# AI for Dynamics 365 Business Central in Metal Fabrication > Source: https://netray.co/erp-ai/dynamics-365-business-central-metal-fabrication-ai > Publisher: Netray (netray.co), AI and integration engineering for ERP and manufacturing systems. > Section: AI for ERP ## Short answer AI for Business Central in metal fabrication reads items, variants, production orders, routings, subcontracting and lot records so estimators, schedulers and quality staff can ask about job cost, heat-lot traceability and outside-processing status in plain English. A private model grounds answers in your data and shows the query, while quoting and write-backs stay as drafts for approval. ## Kind industry ## Erp Family microsoft ## Erp Products - Dynamics 365 Business Central ## Industries - Metal Fabrication - Job Shops - Sheet Metal and Welding ## Region Global ## Persona Operations Manager ## Eyebrow Business Central + fabrication AI ## Intro Fabricators and job shops running Business Central usually live with a particular tension: the ERP models production orders, routings and BOMs well, but a shop's real world is sheet and plate in odd sizes, remnants, cut lists, welding and finishing operations, outside processing at galvanizers or powder coaters, and customers who want material certifications by heat number. Much of this is handled through conventions. Material grades and thicknesses become items or variants, heat numbers and mill certificate references become lot numbers, outside processes use work centers flagged as subcontracting and the Subcontracting Worksheet, and nesting happens in a separate CAM tool whose output arrives as a spreadsheet or a custom import. The conventions work, but they live in people's heads. That is where grounded AI is useful: reading the real posted data to answer how last quarter's jobs compared with their estimates, where a heat lot went, which jobs are waiting on a vendor, and what remnant stock could cover a new request. It is not a nesting engine and it does not weld anything; it shortens the time between a question and an evidence-backed answer. This page describes what that looks like on Business Central, which objects and integration points matter, how to protect customer drawings and quoted pricing, and when a simpler tool or a specialist add-on is the better choice. ## Pain Points ### Estimates and actuals are never compared **Detail:** Quoted hours and material sit on the sales quote or project; actual hours accrue in capacity ledger entries and material in consumption. Comparing by part family or operation rarely happens, so the same underestimates repeat. ### Remnants and offcuts disappear **Detail:** Leftover sheet and bar often exist only as a bin location or a lot with an odd quantity. Estimators order new stock because finding a suitable remnant is not practical. ### Heat-lot certs must follow the part **Detail:** Customers in structural, pressure and aerospace-adjacent work ask for mill certificates by heat number. Linking a finished weldment back to every heat consumed is manual unless tracking was done consistently. ### Outside processing is a status black box **Detail:** Parts sent for plating, galvanizing or heat treat sit on subcontract purchase orders. Schedulers chase vendors by phone because the system shows a due date but no real status. ### Price volatility in steel and aluminum **Detail:** Surcharges and material price swings between quote and purchase affect margin. Spotting which open quotes are exposed means recalculating cost against current vendor prices. ## Use Cases ### Estimate versus actual job analysis **Description:** Estimators ask how a part family performed against its quoted hours and material. The assistant compares routing time, capacity ledger actuals and consumption by job, and highlights operations that consistently overrun. **Erp Objects:** Production Order, Routing Line, Capacity Ledger Entry, Item Ledger Entry, Sales Quote Line **Outcome:** Evidence for adjusting standard times and quote factors; estimators still decide the changes. ### Heat-lot traceability by shipment **Description:** For a customer's shipment, the agent lists the heat lots consumed in each part, with certificate document references, ready for the quality lead to assemble the package. **Erp Objects:** Item Ledger Entry, Lot No. Information, Item Tracking Line, Sales Shipment Line, Document Attachment **Outcome:** Cuts the time to compile certification packages and exposes parts consumed without a lot recorded. ### Remnant and offcut matching **Description:** Given a new job, the assistant searches remnant stock by material, thickness, and minimum dimensions stored in variants or custom fields, and suggests candidates before purchasing new sheet. **Erp Objects:** Item, Item Variant, Bin Content, Lot No. Information, Production Order Component **Outcome:** Less purchased material for small jobs where suitable offcuts already exist. ### Outside processing tracker **Description:** The agent lists subcontract purchase orders by vendor, expected return date and the production orders they gate, and drafts follow-up emails to vendors for the buyer to send. **Erp Objects:** Purchase Line, Work Center (subcontracting), Subcontracting Worksheet, Prod. Order Routing Line, Vendor **Outcome:** Replaces phone-tag scanning with a short list of at-risk jobs. ### Quote exposure to material price changes **Description:** The assistant recomputes material cost on open quotes against latest vendor prices and flags those whose margin now falls below a threshold. **Erp Objects:** Sales Header, Sales Line, Purchase Price, Item Vendor, Production BOM Line **Outcome:** Earlier repricing conversations on exposed quotes. ### Scheduling bottleneck summary **Description:** Daily, the agent summarizes load on laser, brake, weld and paint work centers against capacity and lists jobs likely to miss ship dates. **Erp Objects:** Work Center, Work Center Calendar Entry, Prod. Order Routing Line, Sales Line **Outcome:** A clearer morning view for the production meeting; the schedule is still set by people. ### Nonconformance and rework lookup **Description:** Quality staff ask for rework history by customer, part and weld cell; the assistant reads scrap and rework postings and linked comments. **Erp Objects:** Output Journal (scrap), Prod. Order Line, Item Ledger Entry, Capacity Ledger Entry **Outcome:** Faster root-cause conversations backed by the posted history. ## Architecture **Overview:** The AI layer reads Business Central production, inventory and purchasing data through scoped API pages and indexes drawings, certificates and WPS documents on your infrastructure. It does not alter nesting or CAM output; it connects what posted in the ERP to what people ask about it. **Layers:** #### ERP data access **Detail:** Read-only endpoints for production orders, routing and capacity ledger entries, item ledger, lot records and purchase lines. #### Document index **Detail:** Mill certs, drawings, weld procedure specs and inspection reports indexed locally with item, job and lot metadata. #### Shop conventions map **Detail:** How your shop encodes thickness, grade, remnant dimensions and heat numbers, written down so the model does not guess. #### Model serving **Detail:** Open-weight models running on your GPUs or private cloud, keeping customer drawings and prices inside your boundary. #### Approval layer **Detail:** Drafted emails and proposed quote changes are queued for staff; no autonomous postings. ## Deployment Options ### Small on-prem GPU server **Fit:** Shops with controlled customer drawings or ITAR-related work **Detail:** A single server runs the model and index inside the shop network, reading the tenant or on-prem database via scoped access. ### Private cloud tenant alongside SaaS **Fit:** Growing fabricators on Business Central online **Detail:** Model runs in your Azure subscription; service-to-service OAuth reads only the objects exposed. ### Shared service for multiple shops **Fit:** Groups with several plants **Detail:** One hosting location with per-entity access controls and separate indexes per company. ## Compliance ### Traceability and weld documentation retrieval is faster; certification and procedures remain the shop's responsibility. **Framework:** EN 1090 and ISO 3834 where applicable ### Index procedure documents and welder records so questions retrieve them with references; qualification decisions stay with certified staff. **Framework:** AWS D1.1 and customer weld requirements ### Run in a controlled, access-limited environment so technical data is not sent to public AI services; customer responsibility for registration and controls. **Framework:** ITAR/EAR for controlled drawings ### Lot traceability and rework history are retrievable with sources for audits. **Framework:** AS9100 and customer quality flow-downs ### Quotes and vendor prices stay in your infrastructure with role-based access. **Framework:** Pricing confidentiality ## Integration Notes - Standardize how heat numbers map to Lot No. and ensure Item Tracking Codes are on for structural and certified materials. - Subcontracting uses work centers with a subcontractor and the Subcontracting Worksheet; expose the resulting purchase lines linked to the production order. - Remnant dimensions need a home: item variants, lot attributes or custom fields. Without it the AI cannot match offcuts. - Nesting software output arrives via spreadsheet or custom import; record the nest identifier on the order so jobs can be tied to yield. - Index certificates and drawings from file shares or SharePoint with job, item and lot IDs in metadata. - Cache master data like routings and work centers; keep ledger queries date-bounded. ## Product Fit ### ERPray **Why:** Estimate-versus-actual analysis, scheduling summaries and traceability questions with visible queries. ### DataRay **Why:** Searching drawings, mill certs and inspection reports on file shares alongside ERP records. ### Custom build **Why:** Integrations with nesting or CAM tools and drafted vendor follow-up agents. ## Engagement ### Shop conventions review **Duration:** 1 to 2 weeks **Deliverables:** - Documented material, remnant and heat-lot conventions - Sample questions from estimators and quality - Access plan ### Data and document layer **Duration:** 2 to 3 weeks **Deliverables:** - Read-only API pages - Indexed certificates and drawings - Test question set ### Pilot with estimating and scheduling **Duration:** 3 to 4 weeks **Deliverables:** - Estimate-versus-actual assistant - Outside processing tracker - Accuracy review ### Extend **Duration:** 2 to 4 weeks **Deliverables:** - Remnant matching - Quote exposure alerts - Operations runbook ## Buyer Questions - How do we record heat numbers and remnant dimensions so the AI can use them? - Does the assistant touch our nesting software or only read posted ERP data? - Where do customer drawings and pricing get processed? - How are estimates compared with actuals across revisions of routings? - What does it write, if anything, and who approves it? - How do you handle controlled technical data? ## Faq ### Can AI do the nesting or cut optimization? **Answer:** No. Nesting is a specialized optimization problem handled by CAM software. The AI helps around it: recording yields, comparing nested versus quoted material, matching remnants and explaining overruns. If you need better nesting, evaluate nesting tools rather than a language model. ### Is Business Central good enough for job shops? **Answer:** Many fabricators run it successfully, particularly with a few extensions for sheet-metal conventions, but native support for remnants, nesting and finishing steps is limited. Some choose ISV add-ons. AI is not a substitute for choosing the right foundation; it adds value once the data is posted consistently. ### How does heat-lot traceability work? **Answer:** Business Central tracks lots on items with an Item Tracking Code. If you receive plate or bar by heat number as a lot and consume lots into production, the ledger holds the link. The assistant traces from shipment to heat lots using those entries and attached certificates, and reports gaps where lots were not recorded. ### Will it improve our estimates? **Answer:** It gives estimators evidence by comparing quoted and actual hours and material per part family and operation. Improvement depends on acting on that evidence by adjusting routing times and factors. Where actual time posting is sloppy, the first outcome is a data quality finding. ### Can it chase vendors for us? **Answer:** It can draft follow-up emails for subcontract purchase orders that are late or at risk, listing the jobs affected. A buyer reviews and sends them. We do not recommend autonomous vendor contact, because relationships and negotiated exceptions matter. ### Is controlled drawing data safe? **Answer:** The design keeps models and indexes on your servers or in a private environment you operate, with open-weight models and local logging, so drawings are not sent to public AI services. Your own export control program and access policies still govern who may use the system. ### What size shop is this practical for? **Answer:** Shops with a few thousand jobs a year and a few dozen users tend to find value, as the volume of data and recurring questions justify a layer. Very small shops may get most benefit from Power BI and good routing discipline, and we would say so after a short review. ## Search terms business central metal fabrication ai, business central sheet metal manufacturing, business central job shop erp ai, business central heat lot traceability, business central subcontracting worksheet, dynamics 365 business central fabricator, ai for metal fabrication erp, private ai fabrication shop drawings, business central estimate versus actual job cost, business central remnant inventory, business central mill certificate traceability --- Talk to an engineer: https://netray.co/contact?intent=erp_ai | Machine catalog: https://netray.co/agent/catalog.json