Abstract

Efficient business organizations must balance quality, cost, and time constraints in competitive environments. Reflecting the complexity of this task, we consider manufacturing systems including several stages of production chains requiring time measurement. When production scheduling is not prioritized in such enterprises, several negative effects may occur. A corporation may suffer financial penalties as well as negative brand exposure, and thus may find its credibility challenged. Therefore, in this study, we propose constructive methods to minimize a total tardiness criterion, considering preventative maintenance constraints to reflect the reality of industrial practice, focusing on a no-wait flowshop environment in which jobs are successively processed without operational interruptions. In addition to proposing constructive methods to solve the no-wait flowshop production scheduling problem, a metaheuristic is presented as an approach to improve results obtained by constructive methods. Computational experiments were designed and performed to compare several production scheduling algorithms. Among various constructive heuristics considered, an algorithm called HENLL using an insertion logic showed the best performance. The proposed metaheuristic is based on the iterated greedy (IG) search method, and the results obtained demonstrated significant improvement compared to the heuristics alone. It is expected that this study may be used by production planning and control (PPC) professionals to apply the proposed method to schedule production more efficiently. We show that the proposed method successfully presented a better solution in relation to total tardiness, considering the above mentioned environment.

Highlights

  • Production scheduling is among the most important activities in the operations of manufacturing systems, because it is responsible for scheduling jobs on machines and specifying the times each job must be performed (Ruiz et al, 2007)

  • The problem addressed in this study is defined as a no-wait flowshop scheduling problem with the goal of minimizing the total tardiness under a preventive maintenance restriction specified as Fm|no-wait, MP(m)| ∑i Ti

  • If there is a tie in total tardiness time, select the subsequence with the lowest makespan

Read more

Summary

Introduction

Production scheduling is among the most important activities in the operations of manufacturing systems, because it is responsible for scheduling jobs on machines and specifying the times each job must be performed (Ruiz et al, 2007). The no-wait flowshop problem has been studied since the 1970s (Reddi & Ramamorthy, 1972; Wismer, 1972) It consists of processing n jobs on m machines in the same order continuously with no interruptions. Aldowaisan and Allahverdi (2012) proposed dispatch rules and heuristic methods for the Fm|no-wait| ∑i Ti problem, formulating modified due date (MDD), single machine processing time (SMPT) and earliest due date with processing time (EDDP) rules, generating an initial solution for their proposed simulated annealing (SA) and a GA. The authors tested dispatch rules based on problem data, such as processing time and delivery date, to generate an initial solution for the NEH heuristic second phase. Some authors who studied no-wait flowshop problems considering preventive maintenance in the context of alternate objective functions have proposed solutions with constructive heuristics (Miyata et al, 2019a, 2019b).

Preventive maintenance
No-wait flowshop problem with preventive maintenance and total tardiness minimization
Proposed constructive heuristics
HIN proposed algorithm
HMN proposed algorithm
HENN proposed algorithm
HENLL proposed algorithm
Proposed metaheuristics
Computational experiments
Analysis of heuristic results
Analysis of metaheuristic results compared to the best heuristic
Conclusion
Full Text
Paper version not known

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.