• Journal of Korean Institute of Industrial Engineers
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• v.35 no.1
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• pp.15-39
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• 2009

Advanced planning and scheduling (APS) refers to a manufacturing management process by which raw materials and production capacity are optimally allocated to meet demand. APS is especially well-suited to environments where simpler planning methods cannot adequately address complex trade-offs between competing priorities. However, most scheduling problems of APS in the real world face both inevitable constraints such as due date, capability, transportation cost, set up cost and available resources. In this survey paper, we address three crucial issues in APS, including basic scheduling model, job-shop scheduling (JSP), assembly line balancing (ALB) model, and integrated scheduling models for manufacturing and logistics. Several evolutionary algorithms which adapt to the problems are surveyed and proposed; some test instances based on the practical problems demonstrate the effectiveness and efficiency of evolutionary approaches.

• Journal of the Korea Safety Management & Science
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• v.9 no.3
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• pp.119-125
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• 2007

As competition in manufacturing enterprise is contested, the scope of safely production planning, manufacturing enterprise should ensure, has been reduced. The more upstream of SCM, the more reduction of scope of production planning. As a result, order fluctuation is more sharply contested. Through improving the logistics network, it is best way that the end user's demand information is conveyed to upstream of SCM, but it is difficult in fact. In this paper, it mention the way of robustic adjustment, in the suppliers' point of view, the end user's demand information is dammed up, as they postpone responding the customer's order as a possible. And it will show the result of appling the way, as a case study.

• Journal of Korean Society for Quality Management
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• v.22 no.1
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• pp.188-204
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• 1994

Most of computer-aided process planning(CAPP) systems have been developed to automate the process planning function. In this paper, we describe an analytical model for a CAPP system in order to improve the performance of production system in flexible manufacturing systems(FMSs) for computer intergrated manufacturing(CIM) architecture. This paper proposes an optimal process planning that minimizes the load time by minimizing the cycle time and the number of workstations using Kang and Hahm's heuristic approach so as to improve the performance of production system under the batch production of discrete products. We also perform simulation using SIMAN language to campare the line utilization of each for various product types. The proposed algorithm can be implemented in existing FMSs for on-line control of product quantity using programmable logic controllers(PLC) and communication devices.

• Journal of the Korean Society for Precision Engineering
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• v.23 no.11 s.188
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• pp.68-77
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• 2006

Nowadays, the increasing global competition forces automobile manufacturer to increase quality and to reduce the cost and time for manufacturing planning. To solve these problems, automobile manufacturers try to apply digital manufacturing technologies. In this paper, a concept of method for planning the digital assembly system is proposed. Based on the requirements of assembly tasks obtained through product analysis, the function and sequence modeling for assembly process is executed using the IDEF0 and UML model. For implementation of digital assembly system, the selected components are modeled by using 3D CAD tools. According to the system configuration strategy, lots of the alternative solutions for the assembly system are generated. Finally, the optimal assembly system is chosen by the evaluation of the alternative solutions with TOPSIS(Technique for Order Preference by Similarity to Ideal Solution) method. According to proposed procedure, digital laser welding system is implemented in DELMIA.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.24 no.63
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• pp.101-110
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• 2001

This study is concern with the design of experiment planning for quality improvement in flow shop manufacturing system. In this study, the procedure of two stage experiment planning are proposed and applied to the manufacturing process of Li/$MnO_2$ batteries. The result of in this paper is that, compared with the current process conditions, 52% of the insulation inspection process, 81.6% of the first premier discharge process, 98.5% of the second premier discharge process, 84.7% of O.C.V./C.C.V. process, and 86.2% of voltage inspection process are decreased. After a given period of time, the life of the batteries extends to 75 hours, which means the 15% improvement in capacity. In case that the proposed methods are applied to the process Improvements of the flow shop manufacturing system, the much effected in experimental cost- saving and quality improvement.

• Industrial Engineering and Management Systems
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• v.9 no.3
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• pp.227-241
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• 2010

A memory module industry's supply chain usually consists of multiple manufacturing sites and multiple distribution centers. In order to fulfill the variety of demands from downstream customers, production planners need not only to decide the order allocation among multiple manufacturing sites but also to consider memory module industrial characteristics and supply chain constraints, such as multiple material substitution relationships, capacity, and transportation lead time, fluctuation of component purchasing prices and available supply quantities of critical materials (e.g., DRAM, chip), based on human experience. In this research, a directed graph-based supply network planning (DGSNP) model is developed for memory module industry. In addition to multi-site order allocation, the DGSNP model explicitly considers production planning for each manufacturing site, and purchasing planning from each supplier. First, the research formulates the supply network's structure and constraints in a directed-graph form. Then, a proposed genetic algorithm (GA) solves the matrix form which is transformed from the directed-graph model. Finally, the final matrix, with a calculated maximum profit, can be transformed back to a directed-graph based supply network plan as a reference for planners. The results of the illustrative experiments show that the DGSNP model, compared to current memory module industry practices, determines a convincing supply network planning solution, as measured by total profit.

• Journal of the Korean Society of Safety
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• v.34 no.6
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• pp.65-75
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• 2019

The purpose of this study was to investigate the effects of safety culture on the safety awareness and safety behaviors of manufacturing workers, and to suggest ways for manufacturing workers to understand the safety culture and improve safety awareness and safety behavior. In order to verify this, data were collected from 282 research subjects for 1 month from August 1 to 31, 2018, using the manufacturing workers in the Seoul and Gyeonggi area as a population. The results of the study are as follows. First, the safety culture (safety climate, safety procedures) has a positive effect on the safety awareness (recognition of importance, interest and participation inducement) of the manufacturing workers. Second, the safety culture (safety climate, safety procedures) has a positive effect on the safety behavior (safety planning, safety check) of manufacturing workers. Third, safety awareness (recognition of importance, interest and inducement of participation) has a positive influence on the safety behavior (safety planning, safety check) of manufacturing workers. Fourth, the safety awareness (recognition of importance, interest and inducement of participation) appears to have a partial mediating effect in relation to safety culture (safety climate, safety procedure) and safety behavior (safety planning, safety check) of manufacturing workers. The implication of this study is that although the industrial accidents have occurred in the manufacturing industry in recent years, the studies on the workers in the manufacturing industry are insufficient. However, this study is meaningful that it has suggested ways for manufacturing workers to understand the safety culture and improve the safety awareness and safety behavior by analyzing the effects of safety culture on safety awareness and safety behavior of manufacturing workers.

• Journal of Korean Society of Rural Planning
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• v.14 no.3
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• pp.37-51
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• 2008

This study aims to build a model dealing with the location decision of new manufacturing firms and their land demand. The model is composed with 1) the binary logit model structure identifying a future probability of manufacturing firms to locate in a city and their land demand; and 2) the land use suitability of the land demand. The model was empirically tested in the case of Anseong City. We used establishment-level data for the manufacturing industry from the Report on Mining and Manufacturing Survey. 48 industry groups were scrutinized to find the location probability in the city and their land demand via logit model with the dependent variables: number of employment, land capital, building capital, total products, and value-added for a new industry since 2001. It is forecasted that the future land areas (to 2025) for the manufacturing industries in the city are $5.94km^2$ and additional land demand for clustering the existing industries scattered over the city is $2.lkm^2$. Five industrial complex locations were identified through the land use suitability analysis.

• International Journal of Quality Innovation
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• v.6 no.2
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• pp.59-89
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• 2005

Manufacturing Resources Planning (MRPII) is one kind of manufacturing information system that can help manufacturing companies gain competitive advantages. It is estimated that more than one hundred MRPII systems are available in the market, many of them are mature enough to solve most operational issues in accordance with users' requirements. More often than not, many of these systems provide more functions than a company expects. Manufacturing companies worldwide have attempted to implement these MRPII systems, however, many companies experienced failure (Turbide, 1996) due to managerial rather than technical issues. The authors propose an approach utilising a roadmap to integrate BPR and the MRPII implementation in order to overcome this difficulty. A detail road map is developed to guide this implementation, which is designed using a hierarchical analysis technique known as Integrated DEFinition Method (IDEF). IDEF is a systematic manufacturing management and integration-modeling tool. The proposed approach is implemented and illustrated using a reference company and the results indicated that 66% reduction in errors for maintaining the bills of materials system; 99% reduction in time to carry out material requirement planning; and 70% reduction in time previously taken for non-productive discussions.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1995.04a
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• pp.185-192
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• 1995

A common control model used to implement computer integrated manufacturing(CIM) is based on the hierarchical decomposition of the shop floor activities, in which supervisory controllers are responsible for all the interactions among subordinates. Although the hierarchical control philosophy provides for easy understanding of complex systems, an emerging manufacturing paradigm, agile manufacturing, requires a new control structure necessary to accommodate the rapid development of a shop floor controller. This is what is called CSCW(computer supported cooperative work)-based control or component-based heterarchical control. As computing resources and communication network on the shop floor become increasingly intelligent and powerful, the new control architecture is about to come true in a modern CIM system. In this paper, CSCW-based control is adopted and investigated, in which a controller for a unit of device performs 3 main functions - planning, scheduling and execution. In this paper, attention is paid to a planning function and all the detailed planning activities for CSCW-based shop floor control are identified. Interactions with other functions are also addressed. Generally speaking, planning determines tasks to be scheduled in the future. In other words, planning analyzes process plans and transforms process plans into detailed plans adequate for shop floor control. Planning is also responsible for updating the process plan and identifying/resolving replanning activities whether they come from scheduling or execution.