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.

Up to date cosmetic OEM/ODM (original equipment manufacturing/original development manufacturing) industry receives attention as a future growth engine due to steady growth. However, because of limited research and development capability, many companies have employed commercial management platforms specialized for large-sized companies; thus, overall system effectiveness and efficiency is low. Especially, MRP (material requirement planning) system introduced originally in 1970s is employed to calculate the requirement of the parts. However, dynamic nature of production lead time usually results in incorrect requirements. In addition, its algorithm does not consider the capability of the production resources. Also, because the commercial MRP system calculates all subcomponent for fixed period, the more goods have subcomponent, the slower calculation is. Therefore, conventional MRP system cannot respond complicated situation in time. In this study, we will suggest a new method that can respond to complicated situations resulting from short lead time and urgent production order in Korean cosmetic market. In particular, a distributed MRP system is proposed, that consists of multi-functional and operational modules, based on the characteristic of the BOM (bill of material). The distributed MRP system divides components (i.e. products and parts) into several fields and decrease the problem size; thus, we can respond to dynamically changed data any time. Through this solution, we can order components quickly, adjust schedules and planned quantity, and manage stocks reasonably. In addition, a prototype of the distributed MRP system is presented in this paper, in which ERP (enterprise resource planning) sever data is associated with an excel spreadsheet via MSsql. System user interface is implemented by a VBA (visual basic for applications) tool. According to a case study, response rate for delivery and planning achievement rate were enhanced about 20%, and inventory turnover was also decreased. Consequently, the proposed system improves overall profit.

The up-to-date business environment for Korean manufacturers is very complex and rapidly changing. Especially, the companies have faced with various changes derived from small quantity batch production, diversification of customer demands, and short life cycles of products. Consequently, the Korean manufacturing companies are in need of more efficient production planning and scheduling techniques. In this paper, the research trend of scheduling techniques is investigated to provide relevant information to researchers in this field. Furthermore, some implications for future researches are presented regarding literatures published in Korea over the last 10 years. This paper presents an entire investigation into Korean research works on scheduling (2,569 papers) that are published from 2007 to 2016. Especially, detailed analysis was carried out in the following three industry : 1) semiconductor, 2) shipbuilding and 3) automobile. In this paper, approaches to scheduling presented in the literature are categorized into the following three categories : 1) application, 2) algorithm, and 3) simulation modeling. First, in the semiconductor industry, scheduling techniques related to semiconductor cleaning processes, photolithography processes, chemical processes, transport and transport equipment have been found to be dominant. Second, the shipbuilding industry is focused on assembly processes, transporter, crane and various existing production management system. On the other hand, the scheduling research of the automobile industry is mainly focused on the vehicle movement routing and procurement supply-chain planning algorithm in terms of logistics. The conclusion of this study are expected to provide many implications for various types of academic and practical follow-up studies related to scheduling in consideration of main characteristics of semiconductor, shipbuilding and automobile industries.

Up-to-date manufacturing companies have faced a market-driven environment of pull production order. There should be a difference in operating manufacturing resources according to the type, quantity, and delivery time of manufactured products, because the process situation in pull production is changed by customer orders. And it should be taken into account from the stage of preparing for production such as process design and the placement and utilization of manufacturing resources. However, the feasibility of production plans is limited because most of small manufacturing businesses make production/supply plan of the parts and products assuming that equipment abilities in scheduling is sufficient without managing process standard information systemically. In this study, a discrete event simulation system based on BOM (bill of material), that is F-OPIS (online productivity innovation system), is introduced and a case study on application of the system leading to improving productivities is presented. F-OPIS deals with a decision-problem on production management and it is specialized for small-and- medium sized manufacturing companies. The target company of this case study is a typical small-and-medium sized manufacturing company in Korea, that produces various machined parts. The target company adopts make-to-stock production management to prevent tardy delivery because of fluctuations in demand. Therefore, it is required to apply an efficient inventory control solution for improving productivities. In this paper, based on the constraints of working capacity of manufacturing resources, the bottleneck process is analyzed as production conditions are changed. Consequently, an improvement plan is proposed, that eventually enhances overall utilization rates of resources in the bottleneck process and reduces overall production lead-time and inventory level.

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.