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.

Industry 4.0 aims to revolutionize the manufacturing sector to achieve sustainable and efficient production. The novel coronavirus pandemic has brought many challenges in different industries globally. Shortage in supply of raw material, changes in product demand, and factories closures due to general lockdown are all examples of such challenges. The adaption of Industry 4.0 technologies can address these challenges and prevent their recurrence in case of another pandemic outbreak in future. A prominent advantage of Industry 4.0 technologies is their capability of building resilient and flexible systems that are responsive to exceptional circumstances such as unpredictable market demand, supply chain interruptions, and manpower shortage which can be crucial at times of pandemics. This work focuses on discussing how different Industry 4.0 technologies such as Cyber Physical Systems, Additive Manufacturing, and Internet of Things can help the manufacturing sector overcome pandemics challenges. The role of Industry 4.0 technologies in raw material provenance identification and counterfeit prevention, collaboration and business continuity, agility and decentralization of manufacturing, crisis simulation, elimination of single point of failure risk, and other factors is discussed. Moreover, a self-assessment readiness model has been developed to help manufacturing firms determine their readiness level for implementing different Industry 4.0 technologies.

Microgrippers are miniature tools that have the capability to handle and manipulate micro- and nano-scale objects. The present work demonstrates the potential impact of the incorporation of perforations on a ‘hot and cold arm’ electrothermal actuation mechanism in order to improve the operation of microgrippers in terms of arm opening and operating temperature. By applying a voltage to one arm and setting the other as a ground, the current passes through the electrothermal actuator and induces its displacement along the in-plane direction. The difference in the geometry of the two arms causes one arm to expand more than the other and this results in transverse bending. A computational model was developed using a finite element analysis tool to simulate the response of the thermal actuators with varying geometries and investigate the impact of incorporating perforations on the arms of the thermal actuators to enhance its performance in terms of deflection and operating temperature. The simulation results were compared to their experimental counterparts reported in the literature. A good agreement between the numerical and experimental data was obtained. A novel design of a microgripper, made of perforated electrothermal actuators, was introduced. Its main characteristics, including the tip opening of the gripper arms, the applied voltage, and the stress and temperature distributions, were analyzed using the developed computational model. Different perforation shape and distribution were investigated. The present study demonstrates the capability of perforations to enhance the operation of microgrippers as manifested by the obtained higher tip displacement and lower tip temperature in comparison to conventional microgripper designs made of non-perforated thermal actuators. Furthermore, the highest stress generated on the microgripper elements was found to be much lower than the yield strength of the constituent material, which indicates proper functioning without any mechanical failure.

This paper studies the effect of a type-2 fuzzy adaptive PID (type-2 FAPID) controller on the performance of a mechatronics system such as differential mobile robot. In the proposed adaptive controller, the PID controller gains are automatically tuned using type-2 fuzzy systems. The performance of controllers is compared by simulating the robot traveling an undisturbed straight route and a circular route. Torque load disturbance is later added to the DC motors to draw better comparisons between the type-1 and type-2 FAPID controllers. The findings of this paper showed that the designed type-2 fuzzy adaptive PID controllers have enhanced the performance of differential mobile robot.

Composite sandwich structures are renowned for their ability to provide high flexural stiffness to weight ratios. This ability made them appealing to aerospace, wind turbines, and marine industries. The functionality of sandwich structures primarily depends on the stiffness and strength of the two composite sheets bounding their inner cores. However, when sandwich structures are subjected to transverse impacts or transverse concentrated loads, their cores can fail due to local buckling. This can subsequently trigger the failure of the entire sandwich structure. To prevent such failure, inner cores with increased buckling strengths are sought. However, currently, increasing the buckling strength of sandwich structures' cores mostly comes at the cost of increasing their weights. Conversely, this work aims to increase the buckling strength of one of the most common sandwich structure cores, namely the hexagonal honeycomb core, without increasing its weight. This is accomplished through superposing periodic imperfections to its cell walls. The introduced imperfections follow a sinusoidal form and are applied to each cell wall as a perturbation. Finite element simulations are used to determine the effect of applying the imperfections to the cell walls and to determine the imperfection level that leads to significant improvement in the core's buckling strength. Results demonstrate that the buckling strength of honeycomb cores can be enhanced by more than 30% with the introduction of a minimal amount of sinusoidal periodic imperfections.