The industrial sector is a crucial economic pillar, seeing annual increases in the production output. In the last few years, a greater emphasis has been placed on the efficient and sustainable use of resources within industry. The use of compressed air in this field is hence gaining interest. These systems have numerous benefits, such as relative low investment costs and reliability; however, they suffer from low-energy efficiency and are highly susceptible to faults. Conventional detection systems, such as ultrasonic leak detection, can be used to identify faults. However, these methods are time consuming, meaning that leakages are often left unattended, contributing to additional energy wastage. Studies published in this area often focus on the supply side rather than the demand side of pneumatic systems. This paper offers a novel review based on the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) methodology of fault detection methods on the demand side of compressed air systems, leading towards a comprehensive understanding of smart and sustainable pneumatic systems. Fifty-three studies were classified and reviewed under the following three areas: (a) demand parameters which help in identifying fault sources; (b) approaches taken to analyse the parametric data; and (c) the role of Artificial Intelligence (AI) in pneumatic fault monitoring systems. This review shows that fault detection on the demand side has received greater importance in the last five years and that data analysis is crucial for AI to be implemented correctly. Nevertheless, it is clear that further research in this sector is essential, in order to investigate more complex systems. It is envisaged that this study can promote the adoption of such systems, contributing to an energy-efficient and cost-effective industry.

It has long been argued that Factories are long life and complex products. The complexity of designing factories, and their underlying manufacturing systems, is further amplified when dealing with continuously changing customer demands. At the same time, due to research fragmentation, little if any scientific explanations are available supporting and exploiting the paradigm that "factories are products". In order to address this weakness, this paper presents research results arising from a comparative analysis of systematic "product design" and "manufacturing system design" approaches. The contribution emerging from this research is an integrated systematic design approach to changeable manufacturing systems, based on scientific concepts founded upon product design theories, and is explained through a case study in the paper. This research is part of collaboration between the CERU University of Malta and IAO Fraunhofer aimed at developing a digital decision support tool for planning changeable manufacturing systems

The World Bank has reported that over one billion individuals have a disability, implying that almost fifteen percent of the global inhabitants are susceptible to undergoing levels of discrimination, especially in employment. This issue may prevail on a manufacturing shop floor, whereby a wave of standardisation dominates such as in the design of shop floor workstations. Despite advances made in the literature, people with disabilities are still siloed from manufacturing. Consequently, the aim of this research work was to analyse literature’s current state of the art on the design of workstations for operators with disabilities within the context of Industry 5.0, where sustainability, human-centricity, and resilience are upheld. The study employed a systematic review of 69 publications from Scopus and Google Scholar published between 2013 and 2023, adhering to the updated PRISMA guidelines to identify the major research gaps. The review contributes an understanding of the current academic and industrial limitations such as the absence of social applicability of Industry 4.0 technology, the rift between academic knowhow and industrial implementation, and the lack of alignment with the sustainable development goals (SDGs). Additionally, the review uncovered an absence in work bridging four disciplines together: workstation design, Industry 5.0, sustainability, and disability. An unprecedented understanding of the interdependency between all four disciplines within the remit of smart, sustainable, and inclusive manufacturing workstations is contributed. This review proposes directions amidst the four most relevant SDGs—SDGs 8, 9, 10, and 12 to the topic.

In order to meet customer requirements, manufacturing companies need to cope with the challenge of constantly evolving product ranges. Breakthroughs in the analysis of big data will give us a better understanding of market trends and customer requirements, but there will always be some degree of uncertainty when foreseeing product evolution. Manufacturing system designers have to therefore take decisions under uncertainty, whilst considering other factors such as business, manufacturing and change strategies. In order to address this problem the factories need to be designed with a level of changeability that will allow them to be flexible or reconfigurable to produce future product platform evolutions. This paper thus contributes a novel fuzzy logic based approach to support manufacturing system designers in exploring changeability level decisions. Using this approach, this paper presents the system architecture used for an experimental implementation of an intelligent ICT tool for supporting the design of a changeable manufacturing system.