A Quantitative Tool for Analyze Process Design
Some quality control tools use non metric subjective information coming from experts, who qualify the intensity of relations existing inside processes, but without quantifying them. In this paper we have developed a quality control analytic tool, measuring the impact or strength of the relationship between process operations and product characteristics. The tool includes two models: a qualitative model, allowing relationships description and analysis; and a formal quantitative model, by means of which relationship quantification is achieved. In the first one, concepts from the Graphs Theory were applied to identify those process elements which can be sources of variation, that is, those quality characteristics or operations that have some sort of prelacy over the others and that should become control items. Also the most dependent elements can be identified, that is those elements receiving the effects of elements identified as variation sources. If controls are focused in those dependent elements, efficiency of control is compromised by the fact that we are controlling effects, not causes. The second model applied adapts the multivariate statistical technique of Covariance Structural Analysis. This approach allowed us to quantify the relationships. The computer package LISREL was used to obtain statistics and to validate the model.
Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1071182Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1324
 Ford Motor Company, T&C Division. "Dimensional Control Plans. DCP Manual". 1985.
 Carri├│n, A; Jabaloyes, J.; Lopez, A. The characteristics matrix as a tool for analysing process structure. International Journal of Production Research. Vol. 45, num. 42. 2007
 Munro, J. E. "Discrete Mathematics for computing". Chapman & Hall Australia. 1992.
 Maurer,S.B.; Raltson,A."Discrete algorithmic mathematics".Addison- Wesley Publishing Co.1991.
 Tremblay, J.P.; Manohar, R. "Matem├íticas discretas". CECSA, México.1996.
 Everitt, B. "An introduction to latent variable models". Chapman and Hall Ltd. Great Britain. 1984.
 Long, J. S. "Covariance Structure Models. An introduccion to LISREL". Sage publications. Beverly Hills, California. 1983.
 Long, J. S. "Confirmatory Factor Analysis. A preface to LISREL". Sage publications. Beverly Hills, California. 1983.
 Hair, J.F.; Anderson, R. E.; Tatham, R. L.; Black, W. C. "Multivariate data analysis with readings". Fourth edition. Prentice Hall. USA.1995.
 Jöreskog, K.; Sörbom, D. "LISREL 8: User's References Guide". Scientific Software International SSI, U.S.A. 1996.