Digital Retrofitting of legacy machines: A holistic procedure model for industrial companies. (January 2022)

• Record Type: Journal Article
• Authors: Tantscher, Dominik; Mayer, Barbara
• Is Part Of: CIRP journal of manufacturing science and technology. Volume 36(2022)
• Page Start: 35
• Page End: 44
• Publication Date: 2022-01
• Subjects: Digital Transformation -- Digital Retrofitting -- Industry 4.0 -- Procedure model; Manufacturing processes -- Periodicals; 670.5
• DOI: 10.1016/j.cirpj.2021.10.011
• Languages: English
• ISSNs: 1755-5817

Abstract

Abstract: Digital Transformation is a demanding evolutional process for industrial companies that touches all important business areas. A central role for the development towards a more flexible and efficient manufacture play production data. However, most machines in use lack a digital interface, such that they are not capable to connect in a network. Thus, data cannot be utilized. One solution from the technical perspective is Digital Retrofitting focusing on the implementation of additional sensors and edge devices to digitally connect the machine and transforming it into a cyber-physical system. This approach is also economically promising for companies since investing in new machines is far more expensive than the retrofitting of legacy systems. Nevertheless, industrial practice shows that Digital Retrofitting projects often do not lead to sustainable solutions because they lack integration into the digital transformation process. This paper thus introduces a holistic procedure model for Digital Retrofitting that is the result of an analysis and clustering of existing process models. The framework incorporates the perspectives on digital strategy, interdisciplinarity, change and lean management and, therefore, provides a guideline for companies leading to a more effective and efficient implementation process with sustainable impact. Furthermore, a description of a successful validation of the procedure model is given on the example of a condition monitoring use case in the Smart Production Lab of FH JOANNEUM.