Minimizing total flow time and maximum tardiness with periodic maintenance

Abstract

Purpose -In today's industry, a machine breakdown is common for a machine running a long period of time without maintenance. To avoid a sudden breakdown, periodic maintenance is usually performed in the production system. This paper aims to find a set of efficient schedules that considers both jobs and maintenance simultaneously. Design/methodology/approach -This paper addresses a real-life scheduling problem in a plastic company. An algorithm based on the variable range technique is developed to solve the problem by providing a small set of efficient schedules. Findings -Once maintenance is performed, the job being processed must be stopped. This will result in some jobs being late or tardy and a relatively larger flow time is generated. Therefore, how to minimize these two criteria in the production system becomes an important issue in the company. Computational results show that problems with larger maintenance intervals and smaller maintaining time can produce a smaller number of efficient schedules. Practical implications -It is seen that scheduling maintenance will result in some jobs being tardy and a larger flow time is generated. A decision maker can easily select a preferred schedule from the small set of efficient schedules. The proposed algorithm is appropriate not only for the studied company but also for those companies where periodic maintenance is required. Originality/value -Presents an algorithm to find a small set of efficient schedules.

A new approach for performance assessment of parallel and non-bottleneck machines in a dynamic job shop environment

“…In addition, D je is the decision variable for job j and e in such a way that job e is proceeded by the job j. Equation (2) specifies the second objective function, which is the minimization of the maximum tardiness (Chen, 2007). Equation (3) demonstrates the constraints regarding the completion time (C j ), processing time (P j ) and the releasing date (R j ) in the dynamic job-shop environment.…”

A Mixed-integer Multi-objective Maintenance and Production Workforce Planning Model

“…Sanchez et al (2009) used a multiobjective genetic algorithm (MOGA) to optimised unavailability and cost criteria in maintenance and testing of machines under uncertainty conditions. Chen (2007) applied a combined shortest processing time and maximum tardiness scheduling model in solving the problems of maximum tardiness and minimum total flow time under periodic maintenance condition. Berrichi et al (2001) compared a multi-objective ant colony optimisation model and MOGA as solution methods for maintenance-production scheduling of parallel machines.…”

Supply chain scheduling problem in the hospital with periodic working time on a single machine

“…Xu and Xiong (2012) discussed the numerical example in Chen (2006). Akturk et al (2003), Akturk et al (2004), Qi et al (1999), Qi (2007) and Chen (2007) considered the problems to determine the job schedule and machine maintenance activities simultaneously. The more reviews can be referred to Ma et al (2010), Chen (2010) and Hadidi et al (2012).…”