AI automation · Manufacturing AI in industry and mechanical engineering: automating orders, quality records and service

Typical workflows in manufacturing

These are typical processes, not client projects. In each, the AI prepares and checks against your rules, and a person in sales, purchasing or quality decides. For the work on the shop floor itself, such as production orders, shift reports and quality, see AI in production.

1. Orders and requests for quotation into the ERP

Orders and enquiries arrive as PDFs, emails, drawings and portal exports, each customer in their own layout.

• Input: the order or request by email, portal or PDF.
• AI prepares: reads item numbers, quantities, delivery dates and prices, matches them to the item master and price lists, and flags what does not fit: an unknown item, a price that differs from the list, a delivery date shorter than the lead time. It drafts the sales order and the order confirmation.
• Sales checks: every flagged deviation. Standard orders without deviations can be approved in one click.
• Output: a sales order draft in the ERP and a confirmation draft for the customer.

2. Quality records and certificates

Material certificates, test records and supplier declarations have to be checked against the specification and filed.

• Input: certificates and test reports from suppliers, your own measurement records, the specification or drawing.
• AI prepares: reads the values, compares them with the limits in the specification, lists every deviation with the page it came from and assembles the inspection file for the batch. For a non-conformance it drafts the report with the measured values.
• Quality staff check: every deviation and release the batch. Conformity statements are signed by authorised people.
• Output: a checked document set per batch and a draft non-conformance report where needed.

3. Supplier confirmations and goods receipt

Order confirmations and delivery notes are compared with the purchase order, usually when someone finds the time.

• Input: purchase order, supplier confirmation and delivery note.
• AI prepares: compares price, quantity, delivery date and terms, and lists the differences with both document lines. Confirmations without differences are marked as checked.
• Buyer checks: each difference and decides whether to accept it or go back to the supplier.
• Output: a short summary for the buyer and updated delivery dates in the ERP.

4. Service and spare-parts enquiries

Customers ask for spare parts, manuals and fault help, often quoting only a serial number or a photo.

• Input: the enquiry with serial number, photo or fault description.
• AI prepares: identifies the machine and variant from the serial number, finds the right manual section and parts list and drafts the reply with the source pages.
• Service engineer checks: the answer before it goes out and takes over anything that involves safety or warranty.
• Output: a reply draft with sources and a service ticket with the details already filled in.

What stays with engineers, and what we do not do

• Engineering and safety: design decisions, risk assessments and the release of a product stay with qualified staff.
• Conformity: declarations of conformity and CE or UKCA marking are signed by the responsible person, never by software.
• People on the shop floor: we do not build systems that allocate work to individuals, monitor behaviour or evaluate performance. These are high-risk under Annex III of the AI Act, see risk categories.
• Machine control: we automate documents and communication, not control systems or safety functions.
• Customer chat: answers from your documents, with sources, says clearly that it is an AI and hands over to service for anything about safety, warranty or liability.

Rules that matter

The table lists the main sources as an orientation. Which rules apply depends on your product, your markets and your customers’ requirements.

On top of this, the GDPR applies to employee and customer data: a data processing agreement with every provider (Art. 28) and processing in the EU or UK. Art. 4 of the AI Act asks for sufficient AI literacy among staff, and Art. 50 requires AI chatbots to identify themselves. This overview is general information, not legal advice. Your quality manager, your works council and your legal adviser can confirm what applies.

Systems you probably use

Manufacturers typically work with an ERP such as SAP, Microsoft Dynamics 365, Odoo or Sage, often with a separate quality or maintenance system and a shared drive of drawings and certificates. We connect through the interfaces these systems offer (API, export, EDI, email or a watched folder) and work alongside them where none exists. The names are for orientation only and do not imply any partnership.

How AI assistants find manufacturers

Buyers ask ChatGPT, Gemini or Google’s AI Overviews for “CNC machining supplier with ISO 9001 in the Midlands” or “who makes stainless steel enclosures to order”. The answer is built from product and capability pages, certification registers, trade directories, trade fair listings and reviews.

• A page per product group or process: materials, tolerances, batch sizes, certifications and lead times in plain words.
• Structured data: Schema.org Product, Organization and certifications, so that machines can read the facts.
• Consistent company data: the same name, address and certificates on the website, in directories and in certification registers.
• Documents that can be cited: data sheets and technical descriptions as readable pages, not only as scans.

Our article Manufacturing SEO: B2B product data and AI covers the details.

Is it worth automating? Eight questions

1. Does someone re-key orders from PDFs or emails into the ERP every day?
2. Do customers send enquiries without item numbers, only with drawings or photos?
3. Are certificates checked against the specification by eye?
4. Do order confirmations from suppliers get compared with the purchase order only sometimes?
5. Does service spend time finding the right manual page for a serial number?
6. Do quality records live in folders, spreadsheets and the ERP at once?
7. Is there a written rule on what may go into AI tools and who checks the result?
8. Can you name one task where a draft that needs checking would already save time?

Three or more yes answers usually point to a workflow worth testing. Question 7 is the prerequisite.