Implementation of total productive maintenance in food industry: a case study

Author:

Tsarouhas Panagiotis

Abstract

PurposeThe purpose of this paper is to adopt the total productive maintenance (TPM) in the food industry and especially in bakery products. The paper aims to develop a methodology for increasing production rate, improving the quality of the products and providing a healthier and safer work environment.Design/methodology/approachThe methodology is based on analysing the reliability data of an automatic production line. It is divided into four steps, whose aims are to bring forth improved maintenance policies of the mechanical equipment. Also, the continuous and thorough inspection of the production process is achieved through measurements of the overall equipment effectiveness (OEE).FindingsThe goal of development methodology is to bring competitive advantages, such as: increasing the productivity; improving the quality of the products; and reducing the cost production of the line.Practical implicationsThe development methodology in the food industry increases the production rate, improving the quality of the products and providing a healthier and safer work environment. It can be useful to guide food product machinery manufacturers and bread and bakery products manufacturers to improve the design and operation of the production lines that they manufacture and operate.Originality/valueThis paper presents the implementation of TPM in a pizza production line and, using certain assumptions, the generalization of the results in bakery production lines.

Publisher

Emerald

Subject

Industrial and Manufacturing Engineering,Strategy and Management,Safety, Risk, Reliability and Quality

Reference43 articles.

1. Aerospace (1999), “Aerospace supplier blasts off with TPM”, Industrial Maintenance & Plant Operation, Vol. 60 No. 9, pp. 44‐6.

2. Al‐Najjar, B. and Alsyouf, I. (2003), “Selecting the most efficient maintenance approach using fuzzy multiplecriteria decision making”, International Journal of Production Economic, Vol. 84 No. 1, pp. 85‐100.

3. Babicz, G. (2000), “Teach operators maintenance”, Quality, Vol. 39 No. 11, pp. 72‐3.

4. Bain, L.J. and Engelhardt, M. (1991), Statistical Analysis of Reliability and Life‐Tesing Models, 2nd ed., Marcel Dekker, New York, NY.

5. Bohoris, G.A., Vamvalis, C., Tracey, W. and Ignatiadou, K. (1995), “TPM implementation in Land‐Rover with the assistance of a CMMS”, Journal of Quality in Maintenance Ergineering, Vol. 1 No. 4, pp. 3‐16.

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