• Journal of Institute of Control, Robotics and Systems
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• v.12 no.6
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• pp.600-607
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• 2006

For the effective operation of manufacturing system, FMS(Flexible Manufacturing System) and CIM(Computer Integrated Manufacturing) system are developed. In these systems, a machine tool is the target of integration in last 3 decades. In nowadays, the conventional concept of machine tools is changing to the autonomous manufacturing device based on knowledge-evolution through applying advanced information technology in which open architecture controller, high speed network and internet technology are contained. In this environment, a machine tool is not the target of integration but the subject of cooperation. In the future, a machine tool will be more improved in the form of a knowledge-evolution based device. In order to develop the knowledge-evolution based machine tools, this paper proposes the structure of knowledge evolution in M2M(Machine To Machine) and the scheme of a dialogue agent among agent-based modules such as a sensory module, a dialogue module, and an expert system. The dialogue agent has a role of interfacing with another machine for cooperation. To design the dialogue agent module in M2M environment, FIPA-OS and ping agent based on FIPA-OS are analyzed in this study. Through this, it is expected that the dialogue agent module can be more efficiently designed and the knowledge-evolution based machine tools can be hereafter more easily implemented.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2006.05a
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• pp.633-634
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• 2006

Recently we started a development of the digital meister expert system for the product design supporting in manufacturing industry. Knowledge representation is of major importance in digital moister expert system. This rule-based expert system-knowledges are designed for a certain type of knowledge representation such as rules or logic. The way in which a rule-based expert system represents knowledge affects the development, efficiency, speed, and maintenance. Eventually, this digital moister system is used to the engineer in manufacturing industry for the process control, production management and system management. In this paper, we propose the digital moister system knowledge representation method for product design supporting in manufacturing industry and we present introduction and contents of rule-based knowledge representation supporting tool.

• Journal of Advanced Marine Engineering and Technology
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• v.23 no.5
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• pp.622-629
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• 1999

This paper presents the development of an interactive knowledge-based CAM system for design-ing and manufacturing the mold. The system is composed of two functional parts. One is the geo-metric modeller that uses the feature-based models. The models include base plate step, hole, pocket, boss and slot, These are designed by interactive user interface. The other is the expert sys-tem module with inference engine and knowledge database of workpiece material tools manufac-turing machines process an working conditions. With two parts the final mold shape is generated with manufacturing information for effective production.

• Knowledge Management Research
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• v.7 no.2
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• pp.53-68
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• 2006

Knowledge has become an important resource for organization. The manufacturing industry is usually operated on the basis of business processes, and most workers are familiar with their own processes. The process-based approach, therefore, can provide an efficient way to capture and navigate knowledge. In this study, we focus on knowledge which may be missed during knowledge transfer among workers. For this, we propose a method for analyzing knowledge flow, which is passed among business processes. We propose a process-based knowledge management framework for analyzing knowledge flow, which employs a two-phase analysis: process analysis and knowledge flow analysis. A knowledge flow model, represented by Knowledge Flow Diagram, is proposed as a tool for representing knowledge. We formulate several semantics for knowledge flow modeling. We build the three-level schema: conceptual, logical, and physical in order to automate the knowledge model adaptive to knowledge management systems. The proposed approach is verified and illustrated through a case study on the manufacturing process of A Company.

• IE interfaces
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• v.25 no.1
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• pp.40-51
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• 2012

Today, many manufacturing companies realize that collaboration is crucial for their survival. Especially, in the perspective of quality, the importance of collaboration is emphasized because economic loss increases exponentially while defective parts go through the process in supply chain. However, the manufacturing companies are facing two main difficulties in implementing collaborative relationships with their suppliers. First, it is difficult for the suppliers to produce reliable products due to their obsolete facilities. The problem gets worse for second- or third-tire vendors. Second, the companies experience the lack of universally understandable set of terminology and effective methodologies for knowledge representation. Ontology is one of the best approaches to expressing and processing a domain knowledge. In this paper, we propose the manufacturing ontology-based quality prediction framework to represent and share the knowledge of industrial environment and to predict product quality in manufacturing processes. In addition, we develop the ontology-based quality prediction system based on the proposed framework. We carried out a series of experiments for an injection molding process at an automotive part supplier. The experimental results demonstrated that the proposed framework and system can be successfully applicable in manufacturing industry.

• 제어로봇시스템학회:학술대회논문집
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• 1990.10a
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• pp.514-518
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• 1990

This paper describes an experimental Knowledge-Based Control System, named KBCS, for manufacturing and assembly. The KBCS of five parts and function : data-base, knowledge acquisition, optimization, and graphic monitoring. The KBCS is utilized for a FMS which is of five machine centers and automatic assembly lines. Each machine can perform almost all manufacturing functions which some difference in efficiency. Buffers store temporarily the incoming components and the outing components. Parts arrive at assembly lines after many steps of manufacturing, and the transfer path and time are determined by procedural knowledge of control systems. Nine different incoming components are set up. The total control system is expected to perform four algorithms, timing algorithm ,sequencing algorithm, penalty algorithm, and cart algorithm. The construction of controller require basic components of manufacturing systems in which knowledges are formulated on the base of the results and the repeated simulation of KBCS with graphic monitoring system. Simulation results by KBCS are compared with those by the other rules of manufacturing.

• Journal of Technology Innovation
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• v.6 no.1
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• pp.71-98
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• 1998

This paper analyzes the characteristics of technological knowledge flow-structure of Korean manufacturing in dynamic perspective. In doing that, the concept of the knowledge network is introduced which is defined as a set of industries and their interaction(knowledge flow) or linkage. The analysis of the inter-industrial knowledge flows is based on the technological similarity by using R&D researchers' academic background in the year of 1984, 1987, 1990. The analysis is carried out by such methodology as network analysis, indicator analysis and simple statistical analysis. And the final results are drawn both in absolute terms(dimension effect) and in relative terms(proportion effect) respectively. The main findings are as follow. First, the Korean manufacturing knowledge network appears to strengthen existing inter-industrial knowledge linkages rather than to construct new linkages. Second, the network seems to form a dualistic structure in that some high-technology sectors(knowledge production sectors) emerge along with traditional sectors(knowledge absorbing sectors). Third, since the mid-1980s, an inter-industrial fusion is witnessed among technologically intensive sectors, indicating that some sophisticated innovation modes are emerging in Korean manufacturing system. And fourth, by using the relations of the inter-industrial knowledge-flows, we classified manufacturing industries into 3 type ; knowledge-outflow sector, knowledge-inflow sector and knowledge intermediary sector.

• Design & Manufacturing
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• v.9 no.2
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• pp.6-9
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• 2015

The objective of manufacturing knowledge sharing platform is to convert the production experience like a worker's know-how into quantitative values, to construct database of the process technologies and to share the technologies systematically via web portal service. In addition, the knowledge sharing platform contains the total production processes of automobile and mobile products such as information of experts, facilities, and cutting-edge R&D outputs. Automobile, telecommunication mobile, and semiconductors account for a large amount of Korea's export industry rate. These industries need production technology which is a result of converting worker's know-how and R&D. Manufacturing knowledge portal aims to enable transforming production experience such as worker's know-how into standardized form for constructing database and sharing technologies systematically. Manufacturing knowledge portal can contribute to small and mid-sized manufacturing companies with further improvements.

• Journal of the Korean Society for Precision Engineering
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• v.7 no.3
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• pp.66-74
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• 1990

This paper presents a knowledge-based computer aided process planning system that automatically selects machine tools, machining operations and cutting tools and determines sequences of the machining operations for prismatic parts in die manufacturing. In the proposed system, parts are described by manufacturing features and grouped into part families based on the functions. Each part is repressented by a part frame which consists of basic data and manufacturing features. Knowledge for manufacturing is acquired from the domain expert and represented by frames. A decision model for selection of machine tools, machining operations and cutting tools and for determining sequences of the machining operations are developed by employing the Mealy machine in finite automata with output. The decision procedure and the order of priority which inputs manufacturing features into the Mealy machine are represented by rule for each part family. Backward chaining is used for the proposed system. The proposed system is implemented by using TURBO-PROLOG on the IBM PC/AT. A case study for the slide core is presented to show the function of the proposed system.

• STI Policy Review
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• v.6 no.2
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• pp.146-173
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• 2015

This study explores how to reconcile science and policy in the wind energy sector by providing a conceptual framework for better understanding evidence-based policymaking (EBPM). Regarding this framework, the core issue is to discover how knowledge is formed over time, and which factors affect this knowledge formation. Comparative cases of wind industry emergence in Spain and Britain are examined. This analysis shows that knowledge formation initially starts in the scientific arena in parallel with its formation in the practical, and is followed by political knowledge formation near the beginning of commercial projects. Regarding knowledge formation, three more comparisons are made between wind industry emergence in Spain and Britain: the different approaches to R&D projects, the different adoptions of supporting measures, and the different ways of coping with public opposition. The factors affecting the comparisons are mainly perceptions of energy supply, nuclear power, environment and science and technology. Communication and unfamiliarity are likely to affect the comparisons in EBPM.