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Product and process optimization -case with ANOVA used for root causes of dimensional and geometric
Technical Paper
2007-01-2946
ISSN: 0148-7191, e-ISSN: 2688-3627
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English
Abstract
The objective of this article is to show procedure of dimensional problems resolution by correlation of products measurement results the use of a mathematical model for variance analysis demonstrated in a case.
The base of this work is in the dimensional problem evaluation in the subdivision of components, potentials of improvement, shunting line X variation, mathematical definition, adjustments of product and the process.
The optimization of products and processes is determined by the sequence of activities for problems solution, aligned to the product and process concept development with the possibility to get all the necessary information for continuous improvement.
The product and process activities and optimization standards are determined by the chance to solve problems and being actively directed toward the continuous improvement.
They subdivide themselves by the presented activities, potential of improvement, deviation X variation, mathematical definition, product and process adjustments and process revalidation.
The potential improvements are in the parts, tools, fixtures and in the process, established by the information of measurements in data bases.
Authors
Citation
Peres, E. and de Souza, G., "Product and process optimization -case with ANOVA used for root causes of dimensional and geometric," SAE Technical Paper 2007-01-2946, 2007, https://doi.org/10.4271/2007-01-2946.Also In
References
- AUTO/STEEL PARTNERSHIP AND BODY SYSTEMS ANALYSIS PROJECT TEAM Event-Based Functional Build: An Integrated Approach to Body Development Build 1999 www.a-sp.org July 2006
- GENERAL MOTORS CORPORATION GM-GMS (Global Manufacturing System) Operating Tool 15.13 Body-in-White and Assemblies Dimensional Body Shop Process Control August 2000
- CHRYSLER CORPORATION FORD MOTOR COMPANY GENERAL MOTORS CORPORATION September 1999