Process Optimization vs Stable Operation
Change only one parameter set at a time and document each result before proceeding to the next optimization.
CyberTRIZ analysis · GreenFieldIndustrialProjects contradiction CSO018 · one of 8,235 worked contradictions published by CyberTRIZ.AI
Regulations
Business Context
Start-up teams often identify opportunities to improve throughput, efficiency, yield, energy consumption, or control performance. Continuous optimization changes can make it difficult to establish a stable baseline and determine the causes of abnormal behavior.
Green Field Industrial Projects TRIZ Resolution
Establish stable operating baselines before introducing optimization changes. Modify one controlled set of parameters at a time, measure results, and retain the ability to return to a verified stable configuration.
Applicable TRIZ Principles
Principle 1 – Segmentation separates stabilization from optimization activities.
Principle 15 – Dynamics allows controlled parameter adjustment after baseline performance is established.
Principle 23 – Feedback measures the effect of each optimization change before further modification.
Expected Outcome
More stable operation
Faster effective optimization
Clearer cause-and-effect understanding
Reduced start-up variability
Decision Indicators
Early indicators include:
Multiple process parameters change simultaneously.
Teams cannot identify which change caused performance deterioration.
Stable operating baselines are unavailable.
Optimization repeatedly creates new operating problems.
Control settings change continuously during troubleshooting.