Quality knowledge grows through inspections, complaints and everyday decisions. AI can help put existing information to better use and support recurring tasks.
How much quality knowledge do you have — and how much of it can your team find when it matters?
USE CASE EXAMPLES
How AI could help in everyday work.
Illustrative scenarios. Requirements and value are assessed for your specific process.
01
TEXT & DOCUMENT ASSISTANCE
Prepare complaints and 8D reports
THE STARTING POINT
Customer messages, images, inspection reports and internal notes take time to consolidate. Similar past cases can be difficult to find.
A POSSIBLE APPROACH
AI supports the extraction and organisation of information, searches for similar cases and prepares text drafts for further processing. Missing information is highlighted as an open question.
WHAT YOU NEED
Complaint data, approved reports, defect categories and traceable links to items, batches and customers.
UNDERSTAND THE AI
What happens behind the scenes.
TECHNICAL INSIGHT
POSSIBLE SOLUTION DESIGN
Document AI · Similarity search · 8D assistant
What does the AI actually do?
AI structures complaint text and retrieves similar defect descriptions from completed cases.
How the solution works
01
Extract facts
Populate part, defect, date and missing-information fields.
02
Retrieve related cases
Semantic search returns evidenced cases and recorded actions.
03
Prepare an 8D draft
Map confirmed facts to sections; root causes remain hypotheses until validated.
What value can it deliver?
Less intake effort, more complete case records and greater reuse of documented experience.
A concrete example
A similar crack description suggests a previous investigation approach, without transferring its root cause automatically.
Technology, setup & operation+
Use a pretrained LLM and case index. Templates and status rules distinguish observation, hypothesis, confirmed cause and verified effectiveness.
Illustrative solution design. The final architecture depends on data, systems and pilot evaluation.
Pilot, value assessment & professional responsibility +
HOW A PILOT COULD START
Use one product group and selected closed cases for evaluation before supporting new complaints.
HOW TO ASSESS VALUE
Compare preparation time, completeness and the amount of correction needed with the existing process.
Root cause determination, effectiveness checks and approval remain with the responsible specialists.
02
KNOWLEDGE SEARCH
Find inspection and audit knowledge
THE STARTING POINT
Inspection instructions, internal requirements and audit evidence are stored in different places. Document versions and validity are not always clear at first glance.
A POSSIBLE APPROACH
Source-based search guides users to relevant approved documents. It can prepare answers with references and make the applicable version visible.
WHAT YOU NEED
Controlled documents with status, version, scope and access controls, supported by clearly assigned document maintenance responsibilities.
UNDERSTAND THE AI
What happens behind the scenes.
TECHNICAL INSIGHT
POSSIBLE SOLUTION DESIGN
RAG knowledge search · Metadata filters
What does the AI actually do?
AI finds relevant quality and audit records despite different terminology and explains their content.
How the solution works
01
Limit validity
Filter by site, product, scope and released revision.
02
Retrieve passages
Combine semantic and keyword retrieval.
03
Ground the answer
An LLM summarises passages with sources and unresolved conflicts.
What value can it deliver?
Faster access to valid evidence and less effort separating obsolete versions.
A concrete example
A gauge-check question returns the applicable current instruction rather than an old audit copy.
Technology, setup & operation+
Indexing supports discovery; permissions and release status must come from document management. Evaluate source relevance and correct revision separately.
Illustrative solution design. The final architecture depends on data, systems and pilot evaluation.
Pilot, value assessment & professional responsibility +
HOW A PILOT COULD START
Start with one document area that has sound version control and a defined set of questions.
HOW TO ASSESS VALUE
Test search accuracy, correct version selection and time to reliable evidence using typical quality questions.
Authoritative statements are checked against the original document. AI output does not replace formal approval or an audit decision.
03
ANALYTICAL SUPPORT
Connect defect patterns with process data
THE STARTING POINT
Quality deviations are documented, while relevant process, material and inspection parameters sit in other systems.
A POSSIBLE APPROACH
A shared data foundation and analytical methods can reveal recurring patterns. The quality team uses these insights to prioritise hypotheses for targeted investigation.
WHAT YOU NEED
Traceable links between inspection results, process steps, batches and material properties, together with documented changes.
A model learns associations between process/material combinations and recorded quality outcomes.
How the solution works
01
Link batches
Match inspection results to process and material data available before inspection.
02
Fit the model
A classifier, such as gradient boosting, learns good/defective outcomes and is evaluated on later batches.
03
Investigate signals
Risk indicators and feature analysis prioritise technical investigation.
What value can it deliver?
Less data-screening effort and more focused trials. Confirmed scrap improvements are evaluated only after process validation.
A concrete example
A material-temperature combination occurs more often with a defect and becomes a priority for controlled trials.
Technology, setup & operation+
Representative, correctly linked outcomes are required. Model explanations describe associations rather than proven causes. Exclude leakage from information unavailable at prediction time.
Illustrative solution design. The final architecture depends on data, systems and pilot evaluation.
Pilot, value assessment & professional responsibility +
HOW A PILOT COULD START
Select a frequent defect and analyse completed production batches with domain specialists.
HOW TO ASSESS VALUE
Measure the usefulness of investigation hypotheses and the effort required to assemble data. Track confirmed improvements separately.
A pattern does not prove a cause. Technical review and controlled trials are needed to validate conclusions.
MY CONTRIBUTION
Work out together what is worth pursuing.
I help you turn an interesting use case into a clear, assessable business task.
Structure needs and objectives with business functions and IT
Clarify value, requirements and open questions
Prepare a basis for decisions and define a possible pilot scope
Support alignment with suitable implementation partners
FREQUENTLY ASKED QUESTIONS
Before taking the first step.
What about visual quality inspection? +
This can be another application area. Defect types, image quality, lighting, representative inspection images and acceptable error rates all need to be clarified. Evaluation and implementation involve the relevant specialists and suitable solution partners.
What is my role? +
I help define the use case, structure requirements and expected value, and prepare alignment between the quality function, IT and potential implementation partners.
FROM A USE CASE TO THE NEXT STEP
Which idea would you like to make concrete?
Together, we clarify the starting point, possible use cases and expected value, creating a sound basis for your next decisions.