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The Effect of Prior Experience on Learning Curve Parameters

  • J. E. Cherrington
  • S. Lippert
  • D. R. Towill
Conference paper

Abstract

Learning Curves and Progress Functions are well established management tools used to predict productivity in the start-up of new product lines, and to describe the performance of individual employees. As the authors, amongst others, have shown, these tools have been successfully applied to a wide range of tasks in highly varied industries. It is particularly useful, especially for inter-firm comparisons to compress the Learning Curves and Progress Functions into simple mathematical models in which the parameters may be determined by least squares error curve fitting or other convenient techniques. When on-line prediction is required, a digital computer algorithm is used to estimate the model parameters. It is essential that the parameter estimation technique used is robust in the presence of large amounts of scatter in the raw data.

Keywords

Surface Roughness Tactile Sense Error Curve Individual Employee Simple Mathematical Model 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Copyright information

© Springer-Verlag Berlin Heidelberg 1985

Authors and Affiliations

  • J. E. Cherrington
    • 1
  • S. Lippert
    • 2
  • D. R. Towill
    • 3
  1. 1.City of Birmingham PolytechnicUK
  2. 2.University of MassachusettsUSA
  3. 3.University of Wales Institute of Science and TechnologyUK

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