• 산업경영시스템학회지
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• 제18권36호
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• pp.233-241
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• 1995

Many companies worldwide today are pursuing to make diversified and highly qualified products. Factory automation aims at maximizing profits through the lessened inventory and shortened delivery time, which will enable the company to become more responsive to market changes. This research analyzes the following feartures in the process of factory automation. first, the automation level according to the company class. second, productivity according to the automation level. third, the organization menber's interest in the automation. finally, the possible problems in factory automation.

• 산업공학
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• 제10권1호
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• pp.209-222
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• 1997

The paper provides a methodology to obtain the automaticity indicator of a factory and the sequence of enabling technologies of factory automation. The automaticity indicator is the measure of the current automation status of a factory and can be used as a crucial criteria for the future automation schedule and investment. Although most industries have their own computation methods which usually consider the number of workers in the shop floor, this research covers five evaluation items of automation, such as, production facility, material transfer system, inspection and test system, information system, and flexibility. The detailed evaluation models are developed for each item. Automation sequencing prioritizes the enabling technologies of factory automation on the basis of several criteria which consist of two phases. The first phase includes the automation indicator and the second phase includes six sub-criteria such as production rate, quality, number of workers, capital investment, development duration, development difficulty. For this evaluation, AHP(Analytical Hierarchy Process) is introduced to prevent the decision maker's subject intention. As results of the automaticity indicator and automation sequence, the manager can save time and cost in building constructive and transparent automation plans.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1986년도 한국자동제어학술회의논문집; 한국과학기술대학, 충남; 17-18 Oct. 1986
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• pp.181-183
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• 1986

This paper describes the concept of ADS (Autonomous Decentralized System) and its application to FA (Factory Automation). The schemes of ADFAS (Autonomous Decentralized Factory Automation System) utilizing these concepts are presented.

• 한국산학기술학회논문지
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• 제1권1호
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• pp.55-62
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• 2000

기업의 공장자동화는 가장 중요한 경쟁력 화보 수단이 되고 있으며 생산자동화에서 품질은 소프트웨어의 기술적 품질에 지대한 영향을 받게 되었다. 따라서, 공장자동화 시스템의 품질 향상을 위해 자동화 소프트웨어에 대한 품질평가의 필요성이 대두되었다. 본 연구에서는 공장자동화용 소프트웨어에 대한 품질평가 체계와 평가 프로세스를 확립하고 평가 과정에서 활용되는 메트릭을 개발하였다. 또한, 이를 바탕으로 품질평가 자동화 도구를 설계·구현함으로써 공장자동화 산업의 핵심이 되고 있는 자동화 소프트웨어의 품질 향상을 지원할 수 있도록 하였다.

• Journal of Information Technology Applications and Management
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• 제26권2호
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• pp.13-26
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• 2019

The purpose of this study is to examine the effect of each of the two technology acceptance factors(employees' attitude toward smart factory technology, and ease of smart factory technology use) on the introduction level of each of the three smart factory technologies (manufacturing big data technology, automation technology, and supply chain integration technology), and in turn, the effect of each of the three smart factory technologies on manufacturing performance. This study employed PLS statistics software package to empirically validate a structural equation model with survey data from 100 domestic small-and medium-sized manufacturing firms (SMMFs). The analysis results revealed the followings. First, it is founded that employees' attitude toward smart factory technology influenced all of the three smart factory technology introduction levels in a positive manner. In particular, SMMFs of which employees had more favorable attitude toward smart factory technology tended to increase introduction levels of both automation technology and supply chain integration technology more than in the case of manufacturing big data technology. Second, ease of smart factory technology use also had a positive impact on each of the three smart factory technology introduction levels, respectively. A noteworthy finding is this : SMMFs which perceived smart factory technology as easier to use would like to elevate the introduction level of manufacturing big data technology more than in the cases of either automation technology or supply chain integration technology. Third, smart factory technologies such as automation technology and supply chain integration technology had affirmative impacts on manufacturing performance of SMMFs. These results shed some valuable insights on the introduction of smart factory technology : The success of smart factory heavily depends on organization-and people-related factors such as employees' attitude toward smart factory technology and employees' perceived ease of smart factory technology use.

• 한국경영과학회:학술대회논문집
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• 대한산업공학회/한국경영과학회 1995년도 춘계공동학술대회논문집; 전남대학교; 28-29 Apr. 1995
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• pp.510-510
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• 1995

• 한국경영과학회:학술대회논문집
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• 대한산업공학회/한국경영과학회 1995년도 춘계공동학술대회논문집; 전남대학교; 28-29 Apr. 1995
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• pp.511-511
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• 1995

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1987년도 한국자동제어학술회의논문집; 한국과학기술대학, 충남; 16-17 Oct. 1987
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• pp.376-381
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• 1987

There are many kinds of intelligent devices on the factory floor nowadays. Standardized communication methods became a necessity for efficient flow of production information among various systems. MAP (Manufacturing Automation Protocol) based on ISO (International Standard Organization) OSI (Open Systems Interconnection) is gaining acceptance of major industries worldwide.

• 한국안전학회지
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• 제37권5호
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• pp.22-32
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• 2022

The domestic smart factory is being built and spread rapidly, mainly by mid-sized companies and large enterprises according to the government's active introduction and support policy. But these factories only promote production system and efficiency, so harmfulness and risk factors are not considered. Therefore, to derive harmful risk factors in terms of industrial safety for 12,983 government-supported smart factory workplaces from 2014 to 2019, industrial accident status analysis compared workplaces with automation facilities and government-supported workplaces with automation facilities. Also, to reduce risks associated with domestic smart factory processes, twenty government-supported workplaces with automation facilities underwent analysis, evaluating risks through a status survey using the process evaluation table. In addition, the status survey considered region, size, industry, construction level, and accident rate; the difference in risk according to the structure of the process was confirmed. Based on the smart factory process evaluation results, statistical analysis confirmed that serial, parallel, and hybrid structures pose different risk levels and that the risks of mixed structures are greater. Finally, safety control system application was presented for risk assessment and reduction in the smart factory process, reflecting the results of disaster analysis and actual condition investigation.

• KNOM Review
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• 제23권1호
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• pp.18-25
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• 2020

최근 스마트 팩토리(Smart Factory)에 대한 연구는 단순히 공장 자동화(Factory Automation, FA)의 개념에서 데이터를 수집하고 분석하는 형태로 발전하고 있다. 이것은 통신 기술의 발전(5G)과 IoT 장치(device)들이 현장 상황에 맞춰 다양하게 개발되면서 가속화 되고 있다. 또한, 기업 경쟁력 강화로 디지털트랜스포메이션(Digital Transformation)이 활발히 이루어지고 있으며, 이를 각종 IoT 장비로 부터 수신한 데이터와 자동화된 설비를 결합시켜 공정 재조정을 통한 최적화 연구가 다양하게 진행되고 있다. 따라서 본 논문에서는 관련 연구 중 하나인 예측 시스템을 활용한 설비 장애 진단 및 조치 시스템 구조 및 요소를 제안한다.