Integrated simulation tool for quality support in the low-volume high-complexity electronics manufacturing domain

Low-volume high-complexity printed circuit board manufacturing is a highly dynamic domain because of prevailing global pressures. In such an evolving environment, quality issues caused by manufacturing defects are the major concern. The generation, detection and elimination of those defects further...

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Bibliographic Details
Published in:International journal of production research 2010-01, Vol.48 (1), p.45-68
Main Authors: Huertas Quintero, Lina A.M., West, Andrew A., Velandia, Diana M. Segura, Conway, Paul P., Wilson, Anthony
Format: Article
Language:English
Subjects:
Applied sciences
Decision theory. Utility theory
Defective products
Defects
Electronics
Exact sciences and technology
integration
Manufacturing
Manufacturing defects
Operational research and scientific management
Operational research. Management science
Printed circuit boards
Printed circuits
Product quality
Reliability theory. Replacement problems
Root cause analysis
Simulation
simulation applications
Studies
Wastes
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Summary:Low-volume high-complexity printed circuit board manufacturing is a highly dynamic domain because of prevailing global pressures. In such an evolving environment, quality issues caused by manufacturing defects are the major concern. The generation, detection and elimination of those defects further impact customer requirements and demands. Current practices in terms of identification and solution of quality issues have three major drawbacks: (i) the metrics used are not meaningful; (ii) several manual operations are involved; and (iii) there is no significant decision support. A novel integrated simulation tool for quality support in low-volume electronics manufacturing that overcomes these weaknesses is presented in this paper. The simulation tool supports current needs in the domain, i.e. knowledge capitalisation, waste reduction, right-first-time performance and agility, as well as the domain customer requirements, i.e. lead time, cost, quality and reliability. Quantitative results from a case study are presented as evidence of the usefulness of the tool in a real context. The results show that the approximately 80% non-value-added cost for the product studied is due to just two types of manufacturing defects. This outcome is key for root cause analysis based not only on defect quantity.
ISSN:0020-7543
1366-588X
DOI:10.1080/00207540802427886