Performance Improvement Methods: Not Just For Maintenance of Certification

Chiodo, Anthony E.; Rosenhauer, Eric; Worsowicz, Gregory M.

doi:10.1016/j.pmrj.2011.01.004

Cited by 2 publications

(2 citation statements)

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“…Each has its rationale with relevant features, and each approach, when deployed accurately, can yield some interesting results and sustain improvement (as described in Table 1 (Chiodo, Rosenhauer, & Worsowicz, 2011). The stepwise fashion of problem solving and the associated continuous improvement methodologies can be used at distinct levels of organization, in service and administrative as well as manufacturing processes.…”

Section: Introductionmentioning

confidence: 99%

“…A visual data mining approach can be suitable for building knowledge base in shop floor control systems of semiconductor wafer fabrication (Shiue, Guh, & Tseng, 2012). Table 1 Common continuous improvement methodologies (Chiodo et al, 2011 Since we are interested in knowledge discovery techniques that can help overcome the challenge of defining procedural knowledge, the association rule learning is chosen as knowledge discovery technique in our framework. This technique is domain independent, and can be potentially applied for modeling procedural knowledge in any domain characterized by the fact that for a given task there might be many alternative solution-strategies with an extensive range of practical solutions (Nkambou, Fournier-Viger, & Mephu Nguifo, 2011).…”

Section: Introductionmentioning

confidence: 99%

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Mining association rules for the quality improvement of the production process

Kamsu-Foguem

Rigal

Mauget

2013

Expert Systems with Applications

130

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To cite this version:Bernard Kamsu-Foguem, Fabien Rigal, Félix Mauget. Mining association rules for the quality improvement of the production process. Expert Systems with Applications, Elsevier, 2013, vol. 40, pp. 1034-1045 b s t r a c tAcademics and practitioners have a common interest in the continuing development of methods and computer applications that support or perform knowledge-intensive engineering tasks. Operations management dysfunctions and lost production time are problems of enormous magnitude that impact the performance and quality of industrial systems as well as their cost of production. Association rule mining is a data mining technique used to find out useful and invaluable information from huge databases. This work develops a better conceptual base for improving the application of association rule mining methods to extract knowledge on operations and information management. The emphasis of the paper is on the improvement of the operations processes. The application example details an industrial experiment in which association rule mining is used to analyze the manufacturing process of a fully integrated provider of drilling products. The study reports some new interesting results with data mining and knowledge discovery techniques applied to a drill production process. Experiment's results on real-life data sets show that the proposed approach is useful in finding effective knowledge associated to dysfunctions causes.

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Section: Introductionmentioning

confidence: 99%