Abstract
Today, the dynamic market requires manufacturing firms to possess high degree of adaptability and flexibility to deal with shop-floor uncertainties. Specifically, targeting SMEs active in the machining and metal cutting sector who normally deal with complex and intensive process planning problems, researchers have tried to address the subject. Among proposed solutions, Web-DPP elaborates a two-layer distributed adaptive process planning system based on function-block technology. Function-block enabled machine controllers are one of the elements of this system. In addition, intensive reasoning based on the features data of the products models, machining knowledge, and resource data is needed to be performed inside the function blocks in machine controller side. This paper reports the current state of design and implementation of a knowledge-based operation planning module using a rule-engine embedded in machining feature function blocks, and also the design and implementation of a common interface (for CNC milling machine controller and its specific implementation for a specific commercial controller) embedded in the machining feature function blocks for controlling the machine. The developed prototype is validated through a case-study.
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Acknowledgments
The authors would like to thank Sandvik Coromant Co. for its valuable support to this research.
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© 2013 Springer International Publishing Switzerland
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Givehchi, M., Schmidth, B., Wang, L. (2013). Knowledge-Based Operation Planning and Machine Control by Function Blocks in Web-DPP. In: Azevedo, A. (eds) Advances in Sustainable and Competitive Manufacturing Systems. Lecture Notes in Mechanical Engineering. Springer, Heidelberg. https://doi.org/10.1007/978-3-319-00557-7_55
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DOI: https://doi.org/10.1007/978-3-319-00557-7_55
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