In the manufacturing industry, dispatching systems play a crucial role in enhancing production efficiency and optimizing production volume. However, in dynamic production environments, conventional static dispatching methods struggle to adapt to various environmental conditions and constraints, leading to problems such as reduced production volume, delays, and resource wastage. Therefore, there is a need for dynamic dispatching methods that can quickly adapt to changes in the environment. In this study, we aim to develop an agent-based model that considers dynamic situations through interaction between agents. Additionally, we intend to utilize the Q-learning algorithm, which possesses the characteristics of temporal difference (TD) learning, to automatically update and adapt to dynamic situations. This means that Q-learning can effectively consider dynamic environments by sensitively responding to changes in the state space and selecting optimal dispatching rules accordingly. The state space includes information such as inventory and work-in-process levels, order fulfilment status, and machine status, which are used to select the optimal dispatching rules. Furthermore, we aim to minimize total tardiness and the number of setup changes using reinforcement learning. Finally, we will develop a dynamic dispatching system using Q-learning and compare its performance with conventional static dispatching methods.

This paper presents a method to measure the similarity of assigned jobs in the gravure printing operation based on the chromaticity and color sequence, and order the jobs accordingly. The proposed dispatching rule can be used to fulfill diverse manufacturing site requirements because the parameters can be adjusted to prioritize chromaticity and color sequence. In general, dispatching rules either ignore the job-changing time or require that the time be clearly defined. However, in the gravure printing operation targeted in this study, it is difficult to apply the general dispatching rule because of the difficulties in quantifying the job-changing time. Therefore, we propose a method for generalizing assignment rules of the job planner, allocating relative similarity among assigned jobs, and determining the sequence of jobs accordingly. Chromaticity priority is determined by the arrangement of the color assignments in the printing operation; color sequence priority is determined by the addition, deletion, or change in a specific color sequence. Finally, the job similarity is determined by the dot product of the chromaticity and color sequence priorities. Implementation of the proposed dispatching rule at an actual manufacturing site showed the planner present the same job order as that obtained using the proposed rule. Therefore, this rule is expected to be useful in industrial sites where clear quantification of the job-changing time is not possible.

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.

The up-to-date small and medium-sized enterprises (SMEs) in Korea have tried to respond flexibly and rapidly to dynamic business environment and to establish efficient production management system based on information technologies. However, most of SMEs have faced with low applicability of the production management system resulting from high costs of introduction and maintenance. In this paper, a production planning and control system, that is S-PMS (production management system for SMEs), is proposed to solve the problem of low applicability and limited human resources. S-PMS enables production managers to efficiently collect and manage master data with the actual target production systems and explores the bottleneck process by means of simulation techniques to improve productivity. Furthermore, it implements rescheduling mechanism in terms of a variety of process routes. In essence, intuitive dispatching rules and integrated data management of S-PMS improve field applicability of production management system. Consequently, S-PMS is expected to be used as an efficient production management system of SMEs in Korea.

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.

This paper considers an inbound ordering and outbound dispatching problem for multi-products and multi-vehicles in a third-party distribution center. The demands are dynamic over a discrete and finite time horizon, and replenishing orders are shipped in various transportation modes and the freight cost is proportional to the number of vehicles used. Any mixture of products is loaded onto any type of vehicles. The objective of the study is to simultaneously determine the inbound lot-sizes, the outbound dispatching sizes, and the types and numbers of vehicles used to minimize total costs, which consist of inventory holding cost and freight cost. Delivery time window is one of the general dispatching policies between a third-party distribution center and customers in practice. In the policy, each demand of product for a customer must be delivered within the time window without penalty cost. We derive mixed integer programming models for the dispatching policy with delivery time windows and on-time delivery dispatching policy, respectively and analyze the effect on a dispatching policy with delivery time windows by comparing with on-time delivery dispatching policy using various computational experiments.

A cross docking operation involves multiple inbound trucks that deliver items from suppliers to a distribution center and multiple outbound trucks that ship items from the distribution center to customers. Based on customer demands, an inbound truck may have its items transferred to multiple outbound trucks. Similarly, an outbound truck can receive its consignments from multiple inbound trucks. The objective of this study is to find the best truck spotting sequence for both inbound and outbound trucks in order to minimize total operation time of the cross docking system under the condition that multiple visits to the dock by a truck to unload or load its consignments is allowed. The allocations of the items from inbound trucks to outbound trucks are determined simultaneously with the spotting sequences of both the inbound and outbound trucks.

Customers are generally requiring a variety of products, earlier due date, and lower price. A manufacturing process needs the efficient scheduling to meet those customer's requirements. This study proposes the novel algorithm named MJA(Minimum Job completion time and AGV time) that increases the performance of machines and AGV(Automated Guided Vehicles) in many kinds of job types. MJA optimizes the bottleneck of machines and efficiency of AGV with considering two types of dispatching at the same time. Suggested algorithm was compared with existing heuristic methods by several simulations, it performed better for reducing the time of tardiness.

이 논문에서는 지진이나 해일과 같은 자연재해가 발생했을 때 생존자의 수를 최대화하기 위한 응급차량의 배차문제에 대하여 살펴본다. 이 경우에는 도로 네트워크상에서 최단거리에 있으리라 예상되는 환자부터 실어 나르는 스케줄링 규칙을 많이 이용한다. 이 스케줄링 규칙을 SEPT(Shortest Expected Processing Time)라고 한다. 이 논문에서는 SEPT보다 효율적이라 생각되는 새로운 스케줄링 규칙을 제안한다. 이 스케줄링 규칙은 처리시간과

The purpose of this paper is to develop an efficient production strategy with changing factors to influence the productivity. The factors would be the number of Multi-Function worker, the method of job dispatching, and lot size. A simulation model has been developed for this study. We used AutoMod simulation and the process activity was animated to follow the flow of process easily. The alternatives have been tested through the simulation model, and the various alternatives is proposed for the efficient production strategy. We hope that the system is applied to similar types of small and medium-sized enterprises to develop an efficient production strategy and to achieve the satisfactory result.

The purpose of this paper is to develop an efficient production strategy with changing factors to influence the productivity. The factors would be the number of Multi-Function worker, the method of job dispatching, and lot size. A simulation model has been developed for this study. We used AutoMod simulation and the process activity was animated to follow the flow of process easily. The alternatives have been tested through the simulation model, and the various alternatives is proposed for the efficient production strategy. We hope that the system is applied to similar types of small and medium-sized enterprises to develop an efficient production strategy and to achieve the satisfactory result.

  This study presents the new dispatching rules for improving performance measures of job shop scheduling related to completion time and due dates. The proposed dispatching rule considers information, which includes the comparison value of job workload, w

  The potential needs as well as visible needs of customer should be considered in order to research and analyze of the customer data. The methods to analyze customer data is classified into customer segmentation, clustering analysis model, forecasting cu

This study presents the new dispatching rules of job shop scheduling with auxiliary resource constraint to improve the schedule performance measures related to completion time and due dates. The proposed dispatching rules consider the information of total

본 연구에서는 반도체 업체인 M사의 공정을 조사하고 현재 M사의 일정계획 순서와 기존에 연구되었던 일정계획 방법에 대한 결과를 조사한 후 CLV 알고리즘을 적용한 일정계획 기법을 시뮬레이션을 통해 비교 분석하고 알고리즘에 대한 타당성을 검증하고자 한다. CLV 알고리즘을 통한 고객 분류에 의해서 ATP rule을 적용한다면 생산 공정상의 일정계획이 조정되어 고객이 원하는 납기 준수를 달성할 수 있을 것이다. 또한 기존 연구와의 비교 분석을 위하여 시뮬레이션의 수행은 기존 연구 수행일과 동일한 시간(2003년 11월12월)을 기준으로 수행하였다.

This study presents the new dispatching rules of job shop scheduling with auxiliary resource constraint to improve the schedule performance measures related to completion time and duedates. The proposed dispatching rules consider the information of total work remaining and machine utilization to decrease mean flowtime and mean tardiness. The results of computer experiments show that those schedule performances are significantly improved by using the new dispatching rules. The results provide guidance for the researchers and practitioners of auxiliary resource constrained job shop scheduling to decrease mean flowtime and mean tardiness.

국내 반도체 산업은 불과 20년도 안되는 짧은 기간통안에 곽목할만한 성장을 하여 전세게 반도체 생산 규토 면에서 3위 국가로 부상하였으며, 기술 경쟁력 면에서도 한국인의 자존심을 그나마 지져왔다. 하지만, 반도체 제조는 가장 복잡한 제조공정의 하나로 분류되며, 이러한 복잡한 시스템을 통제하기 위해서는, 다양한 시스템 조건하에서 적절한 생산전략을 마련하는 것이 필요하다. 그러나, 반도체 제조 시스템에 대한 다양한 상황과 관련한 연구 많지 않다. 반도체 제

Scheduling semi-conductor manufacturing process systems is a complicated and difficult job due to such characteristics as reentry into manufacturing processes, high uncertainty of processes, and products and technologies changing rapidly. They have carried out many studies to find the efficient ways for semi-conductor manufacturing systems with a view to accomplishing the goals of systems like saving cycling time and increasing production quantity per unit time. The production flow in the semi-conductor industry has the most unique characteristics and makes it difficult to plan production and to schedule semi-conductor manufacturing. Currently, the scheduling methods in semi-conductor assembly processes follow the dispatching rule by simple FCFS(first come first serve). And backlog is operated as a buffer based on daily production quantity. In this study, therefore, we will apply various dispatching rules by real time basis and verify the effect and result of exact scheduling through simulation, based on the assumption that competitive advantages in production come from efficient inventory control and exact scheduling.