Decision Support Models for the Selection of Production Strategies in the Paradigm of Digital Manufacturing, Based on Technologies, Costs and Productivity Levels

Abstract

Digital manufacturing has opened a new window in the way to approach the manufacture of parts. The possible switch from manufacturing and holding physical stock to manoeuvring with a fully-digital one is promising but still has not been undertaken-or only in a small proportion-by the majority of the manufacturing companies. What are the cost and productivity frontiers that halt the transformation taking place so far? When does it make sense, in terms of production volume and costs, to undertake this transformation? What level of savings could be achieved and what investments would be favourable? The base line of the present chapter is to depict quantitative tools to address the potential impact of endeavouring digital transformation in manufacturing environments, considering costing and production variables, as well as technological decision-making parameters. Keeping the modelling of the demand very basic, some exploration on the degree of postponement of the production is discussed. Also, decision support systems (DSSs) for manufacturing selection are reviewed. Finally, a case study serves to apply the mathematical framework presented and to quantify the results in a realistic industrial case. Using this case, the chapter outlines and describes how to apply artificial intelligence (AI) techniques to implement the DSSs.

Evaluation of a multi-user requirements axiomatic design decision support tool for manufacturing process selection

“…Giachetti (1997) states that the MPS challenge often represents decision-making problem characterised by ambiguous requirements and parameters in the preliminary design stages. According to Minguella-Canela and Buj Corral (2020), decision support for MPS involves making choices which related to process capabilities, market demands, and production constraints. Such decisions are taken on the basis of manufacturing knowledge and experience that exist in design domains.…”

SLM Manufacturing Redesign of Cooling Inserts for High Production Steel Moulds and Benchmarking with Other Industrial Additive Manufacturing Strategies

“…As a framework for comparison, we can use a variation of the cost schema presented in Minguella et al [39]. In particular, the cost per produced unit can be calculated as in Equation ( 1):…”