Performance Improvement Learning Improvement of Performance Reduced Production

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Performance Improvement Learning (Improvement of Performance) = Reduced Production Time and/or Reduced Errors Learning

Performance Improvement Learning (Improvement of Performance) = Reduced Production Time and/or Reduced Errors Learning = Individual + Organizational (Manufacturing Progress)

Learning Curves Theory As people gain experience performing a task, the time it takes

Learning Curves Theory As people gain experience performing a task, the time it takes to complete the task decreases. Specifically, as the accumulated number of units doubles, the time required to produce a unit declines at a constant rate. Note: Cognitive Learning > Manual Learning

Learning Curve Equations Hyperbolic Yx = KXN Logarithmic log Yx = log K +

Learning Curve Equations Hyperbolic Yx = KXN Logarithmic log Yx = log K + N log X Yx K X N = = Cumulative Average Time to Produce X Units Time Required to Produce the First Unit Cumulative Total Number of Units Produced Exponent of the Learning Curve Slope (tan q)

Synonyms Learning Curve Manufacturing Progress Function Cost / Quantity Relationship Product Acceleration Curve Improvement

Synonyms Learning Curve Manufacturing Progress Function Cost / Quantity Relationship Product Acceleration Curve Improvement Curve Performance Curve Experience Curve Efficiency Curve

Typical Productivity Learning Curve

Typical Productivity Learning Curve

80% Learning Curve

80% Learning Curve

Learning Curve Slope - 0. 514 - 0. 415 - 0. 322 - 0.

Learning Curve Slope - 0. 514 - 0. 415 - 0. 322 - 0. 234 - 0. 152 - 0. 074 LC % 70 75 80 85 90 95 Assembling Welding Machining

Notes LC % = 2 N where N = tan q New Production Time

Notes LC % = 2 N where N = tan q New Production Time (Cost) = LC % x Old As total number of production units increases and/ or average production time per unit decreases, q (tan q) decreases which implies LC % increases. Shallow learning curves (higher LC %) means relatively limited cost savings.

Learning Curve Solutions Click for Solutions Generator

Learning Curve Solutions Click for Solutions Generator

Food for Thought Was it Agatha Christie’s Inspector Poirot or maybe Dr. Watson’s comment

Food for Thought Was it Agatha Christie’s Inspector Poirot or maybe Dr. Watson’s comment to Sherlock Holmes “we often go more quickly by going more slowly”. Maxim for Computer-Aided Statistical Analysis Garbage In = Gospel Out