This study focuses on a job-shop scheduling problem with the objective of minimizing total tardiness for the job orders that have different due dates and different process flows. We suggest the dispatching rule based scheduling algorithm to generate fast and efficient schedule. First, we show the delay schedule can be optimal for total tardiness measure in some cases. Based on this observation, we expand search space for selecting the job operation to explore the delay schedules. That means, not only all job operations waiting for process but also job operations not arrived at the machine yet are considered to be scheduled when a machine is available and it is need decision for the next operation to be processed. Assuming each job operation is assigned to the available machine, the expected total tardiness is estimated, and the job operation with the minimum expected total tardiness is selected to be processed in the machine. If this job is being processed in the other machine, then machine should wait until the job arrives at the machine. Simulation experiments are carried out to test the suggested algorithm and compare with the results of other well-known dispatching rules such as EDD, ATC and COVERT, etc. Results show that the proposed algorithm, MET, works better in terms of total tardiness of orders than existing rules without increasing the number of tardy jobs.

Up-to-date business environment for manufacturers is very complex and rapidly changing. In other words, companies are facing a variety of changes, such as diversifying customer requirements, shortening product life cycles, and switching to small quantity batch production. In this situation, the companies are introducing the concept of JIT (just-in-time) to solve the problem of on-time production and on-time delivery for survival. Though many companies have introduced ERP (enterprise resource planning) systems and MRP (material requirement planning) systems, the performance of these systems seems to fall short of expectations. In this paper, the case study on introducing an APS (advanced planning and scheduling) system based on dispatching rules to a machining company and on finding a method to establish an efficient production schedule is presented. The case company has trouble creating an effective production plan and schedule, even though it is equipped with an MRP-based ERP system. The APS system is applied to CNC (computer numerical control) machines, which are key machines of the case company. The overall progress of this research is as follows. First, we collect and analyze the master data on individual products and processes of the case company in order to build a production scheduling model. Second, we perform a pre-allocation simulation based on dispatching rules in order to calculate the priority of each order. Third, we perform a set of production simulations applying the priority value in order to evaluate production lead time and tardiness of pre-defined dispatching rules. Finally, we select the optimal dispatching rule suitable for work situation of the case company. As a result, an improved production schedule leads to an increase in production and reduced production lead time.