# Maintenance 4.0 Technologies for Sustainable Manufacturing
###### Abstract  
The maintenance can be defined as \"the systematic execution of monitoring, repair, and replacement tasks designed to preserve or reinstate the desired functionality of a machine\". Today, maintenance management is a very complex function involving technical and managerial skills and the flexibility to cope with the enormous dynamics of the business environment [8]. Maintenance management is key in modern production systems and requires proper attention [9]. Maintenance management should be treated as long-term strategic planning, integrating all stages of the product life cycle. This strategic planning must also anticipate changes in future social, economic, and environmental trends and incorporate innovative technologies into operations [10]. Moreover, according to [11, 12, 13], maintenance management is commonly considered the first step in an Industry 4.0 environment to have technical and economic advantages. Industry 4.0 technologies offer new possibilities for maintenance managers and support to improve maintenance strategies [14]. Moreover, according to the authors of [15], integrating I4.0 technology with maintenance can support the company in meeting the economic, environmental, and social challenges of sustainable manufacturing.  
19 July 202418 August 2024  
and schedule maintenance actions to maximize its remaining useful-life\". Many predictive maintenance methods have been developed with the development of big data methods and IoT technology [22; 23]. In data-driven predictive maintenance strategies, machine learning (ML) can predict the system's operational status and remaining useful life (RUL) [24; 25; 26]. Additionally, ML methods support the planning of maintenance activities via connected IoT technology to reduce downtime and maintenance costs and increase machine availability [27]. PdM can also be implemented using digital twins [28; 29; 30]. A \"digital twin\" is a dynamic, digital replica of a technical object, such as a physical system, device, machine, or production process. This solution is an integral part of Industry 4.0 and is particularly effective in sustainable production and maintenance [31; 32]. Research on the application of DT in maintenance has been conducted by, among others, [33; 34].  
As predictive maintenance advances and is more widely adopted by companies, augmented reality can more effectively support machine inspection [35; 36]. AR represents effective maintenance support, guiding operators through diagnostics, inspection, and training [37; 38; 39; 40; 41].  
A literature analysis shows that implementing I4.0 technologies has many advantages [42; 43; 44]. However, despite the potential benefits, the implementation of I4.0 technologies in maintenance requires not only overcoming the technological challenges related to the integration with Industry 4.0. Other challenges, such as sustainability, must also be considered, including social, economic, and environmental challenges, to ensure sustainable manufacturing, which is greatly influenced by maintenance [45; 46]. According to the authors of [47; 48], the ability to anticipate, avoid, and quickly solve problems by applying Industry 4.0 technologies to maintenance practices is an invaluable tool for a company in achieving its sustainability goals  
The objective of the following Special Issue (SI) is to present the latest advances and developments in new methods, techniques, systems, and tools dedicated to applying Maintenance 4.0 technologies to the economic, environmental, and social challenges of sustainable manufacturing. The present Special Issue captures the diversity of research focusing on the issues of Maintenance 4.0 and sustainability. The SI contains 13 articles, which are briefly described in the following chapter. The following Editorial encourages the reader to familiarize themselves with the articles and further develop the still topical issues of maintenance, Industry 4.0 technologies, and sustainable manufacturing.