Prior to the physical build of the industrial automation system, some challenges arise, such as processes’ cycle times calculations, ergonomics and safety evaluation, and the integration of separate machines to the complete production shops. This, in turn, requires reconfiguring the processes and component parameters. As a result, the lifecycle of the system development is prolonged, and the potential for erroneous performance increases. In modern digital manufacturing environments, virtual engineering (VE) and virtual commissioning (VC) serve as effective tools to tackle the aforementioned problems and their consequences. The virtual models developed for VE and VC not only assist system developers in the physical build stage but also in the following stages of the system lifecycle by providing a common virtual model, a digital twin (DT), of the manufacturing processes and the product. This developed model should possess the ability to simulate the system behaviour, e.g., the mechanics, kinematics, speed and acceleration profiles. Three stakeholders are involved in the development process: the machine builder, system integrator and end user. The current work focuses on the virtual engineering approach to support the entire lifecycle of a manufacturing system from the machine builder, system integrator and end user perspectives. For this purpose, it puts forward a systematic methodology of implementing VC and VE using a toolset developed by the Automation Systems Group at the University of Warwick within an industrial project. The suggested methodology is illustrated in a case study where a digital twin of a physical station was modelled, developed and tested in parallel with the physical machine development and build. Finally, the benefits and limitations are highlighted based on the gained outcomes and the implemented activities.

The rise in urbanisation and resource consumption has highlighted the urgent need for sustainable economic models. The traditional linear economy, which relies heavily on non-renewable resources, exceeds the Earth’s capacity and poses significant sustainability challenges. As a result, there is an increasing necessity to transition towards a circular economy (CE) as a more sustainable alternative. Saudi Arabia, one of the world’s largest economies, is striving to implement this shift due to considerable environmental and economic challenges. However, the country currently lacks a dedicated circular economy strategy, which hinders its efforts to address issues such as waste management and excessive consumption. To bridge this gap, a comprehensive framework was developed to assess and compare Saudi Arabia’s circular economy initiatives, strategies, and policies with those of China, Japan, and Europe. Data were collected and analysed using thematic analysis, allowing for the identification of key similarities and differences between these regions. The study revealed notable variations in policies and practices, highlighting best practices that Saudi Arabia could adopt to strengthen its sustainability efforts. The findings underscore the importance of incorporating global best practices while tailoring strategies to the Kingdom’s specific needs. Policymakers and researchers in Saudi Arabia can utilise these insights to support a more effective transition towards a circular economy. Future research could adopt a quantitative approach, using indicators and metrics to enhance the impact of these findings.

Energy flexibility of manufacturing systems helps to meet sustainable manufacturing requirements and is getting significant importance with rising energy prices and noticeable climate changes. Considering the need to proactively enable energy flexibility in modern manufacturing systems, this work presents a component-based design approach that aims to embed energy flexibility in the design of cyber-physical production systems. To this end, energy management using Industry 4.0 technologies (e.g., Internet of Things and Cyber-physical Systems) is compared to the literature on energy flexibility in order to evaluate to what extent the energy flexibility practice takes advantage of Industry 4.0 technologies. Another dimension is the coverage of the life cycle of the manufacturing system which guarantees its sustainable design and the ability to achieve energy flexibility by configuring the energy consumption behaviour. A data-based design approach of the energy-flexible components is proposed in the spirit of the Reference Architectural Model Industrie 4.0 (RAMI 4.0), and then it is exemplified using an electric drive (as a component) in order to show the practical applicability of the approach. The energy consumption behaviour of the component is modelled using machine learning techniques. The digital twin of the studied component is developed using Visual Components virtual engineering environment, then its energy consumption behaviour is included in the model allowing the system integrator/decision-maker to configure the component based on the energy availability/price. Finally, external services in terms of an optimisation module and a deep learning module are connected to the digital twin.