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State-based analysis of labour productivity

Publikationstyp
Journal Article
Date Issued
2016-05-18
Sprache
English
Author(s)
Czumanski, Thomas  
Lödding, Hermann  
Institut
Produktionsmanagement und -technik M-18  
TORE-URI
http://hdl.handle.net/11420/5731
Journal
International journal of production research  
Volume
54
Issue
10
Start Page
2934
End Page
2950
Citation
International Journal of Production Research 10 (54): 2934-2950 (2016-05-18)
Publisher DOI
10.1080/00207543.2015.1137372
Scopus ID
2-s2.0-84958536442
Establishing efficient continuous improvement processes requires industrial companies to analyse their productivity quickly on different work system levels and to link productivity losses with suitable improvement measures in the course of productivity management. Common productivity analyses are either narrowed to certain functions of a production process or they do not possess a sufficient level of detail to derive goal-oriented improvement measures. The challenge is to gain production data with a relatively low effort and to gain broad transparency over productivity losses from the work place to the company level at the same time. This paper presents a new methodology for the comprehensive analysis of the various impacts on labour productivity, relying on state-based modelling of worker activities in serial production. Typical application areas include the automotive industry or the production of home appliances. The approach combines straightforward data acquisition methods with a structured evaluation process as foundation for the productivity management on different work system levels, including work stations, production lines, production segments and the plant. An integrated matching procedure processes the analysis results and yields a set of applicable improvement methods from a definable toolset. Compared with existing methodologies, the underlying model promises a reduced data acquisition effort and high usability. Its potential for practical application is shown with two industrial case studies.
Subjects
continuous improvement
decision-making
labour productivity
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