Design of a decision support system for machine tool selection based on machine characteristics and performance tests

Economic globalization, together with heightened market competition and increasingly short product life cycles are motivating companies to use advanced manufacturing technologies. Use of high speed machining is increasingly widespread; however, as the technology is relatively new, it lacks a deep-rooted knowledge base which would facilitate implementation. One of the most frequent problems facing companies wishing to adopt this technology is selecting the most appropriate machine tool for the product in question and own enterprise characteristics. This paper presents a decision support system for high speed milling machine tool selection based on machine characteristics and performance tests. Profile machining tests are designed and conducted in participating machining centers. The decision support system is based on product dimension accuracy, process parameters such as feed rate and interpolation scheme used by CNC and machine characteristics such as machine accuracy and cost. Experimental data for process error and cycle operation time are obtained from profile machining M. Alberti · J. Ciurana (B) Department of Mechanical Engineering and Industrial Construction, Universitat de Girona, Av. Lluis Santaló s/n, 17071 Girona, Spain e-mail: [email protected] M. Alberti e-mail: [email protected] C. A. Rodríguez Centro de Innovacion en Diseño y Tecnología, Tecnológico de Monterrey, Nuevo León, Mexico e-mail: [email protected] T. Özel Department of Industrial and Systems Engineering, Rutgers University, Piscataway, NJ 08854, USA e-mail: [email protected] tests with different geometrical feature zones that are often used in manufacturing of discrete parts or die/moulds. All those input parameters have direct impact on productivity andmanufacturing cost. Artificial neural networkmodels are utilized for decision support system with reasonable prediction capability.