Decision support models for the selection of production strategies in the paradigm of digital manufacturing, based on technologies, costs and productivity levels
Document typePart of book or chapter of book
Rights accessOpen Access
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.
CitationMinguella-Canela, J.; Buj-Corral, I. Decision support models for the selection of production strategies in the paradigm of digital manufacturing, based on technologies, costs and productivity levels. A: "New trends in the use of artificial intelligence for the Industry 4.0". London: IntechOpen, 2019, p. 1-25.