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dc.contributor.authorSerel, D. A.en_US
dc.contributor.authorDada, M.en_US
dc.contributor.authorMoskowitz, H.en_US
dc.contributor.authorPlante, R. D.en_US
dc.date.accessioned2016-02-08T10:29:51Z
dc.date.available2016-02-08T10:29:51Z
dc.date.issued2003en_US
dc.identifier.issn0740-817X
dc.identifier.urihttp://hdl.handle.net/11693/24467
dc.description.abstractThe reduction of variability in product performance characteristics is an important focus of quality improvement programs. Learning is intrinsically linked to process improvement and can assume two forms: (i) autonomous learning; and (ii) induced learning. The former is experientially-based, while the latter is a result of deliberate managerial action. Our involvement in quality and capacity planning with several major corporations in different industries suggested that it would be instructive to devise a model that would prescribe an optimal combination of autonomous and induced learning over time to maximize process improvement. We thus propose such a model to investigate the optimal quality improvement path for a company given that quality costs depend on both autonomous and induced types of learning experienced on a number of quality characteristics. Several properties of an optimal investment path are developed for this problem. For example, it is shown that decisions maximizing short-term gains may actually lead to suboptimal resource utilization decisions when total costs associated with a longer planning horizon are taken into account. Numerical examples are used to assess the sensitivity of the optimal investment plan with respect to changes in several model parameters.en_US
dc.language.isoEnglishen_US
dc.source.titleIIE Transactions (Institute of Industrial Engineers)en_US
dc.relation.isversionofhttp://dx.doi.org/10.1080/07408170304415en_US
dc.subjectCostsen_US
dc.subjectDecision makingen_US
dc.subjectInvestmentsen_US
dc.subjectLearning systemsen_US
dc.subjectProcess engineeringen_US
dc.subjectResource allocationen_US
dc.subjectProduct performanceen_US
dc.subjectQuality controlen_US
dc.titleInvesting in quality under autonomous and induced learningen_US
dc.typeArticleen_US
dc.departmentDepartment of Management
dc.citation.spage545en_US
dc.citation.epage555en_US
dc.citation.volumeNumber35en_US
dc.citation.issueNumber6en_US
dc.identifier.doi10.1080/07408170304415en_US
dc.publisherTaylor & Francisen_US
dc.identifier.eissn1545-8830


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