Parallel Simplex, an Alternative to Classical Experimentation: A Case Study

Experimentation is a strong methodology that improves and optimizes processes. Nevertheless, in many cases, real-life dynamics of production demands and other restrictions inhibit the use of these methodologies because their use implies stopping production, generating scrap, jeopardizing demand accomplishments, and other problems. Proposed here is an alternative methodology to search for the best process variable 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, which is then modified as a simplex by Spendley. It is named parallel simplex because it searches for the best response with three independent Simplexes searching for 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.