Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

Parallel Simplex: An Alternative to Classical Experimentation: Case Study

Version 1 : Received: 17 September 2024 / Approved: 18 September 2024 / Online: 19 September 2024 (08:52:23 CEST)

How to cite: Zorrilla Briones, F.; Meléndez Pastrana, I. Y.; Rodríguez-Morachis, M. A.; Anaya Carrasco, J. L. Parallel Simplex: An Alternative to Classical Experimentation: Case Study. Preprints 2024, 2024091367. https://doi.org/10.20944/preprints202409.1367.v1 Zorrilla Briones, F.; Meléndez Pastrana, I. Y.; Rodríguez-Morachis, M. A.; Anaya Carrasco, J. L. Parallel Simplex: An Alternative to Classical Experimentation: Case Study. Preprints 2024, 2024091367. https://doi.org/10.20944/preprints202409.1367.v1

Abstract

Experimentation is a strong methodology that improves and optimizes processes, never the less, in many cases, real life dynamics of production demands and other restrictions inhibit the use of these methodologies because their use implies stopping production, generate scrap, jeopardize demands accomplishment and other problems. Here is proposed and alternative methodology to search for the best process variables levels and optimize the response of the process without the need to stop production. This algorithm is based on the principles of the Variable Simplex developed by Nelder and Mead and the continuous iterative process of EVOPS developed by Box and then modified as a simplex by Spendley. It is named parallel simplex because it searches for the best response with three independent Simplexes, searching the same response at the same time. The algorithm was designed for three simplexes of two input variables each. The case study documented shows that it is efficient and effective.

Keywords

optimization; design of experiments; variable simplex; evolutive operations; canonical analysis; RSM

Subject

Engineering, Industrial and Manufacturing Engineering

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