The Perceived Value of Additively Manufactured Digital Spare Parts in the Industry: An Empirical Investigation

Abstract

Cite: Chekurov S, Metsä-Kortelainen S, Salmi M, Roda I, Jussila A., "The perceived value of additively manufactured digital spare parts in industry: an empirical investigation".Abstract: The purpose of this paper is to verify the conceptual benefits of the implementation of additive manufacturing (AM) in spare part supply chains from the point of view of the industry. Focus group interviews consisting of five sessions and 46 experts in manufacturing were conducted for this study. The focus group interviews served to identify the issues in the adoption of digital spare parts (DSP) and to expand on the available literature. The benefits found in the reviewed literature were partially verified by the participants but certain limitations, such as the excessive need of post processing, supplier quality parity, and ICT inadequacies, were presented that were absent or not highlighted in literature. The information gathered from the participants made it possible to create a realistic model of a digital spare part distribution network. According to the focus group interviews, digital spare parts could be deployed immediately for a specific type of product in the long tails of company spare part catalogues. However, improvements in AM, company ICT infrastructure, and 3D model file formats need to be achieved for a larger deployment of DSP.

Assessing the potential of additive manufacturing for the provision of spare parts

“…Furthermore, the design initiates with the assumption that a digital model of the spare part exists or can be easily obtained. However, in practice, the design file may be unavailable (since it is the intellectual property of the supplier), nonexistent (as is often the case for obsolete spare parts), or insufficient (like in the case of 2D drawings) (Chekurov, Metsä‐Kortelainen, Salmi, Roda, & Jussila, ). In addition, new products require various product development activities, for example, master data, performance testing, and validation (Krishnan & Ulrich, ).…”

Additive manufacturing systems integration

“…The growth of intelligent product development and frameworks using AM has notably accelerated, spanning applications such as antenna structures corresponding electromagnetics in dependence to the components exclusively designed to be additively manufactured [27]; [28]. Various AM methods have been utilized for electromagnetic structures steering, using materials like filament, resin, powder, and nanoparticle inks adaptable to smart composites [27], characterized by lightness and ease of use.…”

“…AM has evolved from a prototyping method to a valuable tool for manufacturing end-use components, presenting unprecedented design freedom and capabilities. However, the advantages of AM currently extend beyond design possibilities, with operational benefits like improved delivery times and reduced manufacturing costs playing an integral role [28]. In optimizing flow-level understanding of systems development opportunities on AM, it is recommended (also by [28] to classify end-user applications based on design case for each category segregated physics, what composite must be manufactured.…”

“…However, the advantages of AM currently extend beyond design possibilities, with operational benefits like improved delivery times and reduced manufacturing costs playing an integral role [28]. In optimizing flow-level understanding of systems development opportunities on AM, it is recommended (also by [28] to classify end-user applications based on design case for each category segregated physics, what composite must be manufactured. In conjunction with AM advancements, artificial neural network algorithms such as learning vector quantization have emerged as potent tools for processing vast data volumes and enhancing system predictive abilities.…”