Abstract

The emerging scenario designed by digital technologies connected to Industry 4.0 is pushing towards increasingly sustainable companies. Access to the multiple benefits of digitalization (such as increased productivity, flexibility, efficiency, quality, lower consumption of resources, and the improvement of worker safety) is possible by purchasing new-generation machinery. However, thanks to smart retrofitting processes, companies can extend the shelf life of machinery without replacing it entirely. This work aims to present a framework to assess the sustainability of implementing a smart retrofitting process in old machines as an alternative to replacement from a triple bottom line (economic, environmental, and social) perspective. Due to the multidimensional and multidisciplinary variables that the proposed framework must consider, a multicriteria decision-making process is developed to identify the best transition solution from Industry 3.0 to 4.0. Then, we analyze a case study in which, thanks to the previously proposed methodology, two types of smart retrofitting on a column drill are compared with three replacement options for the same machine tool. In conclusion, the case study shows that retrofitting in the context of Industry 4.0 (or smart retrofitting), despite its high acquisition cost, is the best solution in terms of sustainability, and that this is because the smart retrofitting solution not only positively influences all parameters of digitization but also has a strong impact on the safety criterion.

Highlights

  • Industry 4.0 paradigms lead manufacturing companies to rethink their processes and organization, and prepare their structure for radical digitalization through technologies such as the Internet of Things, cloud computing, augmented reality, and artificial intelligence, etc

  • End-of-life management in machine tools is a problem that arises when the machine can no longer guarantee the required functionality in terms of quality, time, reliability, and safety. When these characteristics are no longer met, the choice is made between buying a new machine or retrofitting

  • The framework was developed in five stages: “objectives analysis”, “market analysis”, “retrofitting analysis”, “collecting information,” and “selection of the best solution through the analytic hierarchy process (AHP)”

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Summary

Introduction

Industry 4.0 paradigms lead manufacturing companies to rethink their processes and organization, and prepare their structure for radical digitalization through technologies such as the Internet of Things, cloud computing, augmented reality, and artificial intelligence, etc. In order to remain competitive, companies are forced to adapt their machinery by first considering economic aspects, and more recently by taking into consideration environmental and social aspects [1]. This is a new business model that allows companies to aim for a circular economy capable of self-renewal and the spread of sustainability principles [2]. Despite these business needs, the costs and time needed to replace old machines may be economically unsustainable for many SMEs [3]. In addition to the classical retrofitting features, smart retrofitting involves implementing AI tools and other technologies provided by Industry 4.0

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