Design of Combined Ahp-Topsis Model for Optimizing Selection of Injection Molding Machines

Abstract

In injection molding manufacturing, selection of the optimal machine from various alternatives is a crucial strategy for enhancing productivity, cost-effectiveness, and maintaining performance standards. This article presents an approach that combines two techniques to make the best choice from three presented options. Firstly, it employs the Analytic Hierarchy Process method to determine the weights of five main criteria and eleven sub-criteria, considering both cost and performance. Secondly, it utilizes the Technique for Order Preference by Similarity to Ideal Solution to rank the three machines by comparing each machine's performance against ideal and anti-ideal solutions to determine their relative suitability. The final model is validated through three distinct scenarios, illustrating how key criteria such as cost breakdown and scrap rate can influence the ultimate selection ranking. Through a presented numerical example, the paper provides decision-makers with a scientifically robust decision support system, aiding in strategic and complex decision-making processes for selecting the most suitable machine.