Abstract
Combining the knowledge about additive manufacturing technologies available in the literature with the results of empirical research in Polish manufacturing enterprises, regarding the implementation of AM, using the Bayesian network, will allow the recent demand for AM technologies to be defined in the context of an industry’s needs. The main purpose of the study is to build a new model that integrates: (1) knowledge about the implementation of AM in manufacturing companies, gained from the literature, (2) knowledge about the demands and state of the use of AM from 250 Polish metal and automotive manufacturing enterprises, and (3) Bayesian networks. The results reveal that the model developed is able to accurately detect the key determinants of the implementation process of AM technologies within a manufacturing company and identify the specific requirements for the further implementation of additive technologies. The freshness of our work is defining the demand for AM technology based on the knowledge gained from literature and knowledge received through empirical study. The possibilities of using the results of research in economic practice were demonstrated. This new approach can be treated as a solution, which will both direct and help mangers to take the decision to implement AM technologies.
Highlights
Competitive market and the changing needs of customers mean that, ever more frequently, companies are forced to react quickly and modernise their production lines.In order to avoid technological backwardness, manufacturing companies are looking for new technological solutions in the area of product, process and material improvement.Additive manufacturing (AM) technologies are becoming increasingly popular, and this is the case with laser technologies in the automotive, aviation, military and metal industries [1,2]
Additive manufacturing technologies allow the costly replacement of machine and equipment components to be avoided, offering the possibility of repair using, inter alia, laser material deposition (LMD), referred to as direct energy deposition (DED)
Formalising AM knowledge based on descriptive logics (DLs), Design for Additive Manufacturing (DfAM)
Summary
Competitive market and the changing needs of customers mean that, ever more frequently, companies are forced to react quickly and modernise their production lines.In order to avoid technological backwardness, manufacturing companies are looking for new technological solutions in the area of product, process and material improvement.Additive manufacturing (AM) technologies are becoming increasingly popular, and this is the case with laser technologies in the automotive, aviation, military and metal industries [1,2]. In order to avoid technological backwardness, manufacturing companies are looking for new technological solutions in the area of product, process and material improvement. Additive technologies can be classified by the material used (1) the type of substrate structure (2) and the form of energy supply (3). Additive manufacturing technologies allow the costly replacement of machine and equipment components to be avoided, offering the possibility of repair using, inter alia, laser material deposition (LMD), referred to as direct energy deposition (DED). Often laser technologies allow the production parts with complex shape in a number of materials at various scales are of great interest in the areas of prototyping [3,4]
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