Fuzzy set theory-based model for identifying the potential of improving process KPIs in production logistics area
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Abstract
The high complexity of today’s manufacturing environment brings many problems with planning and managing, especially production, logistic and other key business processes. In many cases, it is quite complicating to identify the real causes of problems that enterprises face or to decide which one of them should be solved first. Especially, in the case of large enterprises, it is complicating to access expertise among all departments and employed professionals in order to solve the problems most efficiently. Our fuzzy model provides a simple tool for easy identification of the most significant problems of observed processes that cause their low performance according to the measured values of their key performance indicators. The model is based on data gained through interviews with production managers, industry experts and other professionals, and verified by real data from a model company. The results are presented in the form of case studies in this contribution.
Keywords: Production logistics, key performance indicators, KPI, productivity, problem identification, fuzzy set theory, process.
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