This book focuses on the application of soft computing in materials and manufacturing sectors with the objective to offer an intelligent approach to improve the manufacturing process, material selection and characterization techniques for developing advanced new materials. It unveils different models and soft computing techniques applicable in the field of advanced materials and solves the problems to help the industry and scientists to develop sustainable materials for all purposes. The book focuses on the overall well-being of the environment for better sustenance and livelihood. Firstly, the authors discuss the implementation of soft computing in the various areas of engineering materials. They also review the latest intelligent technologies and algorithms related to the state-of-the-art methodologies of monitoring and effective implementation of sustainable engineering practices. Finally the authors examine the future generation of sustainable and intelligent monitoring techniques beneficial for manufacturing, and cover novel soft computing techniques for the purpose of effective manufacturing processes at par with the standards laid down by the International Standards of Organization (ISO). This book is intended for academics and researchers from all the fields of engineering interested in joining interdisciplinary initiatives on soft computing techniques for advanced materials and manufacturing.

This book aims at addressing the challenges of contemporary manufacturing in Industry 4.0 environment and future manufacturing (aka Industry 5.0), by implementing soft computing as one of the major sub-fields of artificial intelligence. It contributes to development and application of the soft computing systems, including links to hardware, software and enterprise systems, in resolving modern manufacturing issues in complex, highly dynamic and globalized industrial circumstances. It embraces heterogeneous complementary aspects, such as control, monitoring and modeling of different manufacturing tasks, including intelligent robotic systems and processes, addressed by various machine learning and fuzzy techniques; modeling and parametric optimization of advanced conventional and non-conventional, eco-friendly manufacturing processes by using machine learning and evolutionary computing techniques; cybersecurity framework for Internet of Things-based systems addressing trustworthiness and resilience in machine-to-machine and human-machine collaboration; static and dynamic digital twins integration and synchronization in a smart factory environment; STEP-NC technology for a smart machine vision system, and integration of Open CNC with Service-Oriented Architecture for STEP-NC monitoring system in a smart manufacturing. Areas of interest include but are not limited to applications of soft computing to address the following: dynamic process/system modeling and simulation, dynamic process/system parametric optimization, dynamic planning and scheduling, smart, predictive maintenance, intelligent and autonomous systems, improved machine cognition, effective digital twins integration, human-machine collaboration, robots, and cobots.

In the rapidly evolving landscape of Industry 5.0, integrating emotional intelligence into the industrial framework is becoming increasingly crucial. Organizations are trying to navigate this uncharted territory and seeking guidance on understanding, implementing, and ethically managing artificial emotional intelligence (AEI). However, the absence of a comprehensive resource addressing these complexities has left a significant void in academic scholarship and industrial practice. Human-Machine Collaboration and Emotional Intelligence in Industry 5.0 offers a holistic exploration of emotion recognition, affective computing, and human-robot interaction. It equips readers with the knowledge and tools to successfully integrate AEI into Industry 5.0, ensuring a harmonious collaboration between humans and machines. This book is a go-to resource for scholars, industry professionals, and decision-makers seeking to leverage emotional intelligence in the Fifth Industrial Revolution by addressing practical implementations, ethical considerations, and real-world impacts.

This book evaluates the contributions of the electronic control unit software of an electric vehicle on sustainability and society, such as the reduction of emissions during a product design and the improvements in the vehicle. A sustainable transport model is proposed, demonstrating its economic viability. By validating software in a more efficient way and adding new functionalities to the software to enhance driving efficiency, energy consumption can be significantly reduced. Therefore, software validation and development have a significant impact on sustainability. This book offers innovative validation solutions based on artificial intelligence techniques to reduce validation time and emissions. The impact of driving efficiency on sustainable transport models is studied in detail, making proposals to be considered in the current environmental policies under discussion within the European Union in order to improve the sustainability of transport models. Vehicles are becoming sophisticated electronic systems due to the fact that they are integrating a significant number of electronic control units. This trend will certainly continue in the year to come. Consequently, software validation techniques are a key element for car manufacturers in order to ensure the quality of the vehicle. This book contributes to these efforts.

This book addresses and disseminates state-of-the-art research and development in the applications of soft computing techniques for renewable energy systems. It covers topics such as solar energy, wind energy, and solar concentrator technologies, as well as building systems and power generation systems. In all these areas, applications of soft computing methods such as artificial neural networks, genetic algorithms, particle swarm optimization, cuckoo search, fuzzy logic, and a combination of these, called hybrid systems, are included. This book is a source for students interested in the fields of renewable energy and the application of the soft computing. In addition, our book can be considered as a reference for researchers and academics since it will include applications of soft computing in different renewable energy systems.

Soft Computing Techniques in Solid Waste and Wastewater Management is a thorough guide to computational solutions for researchers working in solid waste and wastewater management operations. This book covers in-depth analysis of process variables, their effects on overall efficiencies, and optimal conditions and procedures to improve performance using soft computing techniques. These topics coupled with the systematic analyses described will help readers understand various techniques that can be effectively used to achieve the highest performance. In-depth case studies along with discussions on applications of various soft-computing techniques help readers control waste processes and come up with short-term, mid-term and long-term strategies. Waste management is an increasingly important field due to rapidly increasing levels of waste production around the world. Numerous potential solutions for reducing waste production are underway, including applications of machine learning and computational studies on waste management processes. This book details the diverse approaches and techniques in these fields, providing a single source of information researchers and industry practitioners. It is ideal for academics, researchers and engineers in waste management, environmental science, environmental engineering and computing, with relation to environmental science and waste management. - Provides a comprehensive reference on the implementation of soft computing techniques in waste management, drawing together current research and future implications - Includes detailed algorithms used, enabling authors to understand and appreciate potential applications - Presents relevant case studies in solid and wastewater management that show real-world applications of discussed technologies

This text emphasizes the importance of sustainable material, design, and manufacturing processes, and how the needs are changing day by day. It comprehensively covers important topics including material recycling, optimal utilization of resources, green materials, biocomposites, clean and green synthesis, stable material properties, utilization of renewable energy sources, ergonomic design, and sustainable design. The text examines the design process, manufacturing, and upscaling of next-generation materials and their application in diverse industries. The text is primarily written for graduate students and academic researchers in the fields of manufacturing engineering, materials science, mechanical engineering, and environmental engineering. Presents an in-depth understanding of the progress of the need for new innovative and next-generation materials. Discusses biocomposites and green materials for eco-friendly products in a comprehensive manner. Explores recycling techniques of materials for sustainable manufacturing. Presents conceptual framework of sustainable product development. Covers important topics such as process optimization, renewable energy, and 3D printing in detail. The text discusses the designing process of these new materials, manufacturing, and upscaling of these materials along with their selection for industrial applications. It further focuses on improving surface homogeneity in nanoparticle scattering during dip coating for stable and efficient wettability during oil/water separation. It will serve as an ideal reference text for graduate students and academic researchers in the fields of manufacturing engineering, materials science, mechanical engineering, and environmental engineering.

The evolution of soft computing applications has offered a multitude of methodologies and techniques that are useful in facilitating new ways to address practical and real scenarios in a variety of fields. In particular, these concepts have created significant developments in the engineering field. Soft Computing Techniques and Applications in Mechanical Engineering is a pivotal reference source for the latest research findings on a comprehensive range of soft computing techniques applied in various fields of mechanical engineering. Featuring extensive coverage on relevant areas such as thermodynamics, fuzzy computing, and computational intelligence, this publication is an ideal resource for students, engineers, research scientists, and academicians involved in soft computing techniques and applications in mechanical engineering areas.

Materials Selection for Sustainability in the Built Environment: Environmental, Social and Economic Aspects presents the current state-of-the-art when it comes to the decision-making process for choosing construction materials to deliver sustainable construction projects. Aspects covered include the science of enhanced decision-making via operational research and machine learning techniques and how this can be implemented in various disciplines such as architecture, engineering and construction. To this end, the book discusses environmental, economic and social aspects in assessing construction materials and presents different tools and methods that can benefit and facilitate this process. Finally, the book reviews previous publications on construction material selection and presents essential discussions on the role professionals, researchers, contractors and governments play in making more sustainable decisions on the built environment. - Presents a lifecycle management-based, systematic and integrated approach for sustainable construction materials selection - Discusses the impact of materials selection, covering every aspect of sustainability (environmental, social and economic aspects) - Looks at the concept of the circular economy - Provides case studies on decision-making methods in combination with lifecycle sustainability assessments

The proclivity of today’s technology to think like humans may be seen in new developing disciplines such as neural computing, fuzzy logic, evolutionary computation, machine learning, and probabilistic reasoning. These strategies are grouped together into one main technique known as "soft computing." This book discusses the most recent soft computing and fuzzy logic-based applications and innovations in industrial advancements, supply chain and logistics, system optimization, decision-making, artificial intelligence, smart systems, and other rapidly evolving technologies. In today’s competitive world, the book provides soft computing solutions to help companies overcome the obstacles posed by sophisticated decision-making systems.