Identification of bottlenecks to improve equipment availability: a case study

Sarat Kumar Jena and Sidhartha S. Padhi

International Journal of Data Analysis Techniques and Strategies, 2011, vol. 3, issue 1, 105-116

Abstract: In this highly competitive market where the demand for the products is increasing gradually, it is essential for a manufacturing company to reduce the production cycle time and cost accordingly. One of the methods for this is to increase the availability of process. This paper attempts to identify and quantify the causes of machine downtime in a manufacturing company. For this a four-prong approach is taken: Firstly, the major causes for the low availability of process are determined, where bearing failure is found to be the major causes of low availability. Second, combining desirability function approach and data envelopment analysis are performed to identify the sensitive input variables that affect the bearing failure. Thirdly, ordinary linear regression is used to validate the results of DEA. Lastly, some managerial implications to reduce the downtime were suggested. We have considered an electrolytic tinplating line process in a tin sheet manufacturing company as a case study.

Keywords: data envelopment analysis; DEA; linear regression; machine availability; machine downtime; desirability function; bottleneck identification; bottlenecks; manufacturing equipment; bearing failure; electrolytic tinplating; tin sheet manufacturing. (search for similar items in EconPapers)
Date: 2011
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Persistent link: https://EconPapers.repec.org/RePEc:ids:injdan:v:3:y:2011:i:1:p:105-116

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