, press, mold, material lot and shift sit in different tables and reports. Linking a defect pattern to a resin lot or a mold revision requires manual joining that happens only after a customer complaint. ### Mold and tool knowledge is tribal **Detail:** Which molds need a specific press, which cavities are blocked, and which maintenance was done last are known by a few setters and toolroom staff and are not easy to retrieve quickly. ### Cycle time drift goes unnoticed **Detail:** A cycle that creeps up by a fraction of a second across a long run is invisible on a daily summary but material over a month; detecting it needs trend analysis per mold and press. ### MES and ERP disagree on counts **Detail:** Good parts, scrap and material consumption in the MES differ from ERP production reporting, particularly when operators correct counts late. ### Regulated customers expect traceability **Detail:** Medical and automotive customers expect lot and process records on demand, which stretches a small quality team during a complaint. ## Use Cases ### Scrap analysis by mold, press and lot **Description:** Ask which scrap reasons rise on a given mold or after a resin lot change and get a breakdown with the data behind it. **Erp Objects:** Scrap events and reasons, jobs, molds, presses; ERP material lot receipts **Outcome:** Faster identification of material or tool related defects, shortening the time between first occurrence and corrective action. ### Cycle time drift detection **Description:** Compare current cycle time with the standard and the historical median per mold and press, and flag sustained drift. **Erp Objects:** Cycle records, standard cycle on job or part, press IDs **Outcome:** Earlier notice of issues such as cooling or hydraulic problems; flagged items need a technician to confirm. ### Downtime Pareto and changeover review **Description:** Rank downtime by reason and compute changeover duration by mold family, highlighting the outliers. **Erp Objects:** Downtime events and codes, job start and end times, mold change records **Outcome:** A targeted SMED focus list instead of a general call to reduce changeovers. ### MES to ERP production reconciliation **Description:** Compare good quantity, scrap and material usage in the MES against ERP production postings and list the jobs that disagree. **Erp Objects:** MES job production totals, ERP job or production order receipts and issues **Outcome:** Month-end variance investigation becomes a short exception list. ### Mold maintenance history lookup **Description:** Retrieve shots since last maintenance, repair history and known cavity issues for a mold before it is scheduled. **Erp Objects:** Mold records, shot counters, maintenance notes, ERP asset or tooling records **Outcome:** Setters and schedulers avoid starting a job on a mold that is overdue for service. ### Customer complaint traceability pack **Description:** Given a part and date range, assemble jobs, presses, molds, material lots and operators involved, for a quality engineer to review. **Erp Objects:** Job history, lot records, process data, shipment lines **Outcome:** Complaint response preparation shrinks from a day of gathering to a review of one assembled pack. ### Shift and plant summary **Description:** Draft a daily summary of efficiency, scrap hot spots and jobs behind schedule for the production meeting. **Erp Objects:** Efficiency metrics, open jobs, due dates **Outcome:** Meeting preparation time falls, with the summary reviewed before circulation. ## Architecture **Overview:** The AI layer reads a replica or reporting copy of the MES database, aligns it with ERP jobs and lots through the ERP's APIs, and uses a locally hosted model that queries curated views and cites its sources. **Layers:** #### Data access **Detail:** Read-only access to a copy of the MES SQL database, scheduled so analytical queries do not affect press monitoring. #### Semantic layer **Detail:** Business-term views for press, mold, job, cycle, downtime and scrap, with metric definitions such as efficiency or good-part yield fixed once. #### ERP join **Detail:** Mapping of MES job numbers and part numbers to Epicor or other ERP jobs, items and lots, using ERP APIs for reads. #### Model serving **Detail:** An open-weight model hosted on a plant or data center GPU, using tool calls to query views instead of recalling facts. #### Controls **Detail:** Query display, role scoping by plant, logging, and human approval before any change to ERP or MES data. ## Deployment Options ### Plant on-prem **Fit:** Molders with the MES hosted locally **Detail:** GPU server beside the MES SQL Server on the plant network, with no external model calls. ### Central private cloud **Fit:** Multi-plant molders **Detail:** Replicated MES data from each plant lands in one analysis environment, scoped per plant. ### Air-gapped **Fit:** Defense or export-controlled programs **Detail:** Isolated analysis environment fed by approved transfers. ## Compliance ### Process and scrap evidence becomes retrievable for audits and corrective actions; the quality system remains the record. **Framework:** IATF 16949 ### For medical molders the AI is a read-only retrieval aid. Validated processes continue to govern device history records. **Framework:** FDA 21 CFR 820 / QMSR and ISO 13485 ### Where part data is controlled, keeping model and index inside the customer's boundary lets their export program decide access. **Framework:** ITAR / EAR ### Answers cite source records, which supports complaint and PPAP evidence requests. **Framework:** Customer quality flow-downs ## Integration Notes - Confirm the Mattec version and database layout with Epicor or your integrator before designing queries, as table structures differ between releases. - Use a SQL Server replica or reporting copy for analysis and a read-only login with access limited to named views. - Normalise press and mold identifiers across the MES, ERP asset records and maintenance notes. - Capture resin lot data at the job level if it is not already recorded, as lot-to-scrap correlation depends on it. - Use Epicor or other ERP APIs for job, item and lot reads instead of querying the ERP database directly where possible. - Treat standard cycle times as data that needs periodic review, since drift detection is only as good as the baseline. ## Product Fit ### Custom build **Why:** A bespoke semantic layer over the MES schema and your ERP is needed; the same pattern covers other MES products if you add them later. ### DataRay **Why:** If scrap logs, quality records and MES data sit in several databases and file shares, DataRay lets users chat across them on-prem. ## Engagement ### Discovery **Duration:** 1 to 2 weeks **Deliverables:** - Question inventory from production and quality - MES version and schema review - ERP integration points ### Semantic model **Duration:** 2 to 4 weeks **Deliverables:** - Curated views for presses, molds and scrap - Metric definitions agreed - Read-only access ### Pilot **Duration:** 3 to 5 weeks **Deliverables:** - Q&A for a set of presses - Verified answer test set - Operator and engineer feedback ### Rollout **Duration:** 3 to 5 weeks **Deliverables:** - Remaining presses and plants - Permissions model - Monitoring and handover ## Buyer Questions - Which Mattec version are we on and what is the database layout? - Can analytics run on a replica without affecting press monitoring? - Is resin lot recorded at the job level today? - How will job numbers be matched between MES and ERP? - Can every answer show its query and underlying rows? - What does the standard Mattec reporting already do well? - How will complaint packs be reviewed before they go to a customer? ## Faq ### What is Epicor Mattec MES used for? **Answer:** It is a manufacturing execution system commonly used by injection molders and similar plants to monitor presses, record downtime and scrap, track production against jobs, and manage molds and tooling. It provides real-time visibility on the floor and feeds production data back to the ERP. ### Does Epicor offer AI for Mattec? **Answer:** Epicor has been adding AI features across its portfolio, so check the current roadmap and licensing for your version. A separate private layer is worth considering if you need cross-system questions, unusual analysis, or want the model and data to remain entirely within your own infrastructure. ### Can the AI find the cause of scrap? **Answer:** It can surface correlations, such as a rise in a scrap reason after a resin lot change or on one mold-press pairing, with the data shown. Confirming a root cause still requires process engineers and sometimes trials. We present correlations as leads, not conclusions. ### Does it only work with Epicor ERP? **Answer:** No. Mattec is often paired with Epicor Kinetic or Prophet 21, but the AI layer joins to any ERP with a usable API or reporting interface. The effort is in matching jobs, items and lots, which is similar across systems. ### Will it slow down the MES? **Answer:** It should not. We read from a replica or scheduled copy of the database, not the live monitoring instance, and use a read-only account limited to specific views. We recommend testing query load during off-peak hours before rollout. ### Can the AI write to Mattec or the ERP? **Answer:** Not by default. The standard design is read-only. If you want it to propose changes such as updated standard cycle times, a person approves them and the change is made through supported interfaces with an audit trail. ### How large a GPU do we need? **Answer:** For a plant team asking questions during the day, a single modest GPU server and a mid-sized open-weight model are often enough. We size from concurrent users and document volume, and some sites begin on shared infrastructure. ## Search terms epicor mattec mes ai, mattec mes integration, injection molding mes ai, press monitoring ai, mattec scrap analysis, mold management ai, epicor mes ai, mattec erp integration, molding downtime analysis, private ai for plastics manufacturing, mattec reporting alternative, cycle time drift detection --- Talk to an engineer: https://netray.co/contact?intent=erp_ai | Machine catalog: https://netray.co/agent/catalog.json