• Proceedings of the Korean Operations and Management Science Society Conference
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• 2004.05a
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• pp.167-170
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• 2004

This paper proposes resource allocation method for achieving investment goals in manufacturing system. In order to align resource allocation and manufacturing system design, the system design decomposition (SDD) approach is used. In this paper, a mathematical formulation for resource allocation based on SDD approach is analyzed and a genetic algorithm application is discussed.

• Korean Journal of Construction Engineering and Management
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• v.24 no.2
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• pp.37-49
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• 2023

In this study, we proposed resource allocation methodologies to improve the productivity of steel bridge manufacturing plants based on the constraint theory which is very popular in the area of manufacturing industries. To this end, after defining the painting process as a bottleneck, three resource allocation methodologies were developed: Operation Specific Resource Allocation (OSRA), Product Specific Resource Allocation (PSRA), and General Resource Allocation (GRA). As a result of experiments for performance evaluation using a simulation model of the steel bridge supply chain, GRA showed the best performance in terms of the Number of Work-In-Process (NWIP) and Waiting Time (WT), in particular, as workload itself and its variability were increased, the performance gap with the specific resource allocation became further deepened. On average, GRA reduced NWIP by 36.2% and WT by 34.6% compared to OSRA, and reduced NWIP by 71.0% and WT by 70.4% compared to PSRA. The reduction of NWIP and WT means alleviating the bottleneck of the painting process, which eventually means that the productivity of the steel bridge manufacturing plant has improved.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.8
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• pp.599-611
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• 2020

The purpose of this study is to explore and empirically analyze the factors affecting the financial performance of Korean small- and medium-sized manufacturing companies, which are relatively insufficiently researched, in terms of human resource management (HRM). In particular, this study intends to examine the human resource management activities focusing on the individual influences of workers' attitudes on systems and policies as well as jobs and organizations. This study reviews previous research and discussions on the human resource management system, as well as the organization and job-related attitudes and financial performance of workers, for the formulation of two hypotheses. Among the HCCP data, the hypothesis was verified through reliability and correlation analysis and stepwise multiple regression analysis for small- and medium-sized manufacturing enterprises. The results show, firstly, that human resource systems and systems have the same effect, but there were differences in the degree of impact. Secondly, job satisfaction has a statistically significant influence on financial performance. Lastly, all worker/employee attitude determinants are statistically significant for both job satisfaction and organizational commitment. HRM, previously relatively overlooked, provided theoretical and practical implications by demonstrating the direct impact on financial performance and the impact of individual human resource management systems and policies.

• Asia Pacific Journal of Business Review
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• v.6 no.2
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• pp.1-26
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• 2022

This study uses the human resource management (HRM) practice and ability, motivation, and opportunities (AMO) theory and corporate social and environmental responsibility, to explore the effects of environmental responsible human resource management practice (ER-HRM) on energy-intensive manufacturing's green technology innovation and organizational effectiveness. A self-completed questionnaire was administered to managers of energy-intensive manufacturing in the Lao PDR. The data was collected from 198 managers of energy-intensive manufacturing for analysis. We used structural equation modeling (SEM) by smart PLS 3.0 to test the hypotheses in this research. The findings have shown a strong direct and positive impact of the environmental ability, motivation, and opportunity of ER-HRM practice on green technology innovation and organizational effectiveness. The ability of ER-HRM practice has the highest influence on green technology innovation and organizational effectiveness. The findings also prove the partial mediation of green technology innovation links ER-HRM with organizational effectiveness. This research is expected to identify the influences of ER-HRM in energy-intensive manufacturing to achieve innovation and performance while reducing emissions.

• Industrial Engineering and Management Systems
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• v.6 no.1
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• pp.83-93
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• 2007

This paper gives an attempt to build a decision support tool linked with a simulation software called ARENA for evaluating and comparing the performance of the push and pull material driven strategies operating in the flow shop environment with a bottleneck resource as the shop's constraint. To be fair for such evaluation, the comparison must be made fairly under the optimal setting of both systems' operating parameters. In this study, an optimal-seeking heuristic algorithm, Genetic Algorithm (GA), is employed to suggest a systems' best design based on the economic consideration, which is the profit generated from the system. Results from the study have revealed interesting outcomes, letting us know the strength and weakness of the push and pull mechanisms as well as the effect of each operating parameter to the overall system's financial performance.

• Proceedings of the Korea Society for Simulation Conference
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• 1996.05a
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• pp.15-15
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• 1996

A shop floor control system (SFCS) is the central part of a CIM system used to control the activities of several pieces of manufacturing equipment (e.g., NC machines, robots, conveyors, AGVs, AS/RS). The SFCS receives orders and related process plans, and then performs selecting a specific process routing, allocating resources, scheduling the workpieces, downloading the processing instructions (e.g., RS-274 instructions for NC machines, VAL II programs for robot), monitoring the progress of activities, detecting and recovering from errors, and preparing reports on the status of the manufacturing system. Simulation has been utilized in discovering control policies used for resolving shop floor be control problems such as resource contentions, part dispatching, deadlock. The simulation model must be designed to respond to real-time data coming from a shop floor. However, to rapidly build a realtime simulation model of SFCS cannot be easily accomplished. This talk is to address an automatic program generator of discrete event simulation model for shop floor control from process plans and resource models. The program generator is capable of constructing complete discrete simulation models for multi-product and multi-stage flexible manufacturing systems.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1996.04a
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• pp.627-630
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• 1996

One of the most common communication mechanisms to describe a situation or a process is a story written as an ordered sequence of events or activities. For example, a shop floor supervisor may present the operations of his manufacturing system by describing the processes of manunfacturing a product in his shop. Although IDEF3 is one of the most commonly used methods for describing a business process, but it is not common for a manufacturing process. In this study, we tried to apply IDEF3 for describing a manufacturing process. Problems and suggestions such as selection probability, programmable process modeling, manufacturing resource model were presented.

• Korean Journal of Computational Design and Engineering
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• v.12 no.6
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• pp.452-460
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• 2007

To achieve rapid developments and cost savings in manufacturing industries including automotive die shops, new paradigm and its supporting systems of information managements through total product life cycle are needed for concurrent and collaborative engineering. For manufacturing of automotive press dies, integrated and efficient managements of PPR information including product, manufacturing process and resource are essential. In this paper, we introduce a PLM approach to achieve engineering collaborations in product development and production of automotive dies. To prove concepts and benefits of PPR information managements, we implement new business workflow and detail procedures, PPR information management system and other related applications. By PPR information managements in PLM, improvements in quality of engineering results and savings in time from design to production of dies are possible.

• Journal of the Korean Society for Precision Engineering
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• v.20 no.9
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• pp.27-31
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• 2003

• Industrial Engineering and Management Systems
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• v.7 no.1
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• pp.57-65
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• 2008

Available-to-promise (ATP) exhibiting availability of manufacturing resources can be used to support customer order promising. Recently, one advanced function called Capable-to-promise (CTP) is provided by several modern APS (advanced planning system) that checks available capacity for placing new production orders or increasing already scheduled production orders. At the customer enquiry stage while considering the order delivery date and quantity to quote, both ATP and CTP are allocated to support order promising. In particular, current trends of mass customization and multi-side production chain derive several new constraints that should be considered when ATP/CTP allocation planning for order promising - such as customer's preference plants or material vendors, material compatibility, etc. Moreover, ATP/CTP allocation planning would be executed over a rolling time horizon. To utilize capacity and material manufacturing resource flexibly and fulfill more customer orders, ATP/CTP rolling planning should possess resource reallocation mechanism under the constraints of order quantities and delivery dates for all previous order promising. Therefore, to enhance order promising with reliability and flexibility to reallocate manufacturing resource, the ATP/CTP reallocation planning mechanism is needed in order to reallocate material and capacity resource for fulfilling all previous promised and new customer orders beneficially with considering new derived material and capacity constraints.