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Optimization Methods in Continuous Improvement Models: A Relational Review

Optimization Methods in Continuous Improvement Models: A Relational Review

Brian J. Galli
Copyright: © 2019 |Volume: 6 |Issue: 1 |Pages: 14
ISSN: 2155-4153|EISSN: 2155-4161|EISBN13: 9781522567622|DOI: 10.4018/IJAIE.2019010103
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MLA

Galli, Brian J. "Optimization Methods in Continuous Improvement Models: A Relational Review." IJAIE vol.6, no.1 2019: pp.46-59. http://doi.org/10.4018/IJAIE.2019010103

APA

Galli, B. J. (2019). Optimization Methods in Continuous Improvement Models: A Relational Review. International Journal of Applied Industrial Engineering (IJAIE), 6(1), 46-59. http://doi.org/10.4018/IJAIE.2019010103

Chicago

Galli, Brian J. "Optimization Methods in Continuous Improvement Models: A Relational Review," International Journal of Applied Industrial Engineering (IJAIE) 6, no.1: 46-59. http://doi.org/10.4018/IJAIE.2019010103

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Abstract

There are numerous processes used to implement quality, such as TQM, 6 Sigma, and Lean. For these quality processes to remain effective, a continuous improvement model is required and implemented from time to time. Some of these models include Define, Measure, Analyse, Improve and Control (DMAIC); Plan, Do, Check, and Act (PDCA); Identify, Measure, Problem Analysis, Remedy, Operationalize, Validate, and Evaluate (IMPROVE); and Theory of Constraint (TOC). Furthermore, continuous improvement tools need to remain effective through the use of optimization techniques to produce the best possible outcomes. This article discusses some of the current utilization of these tools and proposes different optimizing techniques and variations to make robust quality implementation tools.