A Production Scheduling Model with Maintenance

Article Preview

Abstract:

In the paper, a production model with maintenance is presented. Successive failure-free times of a bottleneck are supposed to have predefined distributions and are followed by distributed times of repair. Having values of parameters: Mean Time To Failure and Mean Time of Repair, a predictive schedule is generated. To assess wastes due to unplanned events of the bottleneck, such as unplanned downtime the Overall Equipment Effectiveness indicator is applied. To assess failure rate of the bottleneck the Parts Per Million Opportunities indicator is applied. Prediction capability, detection capability of a failure and effects of the failure occurrence are evaluated and registered in the Exploitation Failure Mode and Effects Analysis form. The objective of the presented predictive scheduling model is to achieve: zero machines failures, zero defects, zero accidents at work.

You might also be interested in these eBooks

Info:

Periodical:

Pages:

885-890

Citation:

Online since:

October 2014

Export:

Price:

* - Corresponding Author

[1] L. Liu, H. Gu, Y. Xi, Robust and stable scheduling of a single machine with random machine breakdowns, Int J Adv Manuf Technol, Vol. 31, (2007), pp.645-656.

DOI: 10.1007/s00170-005-0237-0

Google Scholar

[2] J. Gao, M. Gen, L. Sun: Scheduling jobs and maintenances in flexible job shop with a hybrid genetic algorithm. I Intell Manuf, Vol. 17 (2006), pp.493-507.

DOI: 10.1007/s10845-005-0021-x

Google Scholar

[3] D. Lei: Scheduling fuzzy job shop with preentive maintenance through swarm-based nieghborhood search. Int J Adv Manuf Technol, Vol. 54 (2011), pp.1121-1128.

DOI: 10.1007/s00170-010-2989-4

Google Scholar

[4] M. B. Ali, M. Sassi, M. Gossa, Y. Harrath: Simultaneous scheduling of production and maintenance task in the job shop. Int. J of Production Research Vol. 49, No. 13, (2011), 3891-3918.

DOI: 10.1080/00207543.2010.492405

Google Scholar

[5] D. Crowe, A. Feinberg: Design for Reliability. CRC Press LLC, (2001).

Google Scholar

[6] B. Skołud, Zarządzanie operacyjne. Production in small and medium-sized enterprises (in Polish), Silesian University of Technology, Gliwice (2006).

Google Scholar

[7] I. Paprocka, B. Skołud: Robust scheduling, a production scheduling model of failures, Applied Mechanics and Materials Vol. 307 (2013), pp.443-446.

DOI: 10.4028/www.scientific.net/amm.307.443

Google Scholar

[8] G. Ćwikła, Automatic data acquisition from production systems for management support systems (in Polish). Selected Engineering Problems, Vol. 2 (2011), pp.79-84.

Google Scholar

[9] K. Kalinowski, C. Grabowik, I. Paprocka, W. M. Kempa: The model of discrete production scheduling system in UML notation. Advanced Materials Research, vol. 837 (2014), pp.416-421.

DOI: 10.4028/www.scientific.net/amr.837.416

Google Scholar

[10] W. M. Kempa, I. Paprocka, K. Kalinowski, C. Grabowik: Estimation of reliability characteristics in a production scheduling model with failures and time-changing parameters described by Gamma and exponential distributions. Advanced Materials Research, vo. 837 (2014).

DOI: 10.4028/www.scientific.net/amr.837.116

Google Scholar

[11] I. Paprocka, W.M. Kempa: Estimation of reliability characteristics in a production scheduling model with the renewal theory application – second part, numerical example, Infor. Sys. Arch. and Tech., The Use of IT Models for Organization Management, Wrocław 2012, pp.59-68.

Google Scholar

[12] W. Janik, P. Gendarz, Disassembly and aggregation in computer aided overhaul preparation, Journal of Achievements in Materials and Manufacturing Engineering 44/2 (2011), pp.187-197.

Google Scholar