Editorial: Life cycle engineering in the era of Industry 4.0

Abstract

In today’s sustainability debate, industries are working to modernise their life cycle engineering strategies. Identifying a sustainable competitive edge in the era of Industry 4.0 is the most critical problem. Consequently, researchers and industry experts worldwide have optimised product life cycle by integrating machine learning, modern computing technologies, information management, and other multifaceted technologies, viz., semantic interoperability. Nevertheless, there are gaps between life cycle engineering and evolving Industry 4.0 technologies. Therefore, it is crucial to optimise the product life cycle via. digitalisation, innovation, resilience, and sustainability. This will allow for more value throughout the whole product’s life cycle design and resource planning to environmentally friendly production, unrestricted operational availability, and full recycling or reusability. In light of this, this Research Topic aims to assemble articles highlighting innovations in life cycle engineering motivated by Industry 4.0. Three research articles and one review article are among the papers on this Research Topic that have been published. A sound maintenance plan is crucial for optimising life cycle engineering. The research work by Alamri and Mo used the failure mode and consequences analysis to build novel preventive maintenance (PM) schedule for a complex system. Their methodology mainly relies on mean-time-to-failure (MTTF) information derived from Industry 4.0 system feedback data. If new MTTF data becomes available, the technique makes it simple to change the PM schedule. The case study findings show that over 90% system reliability has been reached while ensuring that related costs are kept to a minimum. The technical, environmental, and economic effects of maintenance choices throughout the product life cycle are considered in this approach. Information management has pushed digital manufacturing to discover more effective ways to link and share data throughout different system stages. One of the cornerstones of Industry 4.0 is the horizontal and vertical integration of intelligent and self-adaptive systems. To develop an intelligent manufacturing system, Pereira et al. tackled the problem of semantic interoperability. This study provided a conceptual OPEN ACCESS