Abstract
Simulation is essential when studying manufacturing processes or designing production systems. This project was a real case study which involved a job shop with five similar CNC milling machines. A total of six jobs were performed and each of them consisted of a different set of operations. The sequence of the six jobs to enter the system was determined by the sequencing rules including shortest setup time (SST), shortest processing time (SPT), shortest processing and setup time (SPST), earliest due date (EDD), least process (LP), and lowest volume (LV). The setup time was taken into consideration to make the results more realistic. Due to the complexity of the model, WITNESS was used to simulate all the sequencing rules. The best approach was then determined by comparing the results of each rule. By doing this, the case company would be able to make a better decision on which job should be processed first instead of selecting it randomly among the jobs.
Highlights
The objectives of this study are to apply various sequencing rules in a company with a high-mix-low-volume manufacturing environment and to simulate all the sequencing rules in order to suggest the best approach for manufacturing multiple high-mix-low-volume products
The sequence of the six jobs to enter the system was determined by the sequencing rules including shortest setup time (SST), shortest processing time (SPT), shortest processing and setup time (SPST), earliest due date (EDD), least process (LP), and lowest volume (LV)
The performance of the six sequencing rules was measured in two aspects which were emphasized by the case company; they were average work in progress (WIP) and average total completion time
Summary
The objectives of this study are to apply various sequencing rules in a company with a high-mix-low-volume manufacturing environment and to simulate all the sequencing rules in order to suggest the best approach for manufacturing multiple high-mix-low-volume products. The most common high-mix-low-volume environment is in a job shop. This project is a simulation-based experimental study of sequencing rules for scheduling a dynamic job shop with five similar CNC milling machines. The job-shop scheduling problem (JSSP) is one of the most critical problems in scheduling (Jayamohan and Rajendran, 2004). It aims to allocate a number of machines over time to perform a set of jobs with certain constraint conditions in order to optimize a certain criterion for example, minimizing the make-span (Yang et al, 2010). The choice of a sequencing rule depends on which criterion is intended to be improved upon (Holthaus and Rajendran, 1997)
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