An almost learning curve model for manual assembly performance improvement
Articles
Vytautas Kleiza
Vytautas Magnus University, Lithuania
Justinas Tilindis
AQ Wiring Systems UAB, Lithuania
Published 2016-11-25
https://doi.org/10.15388/NA.2016.6.7
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Keywords

mathematical modeling
differential equation
optimization of data fitting
learning curve

How to Cite

Kleiza, V. and Tilindis, J. (2016) “An almost learning curve model for manual assembly performance improvement”, Nonlinear Analysis: Modelling and Control, 21(6), pp. 839–850. doi:10.15388/NA.2016.6.7.

Abstract

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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