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Modeling errors in parts supply processes for assembly lines feeding

Modeling errors in parts supply processes for assembly lines feeding PurposeThe purpose of this paper is to develop a quantitative model to assess probability of errors and errors correction costs in parts feeding systems for assembly lines.Design/methodology/approachEvent trees are adopted to model errors in the picking-handling-delivery-utilization of materials containers from the warehouse to assembly stations. Error probabilities and quality costs functions are developed to compare alternative feeding policies including kitting, line stocking and just-in-time delivery. A numerical case study is included.FindingsThis paper confirms with quantitative evidence the economic relevance of logistic errors (LEs) in parts feeding processes, a problem neglected in the existing literature. It also points out the most frequent or relevant error types and identifies specific corrective measures.Research limitations/implicationsWhile the model is general purpose, conclusions are specific to each applicative case and are not generalizable, and some modifications may be required to adapt it to specific industrial cases. When no experimental data are available, human error analysis should be used to estimate event probabilities based on underlying modes and causes of human error.Practical implicationsProduction managers are given a quantitative decision tool to assess errors probability and errors correction costs in assembly lines parts feeding systems. This allows better comparing of alternative parts feeding policies and identifying corrective measures.Originality/valueThis is the first paper to develop quantitative models for estimating LEs and related quality cost, allowing a comparison between alternative parts feeding policies. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Industrial Management & Data Systems Emerald Publishing

Modeling errors in parts supply processes for assembly lines feeding

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References (71)

Publisher
Emerald Publishing
Copyright
Copyright © Emerald Group Publishing Limited
ISSN
0263-5577
DOI
10.1108/IMDS-08-2016-0333
Publisher site
See Article on Publisher Site

Abstract

PurposeThe purpose of this paper is to develop a quantitative model to assess probability of errors and errors correction costs in parts feeding systems for assembly lines.Design/methodology/approachEvent trees are adopted to model errors in the picking-handling-delivery-utilization of materials containers from the warehouse to assembly stations. Error probabilities and quality costs functions are developed to compare alternative feeding policies including kitting, line stocking and just-in-time delivery. A numerical case study is included.FindingsThis paper confirms with quantitative evidence the economic relevance of logistic errors (LEs) in parts feeding processes, a problem neglected in the existing literature. It also points out the most frequent or relevant error types and identifies specific corrective measures.Research limitations/implicationsWhile the model is general purpose, conclusions are specific to each applicative case and are not generalizable, and some modifications may be required to adapt it to specific industrial cases. When no experimental data are available, human error analysis should be used to estimate event probabilities based on underlying modes and causes of human error.Practical implicationsProduction managers are given a quantitative decision tool to assess errors probability and errors correction costs in assembly lines parts feeding systems. This allows better comparing of alternative parts feeding policies and identifying corrective measures.Originality/valueThis is the first paper to develop quantitative models for estimating LEs and related quality cost, allowing a comparison between alternative parts feeding policies.

Journal

Industrial Management & Data Systems – Emerald Publishing

Published: Jul 10, 2017

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