Greater Product Sorting Accuracy vs Higher Processing Throughput
Apply pricing analytics to segment by true price sensitivity, concentrating competitive discounting only where it materially influences purchasing decisions.
CyberTRIZ analysis · Agriculture contradiction SC013 · one of 8,235 worked contradictions published by CyberTRIZ.AI
Regulations
Business Context
Accurate sorting enables agricultural products to be separated according to size, maturity, quality, color, defects, contamination, or market specification. Greater inspection detail improves product classification but may slow processing and increase labor or equipment requirements. Higher line speed increases throughput but can reduce the time available for reliable identification.
Agriculture TRIZ Resolution
Sorting accuracy should be improved through parallel sensing and automated classification rather than longer individual inspection time. Machine vision, optical sensing, weight measurement, automated rejection, and multiple processing lanes can evaluate products rapidly while directing them toward appropriate categories.
Applicable TRIZ Principles
Principle 1 – Segmentation divides product flow into parallel classification pathways.
Principle 28 – Mechanics Substitution replaces slower manual inspection with appropriate automated sensing.
Principle 23 – Feedback continuously verifies sorting performance and adjusts classification parameters.
Expected Outcome
Higher sorting accuracy
Greater processing throughput
Lower classification errors
Better product-value recovery
Decision Indicators
Early indicators include:
Sorting accuracy declines as line speed increases.
Manual inspection becomes a processing bottleneck.
High-value grades are lost because classification is insufficiently precise.
Product flow must be slowed to detect defects reliably.
Sorting errors remain high despite substantial labor input.
These indicators support improved sensing and parallelization rather than slower processing.