An almost learning curve model for manual assembly performance improvement
Author(s) -
Vytautas Kleiza,
Justinas Tilindis
Publication year - 2016
Publication title -
nonlinear analysis modelling and control
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.734
H-Index - 32
eISSN - 2335-8963
pISSN - 1392-5113
DOI - 10.15388/na.2016.6.7
Subject(s) - learning curve , function (biology) , production (economics) , curve fitting , learning effect , computer science , mathematics , artificial intelligence , machine learning , evolutionary biology , biology , economics , macroeconomics , microeconomics , operating system
In this paper, an almost learning curve (ALC) model is presented. This provides a more accurate approximation of the production data than the traditional log-linear learning curve model. The proposed ALC model is based on the solution of differential equations and still has all the necessary log-linear learning curve function properties. The ALC model was tested on the wiring harness manufacturer production data. Findings suggest that the ALC model approximates data accurately and is superior to the classical learning curve (CLC) for various manufacturing situations. Moreover, the use of the ALC showed an additional insight into the analysis of learning and skill development.
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