• Journal of Institute of Control, Robotics and Systems
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• v.20 no.11
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• pp.1131-1135
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• 2014

This paper proposes the enhanced faulty node detection scheme with hybrid algorithm using Markov-chain model on BCH (Bose-Chaudhuri-Hocquenghem) code in naval distributed control networked systems. The probabilistic model-driven approach, on Markov-chain model, in this paper uses the faulty weighting interval factors, which are based on the BCH code. In this scheme, the master node examines each slave-nodes continuously using three defined states : Good, Warning, Bad-state. These states change using the probabilistic calculation method. This method can improve the performance of detecting the faulty state node more efficiently. Simulation results show that the proposed method can improve the accuracy in faulty node detection scheme for real-time naval distributed control networked systems.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.5
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• pp.20-28
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• 2014

This paper proposes a faulty node detection scheme that performs collective monitoring of a distributed networked control systems using interval weighting factor. The algorithm is designed to observe every node's behavior collectively based on the pseudo-random Bose-Chaudhuri-Hocquenghem (BCH) code. Each node sends a single BCH bit simultaneously as a replacement for the cyclic redundancy check (CRC) code. The fault judgement is performed by performing sequential check of observed detected error to guarantee detection accuracy. This scheme can be used for detecting and preventing serious damage caused by node failure. Simulation results show that the fault judgement based on decision pattern gives comprehensive summary of suspected faulty node.

• Korean Journal of Computational Design and Engineering
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• v.11 no.2
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• pp.148-155
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• 2006

This paper presents a new method for assessing the efficiency of production process plans using tolerance chart to lower production cost. The tolerance chart is used to predict the accuracy of a part that is to be produced following the process plan, and to carry out the quantitative measurement on the efficiency of the process plan. By comparing the values of design tolerances and their corresponding resultant tolerances calculated using the tolerance chart, the process plan that is incapable of satisfying the design requirements and the faulty production operations can be identified. Similarly, the process plan that imposes unnecessarily high accuracy and wasteful production operations can also be identified. For the latter, a quantitative measure on the efficiency of the process plan is introduced. The higher the unnecessary cost of the production, the poor is the efficiency of the process plan. A coefficient is introduced for measuring the process plan efficiency. The coefficient also incorporates two weighting factors to reflect the difficulty of manufacturing operations and number of dimensional tolerances involved. To facilitate the identification of the machining operations and the machined surfaces, which are related to the unnecessarily tight resultant tolerances caused by the process plan, a rooted tree representation of the tolerance chart is introduced, and its use is demonstrated. An example is presented to illustrate the new method. This research introduces a new quantitative process plan evaluation method that may lead to the optimization of process plans.