Read & connect
AI helps extract information, connect sources and explain context. Sources, versions and uncertainties remain visible.
INDUSTRIAL AI · FROM IDEA TO WORKFLOW
Understand the AI.
See the value.
Ten scenarios explain what AI does, how each solution processes information and what operational value it can deliver. Explore the methods, concrete examples and evidence needed for a useful pilot.
Explore the scenariosTHE NEXT LEVEL OF DETAIL
From an opportunity
to an operating scenario.
The Industry pages introduce the opportunity areas. Here, the focus shifts to additional, concrete workflows: who needs what information, how AI can help and what the next person receives.
All scenarios are illustrative, not customer references or promises of results. The workflows shown are concepts; no live AI systems or company data are connected here.
View the Industry introductionTEN TASKS. CONCRETE WORKFLOWS.
Find your
starting point.
Select an area and open a scenario for its AI task, technical method, value, workflow and pilot criteria.
10 examples across 7 areas
01 / Production
Prepare a controlled restart after a variant change
A released product change affects tools, operations and inspections. An assistant brings the relevant changes together in a traceable restart pack.
Explore AI, technology & value 02 / ProductionBuild a practical sequence for a bottleneck resource
Orders compete for the same machine. Runtime forecasts and optimisation under fixed constraints make alternative schedules comparable.
Explore AI, technology & value 03 / Quality managementFocus inspection planning after a product change
An engineering change affects specific characteristics and measurement methods. An assistant prepares a traceable change list for quality planning.
Explore AI, technology & value 04 / Complaints managementTrace potentially affected batches after a complaint
From the reported part to stock and customer shipments: AI supports intake, while traceable links establish potential exposure.
Explore AI, technology & value 05 / Compliance & reportsDraft inspection and acceptance reports from verified evidence
Measurements, test records and outstanding items are mapped to the agreed acceptance scope and assembled into a reviewable draft.
Explore AI, technology & value 06 / Compliance & reportsPrepare a compliance report with a traceable evidence chain
An approved requirements catalogue is matched with product, material and supplier evidence. Missing or mismatched records are routed for clarification.
Explore AI, technology & value 07 / LogisticsResolve goods-receipt exceptions before posting
Advance notices, delivery notes and purchase orders are matched line by line. Uncertain quantities, packaging units and batch references enter a focused clarification workflow.
Explore AI, technology & value 08 / Supply chainAssess a material shortage through to customer orders
One missing component affects multiple products. Bill-of-material links and scenarios expose affected orders and available approved options.
Explore AI, technology & value 09 / Service & self-serviceGuide customers through approved self-service tasks
A customer portal offers help matched to the installed machine, collects missing information and hands the complete context to service when needed.
Explore AI, technology & value 10 / Service & self-servicePrepare field visits with the right parts and machine context
Before travel, a visit pack combines installed configuration, case history and confirmed spare parts. After the visit, it supports a reviewable service report.
Explore AI, technology & valueA GUIDE TO THE METHODS
Different tasks.
Different methods.
The scenarios propose possible solution designs. These short explanations help place each component in context.
- Generative AI / LLM
- A large language model interprets and writes text. It supports extraction, explanation and drafting; its output must be checked against the relevant records.
- RAG & semantic search
- Retrieval-augmented generation combines retrieval with a language model. Semantic search uses meaning to find passages; metadata limits the valid sources.
- Document AI / OCR
- Optical character recognition reads image text. Document models additionally identify layout, tables and fields so their content can be processed.
- Predictive AI
- Models learn patterns from operational examples to estimate a value or class. Their performance must be tested on separate data against a practical baseline.
- Optimisation & rules
- Fixed rules check business conditions; mathematical optimisation searches feasible alternatives under constraints. These components can work alongside AI.
Technical background & primary documentation
Background on the methods; these links do not prescribe a vendor for the illustrative designs.
A PRACTICAL DIVISION OF WORK
AI assists.
The process stays accountable.
The method follows the task. Language models, forecasting and deterministic rules play different roles.
Check & compare
Validated rules and planning logic calculate quantities and respect hard constraints. Forecasts provide estimates, with measurable error.
Review & approve
The responsible teams assess proposals, approve changes and measure results against the existing process.
FROM SCENARIO TO A PRACTICAL NEXT STEP
Which process deserves
a closer look?
Together, we can clarify the current process, available evidence and a useful pilot. My contribution: structure, priorities and alignment between business teams, IT and implementation partners.