Recently, benchmarking has become a common approach to optimize production processes by comparing certain aspects of a company with its competitors. However, one of the biggest challenges is not only to define suitable benchmarking topics and partners, to gather and statistically evaluate characteristic data, but to derive concrete measures to interpret the results, i.e. to overcome the revealed weaknesses. The purpose of this paper is to present an already implemented and successfully used functional benchmarking methodology for production performance of small and medium batch size processes, that is currently extended by using a knowledge base for reasoning strategies to semi‐automatically support the interpretation of the extracted statistical data.
A comprehensive approach is presented to develop a new model for the evaluation of a small to medium‐sized enterprise's production performance using an existing European database called BETT Benchmark.
The knowledge‐based concept enables sophisticated interpretation strategies to be used on an already existing base of real company data. The decisive point of the approach presented is to map production variables on room for improvement by taking varying parameters into account.
The proposed tool is a valuable tool that takes advantage of a statistically firmed analysis of a substantial database and combines it with the comprehensive expertise of experienced specialists in the field of performance assessment.
Denkena, B., Apitz, R. and Liedtke, C. (2006), "Knowledge‐based benchmarking of production performance", Benchmarking: An International Journal, Vol. 13 No. 1/2, pp. 190-199. https://doi.org/10.1108/14635770610644673Download as .RIS
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