مسئلۀ زمان بندی و تخصیص جریان کارگاهی در اورهال تجهیزات (مقاله علمی وزارت علوم)
درجه علمی: نشریه علمی (وزارت علوم)
آرشیو
چکیده
در این مقاله، یک مسئله زمان بندی جریان کارگاهی به منظور اورهال تجهیزات ارائه شده است. این مسئله شامل سه مرحله است که در مرحله اول، عملیات تفکیک اجزای یک تجهیز و در مرحله دوم، عملیات تعمیرات و اورهال بر قطعات تفکیک شده مرحله اول انجام می شود؛ سپس در مرحله سوم، قطعات اورهال شده مرحله قبل بر هم سوار می شوند. در مرحله سوم، کارگاه های موازی، عملیات را به صورت موازی انجام می دهند. تابع هدف مسئله، بیشینه زمان تکمیل کارهاست و توالی پردازش کارها باید به نحوی باشد که مقدار تابع هدف، کمینه شود. به منظور حل مسئله، یک مدل برنامه ریزی عدد صحیح آمیخته برای سایز کوچک ارائه شده است که براساس موقعیت هر کار، توالی پردازش کارها را مشخص می کند. برای حل مسئله در ابعاد بزرگ، الگوریتم ژنتیک به کار رفته است. با افزایش سایز مسئله و در سایزهای مختلف، نتایج بررسی و تجزیه و تحلیل شده است که این کارایی مدل و الگوریتم ارائه شده را نشان می دهد.Flow shop scheduling and assignment problem in equipment overhaul
Purpose: This paper aims to propose a flow shop scheduling problem for equipment overhaul. This problem consists of three stages, the separation of the components of an equipment is done in the first stage. Repairs and overhaul operations are carried out on the separated parts of the first stage in the second stage. Finally, the overhauled parts of the previous stage are mounted on each other in the third stage. In the third stage, operations are performed in parallel workshops. The objective function of the problem is the maximum time to complete jobs, and the sequence of processing jobs should be done in such a way that the value of the objective function is minimized.Design/methodology/approach: To solve the problem, a mixed integer programming model has been proposed for small size, which determines the processing sequence of jobs based on the position of each job. A genetic algorithm has been used to solve the problem in large dimensions. By increasing the size of the problem and in different sizes, the results have been examined and analyzed, which shows the efficiency of the model and the proposed algorithm.Findings: To check the accuracy of the model's performance and also the effect of the presence of parallel machines in the third stage, an example was presented in this paper. Accordingly, while the accuracy of the model's performance was checked, the effect of the presence of more machines was determined in the third stage. As the number of machines increased in the third stage, the value of the objective function did not deteriorate. The performance of GAMS in solving the problem in a small size was investigated. Considering that solving the problem for large dimensions is not possible in a reasonable time and the problem is NP-hard, then solving the problem in large dimensions was done using a genetic algorithm. Therefore, solving the problem on a large dimension has been done using the genetic algorithm. According to the obtained results, the efficiency of the genetic algorithm was shown. Due to its low average value, it indicated the convergence of the genetic algorithm.Research limitations/implications: Considering that there are not many published papers in the field of equipment overhaul, it is difficult to access related models and papers. Therefore, in this paper, the model and solution method have been written with many reviews. Also, to check and reduce costs, the number of third-stage machines has been determined using sensitivity analysis.Practical implications: The problem of equipment overhaul is used in many fields in reality. For example, the operations related to the maintenance, repair and overhaul of the aircraft engine have been investigated. Since the planning of maintenance and maintenance operations is difficult, the focus of research has been on improving maintenance operations by finding suitable scheduling for job shop operations in maintenance operations. They emphasized that scheduling can improve maintenance operations and presented a simulation model.Social implications: The purpose of creating a space to start an activity is to reduce costs, earn money and achieve profit. To examine the cost-effectiveness of the equipment overhaul issue, we can refer to the number of third-stage machines. According to the amount of equipment to perform an overhaul on them, the number of third-stage machines can be determined. Therefore, extra machines can be removed to reduce the cost. On the other hand, if the related equipment to the customers is different, to reduce the storage costs or increase customer satisfaction, different goals should be considered. Here, the objective function of maximum completion time is considered for this purpose. If the equipment must be available at a certain time, goals such as the total time to complete the job can be considered. In line with the application of the social implications in the investigated problem in this paper and considering that the investment costs, as well as the ability to respond to the applicants' requests, are related to the number of third-stage machines, the value of the objective function is analyzed based on the number of third-stage machines and analysis has been done.Originality/value: In this paper, a three-stage flow shop scheduling problem in the overhaul industry was studied. Accordingly, a new mathematical model based on the job processing position was proposed, which dealt with the exact solution of the problem in small dimensions. According to the type of problem in the overhaul environment, the combined flow shop problem for equipment overhaul was investigated. Also, the use of parallel machines in the third stage of the equipment overhaul problem is one of the new issues under investigation.
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