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A Heuristic STEP-NC Based Process Planning Tool for Sequencing NC Machining Operations

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Advanced Design and Manufacturing Based on STEP

Abstract

Nowadays, the process planning for sequencing NC (numerical control) machining operations is still done manually in principle. In the last decade several approaches for automatic process planning based on Artificial Intelligence (AI) and heuristic algorithms have been developed. Additionally, new technologies such as CAD/CAM (Computer Aided Design/Computer Aided Manufacturing) systems, feature-oriented specifications, and interfaces (e.g., STEP-NC) were introduced. Nevertheless, the process planner still has to modify and acknowledge the generated Workplans manually. In order to overcome this problem, an approach for enabling the automatic preparation of STEP-NC based Workplans with methods known from graph theory is introduced in this chapter. Therefore a STEP-NC Workplan is mapped into a directed graph in a mathematically defined way. Based on that, it is possible to use algorithms to find the shortest path and a Hamiltonian Path (HP) inside this directed graph as optimal sequenced solution under given requirements. Thus, the Workplan will be structured and reordered. Finally, the corresponding NC machining code will be generated and distributed to the machinery. Hence in this chapter, the requirements, the investigation, and the selection of suitable knowledge structuring and processing concepts, the mathematical fundamentals, and the work flow of sequencing a system are investigated. The focus of this chapter is the investigation of heuristic algorithms in order to sequence the STEP-NC machining operations. Finally, a preliminary demonstrator is introduced.

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Berger, U., Kretzschmann, R., Arnold, KP. (2009). A Heuristic STEP-NC Based Process Planning Tool for Sequencing NC Machining Operations. In: Xu, X., Nee, A. (eds) Advanced Design and Manufacturing Based on STEP. Springer Series in Advanced Manufacturing. Springer, London. https://doi.org/10.1007/978-1-84882-739-4_3

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  • DOI: https://doi.org/10.1007/978-1-84882-739-4_3

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