On the complexity of using performance measures: Enhancing sustained production improvement capability by combining OEE and productivity
2015 (English)In: Journal of manufacturing systems, ISSN 0278-6125, E-ISSN 1878-6642, Vol. 35, p. 144-154Article in journal (Refereed) Published
Abstract [en]
The global speed of change within the manufacturing industry forces companies to constantly improve production performance. In that effort, performance measures are critical for driving and managing production improvements. Two of the most commonly used measures in operations are productivity and overall equipment efficiency (OEE). However, the potential of using these measures as improvement drivers is not fully utilized in industry today due, for example, to ambiguities in definitions and their interpretation. A study of available theory indicates a gap between these implications from a theoretical perspective vs. the industrial perspective. Bridging this theory-practice gap implies great potential for competitiveness and growth in manufacturing, since the latent production capacity that could be utilized is tremendous. Even if a high degree of complexity in definition and calculation when applied in operational conditions might be perceived, this paper will show that a systematically used combined set of OEE and productivity measures can successfully drive production improvements. Also, two new productivity measures for driving improvements at the shop floor level are proposed. The empirical findings are based on a two-year case study within a manufacturing company in the automotive industry using an interactive research approach.
Place, publisher, year, edition, pages
2015. Vol. 35, p. 144-154
Keywords [en]
Improvements, OEE, Performance measures, Production capability, Productivity, Automotive industry, Industrial research, Manufacture, Manufacturing companies, Manufacturing industries, Overall equipment efficiency, Performance measure, Production capabilities, Production performance
National Category
Other Engineering and Technologies
Identifiers
URN: urn:nbn:se:mdh:diva-27978DOI: 10.1016/j.jmsy.2014.12.003ISI: 000354591100011Scopus ID: 2-s2.0-84928722532OAI: oai:DiVA.org:mdh-27978DiVA, id: diva2:812111
2015-05-152015-05-152017-12-04Bibliographically approved