Gains:
- Can write an effective prompt for schema control
- Gains the habit of verifying the findings made by artificial intelligence
- Can link auditing to corporate standard
AI does not validate the flowchart for you. What he does is follow the checklist without getting tired or skipping. The decision always belongs to the engineer.
What a good audit order includes
- Context: capacity, target flour type, wheat characteristics, working hour assumption.
- Input: equipment list in the scheme (passage, roll length, sieve surface, number of purifiers).
- Standard: company's own checklist or reference plant data.
- Desired output format: list of findings, rationale for each finding, and severity rating.
Sample prompt
"The flow chart below was prepared for a facility with a capacity of 300 tonnes/24 hours, targeting type 550 flour. Wheat is hard, protein is 12.5%. Check the scheme according to our checklist: capacity-sieve surface compatibility, purifier adequacy, definition of return lines, aspiration indication, sample points. Rate each finding as 'critical / important / information' and write the rationale. Do not guess where you are not sure, Say 'data insufficient'."
The last sentence is important: telling the AI to shut up when it is unsure reduces its ability to fabricate findings.
Validate the output
Visually confirm each finding on the diagram. Artificial intelligence's job is to implement the list completely, and your job is to confirm its accuracy. Unverified findings do not go to the customer.
The most valuable contribution of artificial intelligence is not to produce new information, but to apply the control you know without skipping a beat. Item skipped during fatigue is the most common cause of poor quality.