• Journal of Korean Society of Industrial and Systems Engineering
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• v.43 no.2
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• pp.110-119
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• 2020

In order to provide priorities of the factors affecting the introduction of Smart Factory, This study reconstructed the factors and calculated the priorities through AHP (Analytic Hierarchy Process). The first layer of the hierarchy have 4 factors; productivity increase, brand image improve, marketing improve, cost reduction. The second layer of the hierarchy have 3 factors belong to the first layer, so the total number of second layer is 12. We divided the characteristics of enterprises into type of manager and age. The C.R. (consistency ratio) values of the respondents were found to be less than 0.1 and were judged to be a 'reasonable test'. As a result, the weights of the higher layer and the lower layer were obtained respectively, and then the weights of the higher layer and the weights of the lower layer were multiplied to obtain the total weights. Unlike previous studies that only surveyed factors that companies consider when introducing smart factory, (1) weighing and prioritizing factors were achieved. There are differences in priorities, (2) smart factory can be studied with the type of manager and firm age. When establishing policies, it is a practical implication (3) to assess its strategy not only for government officials but also for executives.

• Proceedings of the Safety Management and Science Conference
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• 2001.05a
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• pp.293-299
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• 2001

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1999.04a
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• pp.219-220
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• 1999

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.10a
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• pp.69-71
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• 2018

Looking at Korea's manufacturing industry, there are many old manufacturing plants. In fact, the manufacturing process of the product inventory management and the unit price of the product are all created by using Excel, and the factory is operated by using it. Also, the operator can not predict the failure of the equipment in order to produce the product at work. Problems related to this may result in the loss of the documents during the instruction and work process between the manager and the worker, and the communication between the manager and the worker can not be properly performed, There is appear a situation in which the operation is continued by using the equipment without recognizing in the failure. In this paper, we propose a method for upgrading the aging manufacturing plant to improve the productivity and productivity of the product by predicting the efficient inventory management, unit price management, production volume, and the operator's failure prediction.

• Industrial Engineering and Management Systems
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• v.2 no.1
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• pp.9-27
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• 2003

In a wafer fabrication factory, the completion time of an order is affected by many factors related to the specifics of the order and the status of the system, so is difficult to predict precisely. The level of influence of each factor on the order completion time may also depend on the production system characteristics, such as the rules for releasing and dispatching. This paper presents a method to identify those factors that significantly impact upon the order completion time under various combinations of scheduling rules. Computer simulations and statistical analyses were used to develop effective due date assignment models for improving the due date related performances. The first step of this research was to select the releasing and dispatching rules from those that were cited so frequently in related wafer fabrication factory researches. Simulation and statistical analyses were combined to identify the critical factors for predicting order completion time under various combinations of scheduling rules. In each combination of scheduling rules, two efficient due date assignment models were established by using the regression method for accurately predicting the order due date. Two due date assignment models, called the significant factor prediction model (SFM) and the key factor prediction model (KFM), are proposed to empirically compare the due date assignment rules widely used in practice. The simulation results indicate that SFM and KFM are superior to the other due date assignment rules. The releasing rule, dispatching rule and due date assignment rule have significant impacts on the due date related performances, with larger improvements coming from due date assignment and dispatching rules than from releasing rules.

• Information Systems Review
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• v.19 no.2
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• pp.95-113
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• 2017

The advent of information communication technology or the Fourth Industrial Revolution facilitated the fusion of equipment and management systems, such as Manufacturing Execution System, Enterprise Resource Planning, and Product Lifecycle Management, in the successful implementation of smart factories. The government supports the early adoption of these systems in small and medium companies to enhance their global competitiveness in producing products that can be recognized in a dramatically changing manufacturing environment. This study introduces smart factories to improve company competitiveness and address influences from the government assistance, CEO leadership, external consultancy, and organizational participation. We analyzed 101 results received from the questionnaires circulated to small- and medium-sized manufacturing companies. Given a successful smart factory implementation, company competitiveness is the factor that mostly influences organizational participation, government assistance, external consultancy, and CEO leadership. This study suggests several perspectives to implement a smart factory, which is the most important aspect of company competitiveness.

• Journal of the Korea Safety Management & Science
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• v.10 no.3
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• pp.43-53
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• 2008

This study is carried out for the fire safety of the factory building, the fire risk reduction measure in compliance with an example approached in fire risk reduction systematically, contribute to reduce the fire risk. The analytical fire risk process of discovering, identifying, estimating and evaluating risk and control measure as risk reduction measures are core concept, applies loss prevention with loss control techniques. The painting process in the workplace where the fire hazard and death accident accompanies coexists. Loss prevention problem of creation prevention of dangerous atmosphere at workplace is health and human services problem of normal circumstances, must be inspected with problem of combustible gases at the time of fire explosion. Static electricity measure accomplished the risk control process thoroughly as the fire risk reduction process model with the ignition sources measure which is presented. Fire risk from within organizing will be able to classify with each field by detailedly but risk treatment process will be able to apply basically all the same concept. Consequently about risk management example from before, this study is proposed risk management techniques that standardized rightly in the actual condition of organization with one plan, with discovery of fire risk, the feedback process in compliance with a fire risk reduction and the review which control the result is joint responsibility of engineer, technical expert and manager as part of safety management to practice with the fact must be supervised.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.12 no.5
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• pp.29-37
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• 2017

In this study, real-time monitoring is carried out in the factory site for product quality control such as improvement of productivity through facility automation, improvement of product quality, improvement of factory environment, check of facility maintenance status and check of product defect, And to establish a smart factory for the purpose of protecting the personal environment of the worker. The company is an auto parts company located in the province. The main research content is development of automation and monitoring system of oil filter clipping necessary for smart factory. Smart factory oil filter clipping automation is divided into electric air parts, solenoid valve and other parts processing process. Smart factory quality inspection monitoring system is implemented by server PC and S / W, client software, Operator PC, operating program, and input terminal application. This research data is expected to be very useful data for the auto parts venture companies that are promoting smart factories.

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 2000.11c
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• pp.764-769
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• 2000

A new transplant production system that produces high quality plug seedlings of specific crop has been studied. It is a plant factory designed to produce massive amount of virus free seedlings. The design concept for building this plant factory is to realize maximum energy efficiency and minimum initial investment and running cost. The basic production strategy is the sitespecific management. In this case, the management of the growth of individual plantlet is considered. This requires highly automated and information intensive production system in a closed aseptic environment the sterilized specific crops. One of the key components of this sophisticated system is the irrigation system. The conditions that this irrigation system has to satisfy are: 1. to perform the site specific crop management in irrigation and 2. to meet the no waste standard. The objective of this study is to develop an irrigation scheduling that can implement the no waste standard.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1991.10a
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• pp.51-65
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• 1991

This paper describes computer-integrated manufacturing (CIM) systems as strategic information systems for business which play an important role in accelerating the speed of business, and develops a measure showing a degree of business tendency to be CIM which enables the business to check on its present status as far as CIM is concerned. It is well known that the productivity of knowledge workers is lower than that of other workers. Nowadays, a great deal of effort goes into the productivity improvement of knowledge workers. In this respect, this paper also develops a quantitative model for the productivity of knowledge workers. Finally, this paper deals with following four steps which our small business should follow through its process of CIM: [Step 1] Using expert knowledge; [Step 2] Invention of technological information; [Step 3] Feedback of factory information to the management; and, [Step 4] Accelerating the speed of business.