Jaekoo Joo

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Recently, discrete part manufacturing systems have encountered more impending requests for adaptability and flexibility in order to efficiently survive the increasing dynamics of manufacturing environment. Although feature-based computer-aided process planning plays a vital role in automating and integrating design and manufacturing for efficient(More)
The objective of the paper is to develop a virtual reality-supported rapid configuration and analysis system of a particular product, Unit BathRoom (UBR). The system is divided into the two modules, product configuration module (PCM) and product analysis module (PAM). The PCM, programmed using virtual reality software, enables the customers to replace,(More)
Complex cognitive processes corresponding to human control behaviors cannot be easily inferred using (1) a logical rule-based model, (2) a statistical model, or (3) an analytical predictive model. Predicting human behaviors in complex and uncertain environments like emergency evacuation is considered almost impossible (at least NP hard) in systems theory.(More)
Although feature-based computer-aided process planning plays a vital role in automating and integrating design and manufacturing for ef®cient production, its off-line properties prohibit the shop ¯oor controllers from rapidly coping with unexpected production errors. The objective of the paper is to suggest a neural network-based dynamic planning model, by(More)
  • Jaekoo Joo
  • 2005
Determining such process parameters as rotational speed, feed rate, depth of cut, and width of cut is the critical function that affects not only machining productivity but also quality of a finished part. In the paper, a dynamic planning model is developed to determine efficient process parameters for roughly machining a pocket type of process feature in(More)
Although feature-based process planning plays a vital role in automating and integrating design and manufacturing for efficient production, its off-line properties prohibit the shop floor controller from rapidly coping with dynamic shop floor status such as unexpected production errors and rush orders. The objective of the paper is to address a neural(More)
We propose a predictive modeling framework for human-involved complex systems in which humans play controlling roles. Affordance theory provides definitions of human actions and their associated properties, and the affordance-based Finite State Automata (FSA) model is capable of mapping the nondeterministic human actions into computable components in(More)
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