A methodology for the estimation of build time for operation sequencing in process planning for a hybrid process

Zicheng Zhu, Vimal G. Dhokia*, Aydin Nassehi, Stephen T. Newman

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingChapter in a book

1 Citation (Scopus)

Abstract

The on-going industrial trend toward production of highly complex and accurate part geometries with reduced costs has led to the emergence of hybrid manufacturing processes where varied manufacturing operations are carried out in either parallel or serial manner. One such hybrid process being currently developed is the iAtractive process, which combines additive, subtractive, and inspection processes. The enabler for realizing the hybrid process production is the process planning algorithm. The production time estimation for the additive process, namely build time, is one of the key drivers for the major elements in the algorithm. This paper describes a method for predicting build times for operation sequencing for process planning of the iAtractive process. An analytical model is first proposed, theoretically analyzing the factors that affect build times, which is used to help with the design of four test parts together with 64 sets of variations. The experimental results indicate that part volume, and interactions of volume and porosity, height and intermittent factor have significant effect on build times. Finally, the build time estimation model has been developed, which were subsequently evaluated and validated by applying a wide range of the identified influential factors.

Original languageEnglish
Title of host publicationAdvances in Sustainable and Competitive Manufacturing Systems
Subtitle of host publication23rd International Conference on Flexible Automation & Intelligent Manufacturing
PublisherSpringer Berlin Heidelberg
Pages159-171
Number of pages13
Volume7
DOIs
Publication statusPublished - 2013

Publication series

NameLecture Notes in Mechanical Engineering
Volume7
ISSN (Print)21954356
ISSN (Electronic)21954364

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