This study introduces a step-by-step, summarized overview of direct methanol fuel cell (DMFC) fundamentals, thermodynamic–electrochemical principles, and system evaluation factors. In addition, a parametric investigation of a JENNY 600S DMFC is conducted to simulate cell performance behavior under varying operating conditions. The system is mathematically modeled and solved in MATLAB and accounts for multi-irreversibilities such as the activation and ohmic and concentration overpotentials. The performance of the modeled system was validated against theoretical and experimental results from the literature. The results indicated that increasing the fuel cell’s operating temperature yields enhanced output cell voltages due to enhanced methanol oxidation reactions. Nevertheless, the maximum efficiency limits of the fuel cell tend to decrease with an increase in temperature. In addition, the model has also depicted that enhanced output cell voltages are associated with increased oxygen consumption, resulting in the lower exit flowrates of the reactants.

Characterized by its resilience, connectivity, and real-time data processing capabilities, the fourth industrial revolution, referred to as Industry 4.0, is the main driver of today’s digital transformation. It is crucially important for manufacturing facilities to correctly identify the most suitable Industry 4.0 technologies that meet their operational schemes and production targets. Different technology selection frameworks were proposed to tackle this problem, several of which are complex, or require historic data from manufacturing facilities that might not always be available. The aim of this paper is to develop a novel Industry 4.0 selection framework that utilizes Fuzzy Analytical Hierarchy Process (FAHP) and Fuzzy Technique for Order of Preference by Similarity to Ideal Solution (FTOPSIS) to rank different Industry 4.0 technologies based on their economic, social, and environmental impact. The framework is also implemented on a real-life case study of a manufacturing firm to rank the different Industry 4.0 technologies required for its digital transformation based on their significance to the facility’s key performance indicators. The framework is utilized to select the top three Industry 4.0 technologies from a pool of eight technologies that are deemed important to the manufacturing firm. Results of the case study showed that Cyber-Physical Systems, Big Data analytics, and autonomous/industrial robots are the top three ranked technologies, having closeness coefficient scores of 0.964, 0.928, and 0.601, respectively. Moreover, the framework showed sensitivity towards weight changes. This is an advantage in the developed framework, since its main aim is to provide policymakers with a customized list of technologies based on their importance to the firm.

Friction stir welding (FSW) has gained increasing prominence in the realm of metal–plastic hybrid joints, yet its long-term sustainability remains a subject of uncertainty. This research investigates the sustainability aspect of FSW, positioning it against conventional techniques like adhesive bonding (AB) and self-piercing riveting (SPR). A comprehensive evaluation framework encompassing environmental, social, economic, and physical factors was employed, through which specified criteria were applied to select pertinent sustainability indicators across all dimensions to ensure a thorough assessment. In this study, two advanced multi-criteria decision-making methods (MCDM) were deployed for data normalization and aggregation. Sensitivity analysis was conducted to examine the robustness of the results. The outcomes yielded a sustainability rating system, facilitating a direct and insightful comparison with traditional methods. Based on the results of this study, SPR outperforms both FSW and AB in terms of overall sustainability with comparative average sustainability scores of 75.3%, 54.2%, and 35.3%, respectively. This study not only sheds light on the current state of FSW sustainability but also provides a valuable benchmark for decision-makers in selecting environmentally conscious methods for metal–plastic hybrid joints.