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Original Articles

Network part program approach based on the STEP-NC data structure for the machining of multiple fixture pallets

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Pages 281-300 | Received 05 Jun 2012, Accepted 08 Jun 2013, Published online: 09 Jul 2013
 

Abstract

The adoption of alternative process plans, that is, process plans that include alternative ways of machining a workpiece, can improve system performance through a better management of resource availability. Unfortunately even if this opportunity is deeply analysed in literature, it is not frequently adopted in real manufacturing practice. In order to fill this gap, this article presents the network part program (NPP) approach for the machining of multiple fixture pallets. The NPP approach is based on the STEP-NC data structure which supports nonlinear sequences of operations and process flexibility. In the NPP approach, a machining system supervisor defines the machining sequences and generates the related part programs just before the execution of the pallet. This article provides an approach with high scientific value and industrial applicability based on the integration of new and existing process planning methods. A real industrial case study is considered in order to show that in real applications the final quality is unaffected by the change of the sequence of the operations due to the employment of nonlinear process plans. Since the results appear very encouraging, the proposed approach is a possible solution to accelerate the adoption of nonlinear process planning in real manufacturing practice.

Acknowledgements

The authors thank MCM S.p.A. and CETMA for their contribution in this work and FERRAIOLI S.p.A. for its support in the testing phase.

Notes

1.Geometric and dimensional tolerances were defined for these 22 characteristics. Tolerance values are confidential and cannot be reported in this article. However, as mentioned before, if the tolerance values are considered fixed, the independence of product quality from NPP can be proved by analysing only the expected value and the variance of the quality characteristics.

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