Training course · Claude · Manufacturing

Claude for Manufacturing Teams

Claude as an AI assistant for knowledge work: projects, Artifacts, long documents, analysis and precise writing for teams.

Duration
1 day (7 hrs)
Format
Online or on-site
Language
German or English
Participants
open dates or exclusive for your team
Certificate
Certificate of attendance

Overview

This course connects Claude with the everyday processes of Manufacturing. Participants work on realistic scenarios and leave with prompts, workflows and checklists they can use straight away.

Anthropic's Claude has become a go-to AI assistant for demanding knowledge work: it handles very long documents, reasons transparently and writes in a measured, easily steerable style. In this practical day you learn to exploit these strengths systematically. You analyse lengthy reports, contracts or policies, compare several sources and extract key findings with references to the exact passages. With Projects you store background knowledge and working instructions permanently, so Claude knows your terminology, templates and quality standards and you no longer start from scratch with every request.

We also show how to use Artifacts to produce standalone deliverables – structured documents, tables, charts or small interactive tools – and share them with your team. You analyse files with the built-in analysis capability, use research and connectors to company data, and put Claude to work as a critical reviewer of your own writing. A dedicated session covers Team and Enterprise plans, access management and data protection. By the end you have tested project set-ups and prompt patterns that you can apply straight away in your own function.

Manufacturers face cost pressure, skills shortages, complex product variants and high expectations for on-time delivery. Generative AI adds a new layer to existing Industry 4.0 solutions: AI assistants make knowledge from manuals, fault logs and work instructions accessible, support shift handovers, summarise KPIs from MES and ERP exports and help with root cause analysis using methods such as 5 Whys or Ishikawa. AI agents and automation create shift reports, analyse machine breakdowns and prepare maintenance orders. Experienced staff in particular benefit when their knowledge is documented and made available to new colleagues. Adoption succeeds when it starts with concrete shop-floor problems, involves works councils and health and safety early and keeps production data secure.

The course is delivered live – either online in a virtual classroom or on-site in our training rooms in Munich, Salzburg, Berlin, Augsburg, Hanover, Bremen, Stuttgart and Kaiserslautern. We can also run it exclusively for your team.

Who is this course for?

  • Production and plant managers
  • Shift leaders and supervisors
  • Manufacturing and process engineers
  • Maintenance teams
  • Lean and operational excellence leads

Typical challenges we address

  • Capturing and passing on the know-how of experienced staff
  • Analysing breakdowns quickly and reducing downtime
  • Presenting KPIs such as OEE from various systems in an understandable way
  • Keeping work instructions current and clear across many variants

What you will be able to do

  • You write precise, structured instructions that let Claude handle complex tasks reliably.
  • You analyse long and multiple documents and obtain referenced, verifiable summaries.
  • You set up Projects with a knowledge base and style rules and share them with your team.
  • You use Artifacts and the analysis capability to produce usable documents, tables and evaluations.
  • Use AI for knowledge management, root cause analysis and shift reporting in production.
  • Analyse production KPIs with AI and derive improvement actions.
  • Take data security, co-determination and occupational safety into account in manufacturing AI projects.

Course outline

Module 1 Understanding and directing Claude
  • Model family, strengths and limitations compared with other assistants
  • Clear instructions with context, examples and the desired output format
  • Structured input using sections and tags for complex tasks
  • Extended thinking and step-by-step approaches for demanding questions
Module 2 Analysing long documents
  • Uploading and querying large PDFs, reports and contract sets
  • Comparing multiple documents and surfacing contradictions
  • Summaries with references to specific passages
  • Deriving checklists and review grids from policies and guidelines
Module 3 Projects and knowledge base
  • Creating Projects with knowledge documents and persistent instructions
  • Storing style and terminology rules for consistent results
  • Sharing Projects with the team and developing them together
  • Making good use of connectors to drives and business applications
Module 4 Artifacts, analysis and writing
  • Creating Artifacts for documents, tables, charts and interactive tools
  • Analysing files and spreadsheets with the built-in analysis capability
  • Drafting, shortening, rewording and tailoring text to audiences
  • Using Claude as a critical reviewer of arguments and gaps
Module 5 Team use, data protection and quality
  • Team and Enterprise plans: administration, roles and sharing
  • Handling confidential and personal data in line with GDPR
  • Checking output: verifying facts, figures and quotations
  • Defining internal guidelines and reusable prompt patterns
Module 6 Practice lab: Manufacturing
  • Shop-floor knowledge assistant
  • Root cause analysis
  • Shift reports and handovers
  • Work instructions
  • KPI analysis
  • Maintenance preparation
Module 7 Data protection, quality & transfer to daily work
  • Production data and engineering know-how are trade secrets and belong only in approved AI environments; in Germany, AI-based evaluation of employee performance or behaviour requires works council co-determination. AI components in safety-related machine functions fall under the EU Machinery Regulation and may be high-risk under the EU AI Act.
  • Ground rules for safe AI use in your team
  • Checking results: facts, sources, tests and the four-eyes principle
  • Personal action plan for the next 30 days
  • Open questions, outlook and resources for further learning

Practical scenarios from your field

Shop-floor knowledge assistant

An AI assistant answers questions about machines, changeovers and fault patterns based on manuals, breakdown history and work instructions, always citing the source for verification.

Root cause analysis

AI structures breakdowns and quality issues using 5 Whys, Ishikawa or 8D, suggests possible causes from similar cases and helps document actions and responsibilities.

Shift reports and handovers

Notes, machine data and fault reports are turned into structured shift reports with output, breakdowns and open points, making handover to the next shift easier.

Work instructions

AI turns process descriptions, photos and expert interviews into illustrated, multilingual work instructions and checklists in plain language and keeps variants consistent.

KPI analysis

MES and ERP exports are analysed, OEE losses broken down by availability, performance and quality and anomalies explained clearly for shop-floor meetings.

Maintenance preparation

Automations collect fault reports; AI groups recurring failures, drafts maintenance orders and prioritises actions based on frequency and impact, before maintenance planning takes them over.

Prerequisites

Confident use of office applications and a web browser; prior AI experience is helpful but not required. Your own non-confidential documents are welcome as practice material. You work in production, production planning or maintenance and know the processes at your plant.

Technical requirements

A laptop with an up-to-date browser or the Claude desktop app and a Claude account; we recommend Pro, Team or Enterprise access for Projects and larger files.

Data protection & compliance

Production data and engineering know-how are trade secrets and belong only in approved AI environments; in Germany, AI-based evaluation of employee performance or behaviour requires works council co-determination. AI components in safety-related machine functions fall under the EU Machinery Regulation and may be high-risk under the EU AI Act.

Suggested dates

All dates are suggestions – your preferred date is always possible.

  • Mon, 23 November 2026 Online Request
  • Fri, 4 December 2026 Munich Request
  • Wed, 9 December 2026 Online Request
  • Fri, 8 January 2027 Online Request
  • Fri, 15 January 2027 Hanover Request
  • Mon, 18 January 2027 Online Request

Frequently asked questions

How does Claude differ from ChatGPT in everyday work?

Both are capable general-purpose assistants. Claude particularly stands out with very long documents, careful reasoning and an easily steerable writing style, while Projects and Artifacts support structured work. Which tool fits better depends on your tasks, integrations and company policies – the course gives you criteria for an informed assessment.

What are Artifacts and why would I use them?

Artifacts are standalone deliverables that Claude creates in a separate panel next to the chat – a document, a table, a chart or a small interactive tool, for example. They can be revised in a targeted way, downloaded and shared. A conversation therefore produces ready-to-use results rather than scattered fragments of text.

Is my data used to train Claude?

On Team and Enterprise plans, business content is not used for model training as a matter of principle. For individual accounts this depends on settings you should review yourself. Regardless of the plan, GDPR and internal confidentiality rules apply. In the course we walk through the relevant settings and the questions to ask.

Do we need to connect AI to our machines?

Not necessarily. Many use cases, such as knowledge assistants, work instructions or root cause analysis, work with documents and MES or ERP exports. Connecting directly to machine data is a later step that requires IT and OT security. In the course we start with use cases you can implement quickly.

How do we gain acceptance from the workforce?

By making AI visibly ease work, for example through faster troubleshooting or simpler documentation, rather than being perceived as a monitoring tool. Involve employees and their representatives early, start with pilot areas and clearly define which data will not be used for performance evaluation.

How much does “Claude for Manufacturing Teams” cost?

The course costs a flat €949 plus VAT per participant – whether online or on-site. This includes 1 training day(s) with a live trainer, course materials, a lab environment and a certificate of attendance.

Can I suggest my own date?

Yes. Our suggested dates are just a guide. In the request form you can always describe your preferred date or period in free text – we check availability and confirm within one working day.

Is the course online or on-site?

Both are possible: live online in a virtual classroom or on-site in Munich, Salzburg, Berlin, Augsburg, Hanover, Bremen, Stuttgart or Kaiserslautern. We can also run the course exclusively for your team.

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