EconPapers    
Economics at your fingertips  
 

A CAPP framework with optimized process parameters for rotational components

R. Siva Sankar, P. Asokan, G. Prabhaharan and A. V. Phani

International Journal of Production Research, 2008, vol. 46, issue 20, 5561-5587

Abstract: Process planning, as a critical stage integrating the design and manufacturing phase in a manufacturing environment, has been automated to meet the needs for higher productivity and lower production cost. Being an input to various systems such as scheduling and routing, process planning results are of great importance in the manufacturing stage. Though feature extraction and sequence optimization have been given much attention, the process parameters are rarely dealt with. This paper focuses on the development of a new generative computer aided process planning (CAPP) framework for rotational components. The developed framework includes modules for feature extraction based on CAD application programming interfaces, determination of the optimum sequence and generation of optimum process parameters. The optimization of the machining operations is achieved using the evolutionary technique. The approach resulted in the reduction and prediction of machining time and cost. The framework is demonstrated with a case study.

Date: 2008
References: Add references at CitEc
Citations:

Downloads: (external link)
http://hdl.handle.net/10.1080/00207540701288108 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:taf:tprsxx:v:46:y:2008:i:20:p:5561-5587

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/TPRS20

DOI: 10.1080/00207540701288108

Access Statistics for this article

International Journal of Production Research is currently edited by Professor A. Dolgui

More articles in International Journal of Production Research from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().

 
Page updated 2025-03-20
Handle: RePEc:taf:tprsxx:v:46:y:2008:i:20:p:5561-5587