Method for automating digital fixture-setups that are optimal for machining castings to minimize scrap

Autor: Satchit Ramnath, Nathan Kalish, Jami J. Shah, Joseph K. Davidson, Payam Haghighi, Jiten V. Shah
Rok vydání: 2016
Předmět:
Zdroj: Journal of Manufacturing Systems. 40:15-24
ISSN: 0278-6125
DOI: 10.1016/j.jmsy.2016.05.004
Popis: The motivation for this paper is to describe a method for lowering the cost of finishing large castings that have machined surfaces for attaching other components. Considerable time is required to set-up each cast part on a machine-tool, sometimes taking longer than the machining itself, and errors in set-up can result in scrapping expensive parts or attempts to salvage them by rework. Although the focus of the paper is to demonstrate a new technology and software for set-up prior to the machining of iron/aluminum/steel sand castings, the same technology also is applicable to large welded assemblies on which finished machining occurs. In this paper, we outline a method, currently being implemented, that can predictively, and off-line, identify the adjustments needed to position and orient each part in its fixture before machining operations begin so that, after machining, all finished features will lie in their tolerance zones. Computer models first simulate all the to-be-machined (TBM) surfaces and any contact points with the fixture by feature-fitting point clouds taken from selective scanning of the raw casting. The locations of these features are compared with their locations on the CAD model of the part. Then, by using the T-Map model for tolerances, all possible locations of the part in its machining fixture are identified so that all TBM faces lie in their tolerance-zones. An optimum location may then be chosen.
Databáze: OpenAIRE
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