Abstract
This article presents an efficient Statistic Process Control system architecture for on-line monitoring of manufacturing process. Shenyang Institute of Automation Statistic Process Control system (SIASPC) detects relevant events in Real-time based on digital production model of MES. Failures occur in manufacturing process are diagnosed using control charts and FTA method based on expert knowledge base. The SIASPC has been developed and will be applied to control an Automobile gear-box assembly process.
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Peng, H., Shang, W., Shi, H., Peng, W. (2007). On-Line Monitoring and Diagnosis of Failures Using Control Charts and Fault Tree Analysis (FTA) Based on Digital Production Model. In: Zhang, Z., Siekmann, J. (eds) Knowledge Science, Engineering and Management. KSEM 2007. Lecture Notes in Computer Science(), vol 4798. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-76719-0_56
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DOI: https://doi.org/10.1007/978-3-540-76719-0_56
Publisher Name: Springer, Berlin, Heidelberg
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