Using Computational Intelligence For Sustainable Manufacturing Of Advanced Materials
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Using Computational Intelligence for Sustainable Manufacturing of Advanced Materials
The shift toward sustainable manufacturing is vital for addressing the pressing environmental challenges of the 21st century. By integrating sustainability principles, manufacturing processes can minimize resource consumption, reduce greenhouse gas emissions, and extend product lifecycles. This approach emphasizes designing for regeneration, using eco-friendly materials, and adopting advanced digital technologies like artificial intelligence (AI), Internet of Things (IoT), and blockchain to optimize production and promote environmental stewardship. Sustainable manufacturing not only mitigates ecological harm but also fosters innovation, enhances competitiveness, and supports long-term economic and societal resilience. Adopting such practices is essential for transitioning to a more responsible and sustainable global economy. Using Computational Intelligence for Sustainable Manufacturing of Advanced Materials highlights how the application of computational intelligence techniques can promote resource and environmental sustainability in manufacturing systems and operational practices. It further examines how sustainable practices and advanced technologies in materials manufacturing can revolutionize production processes while minimizing environmental impact and promoting resource efficiency. Covering topics such as energy storage, nanoparticles, and biomaterials, this book is an excellent resource for computer scientists, business professionals, manufacturers, environmentalists, researchers, professionals, scholars, academicians, and more.
Innovative Materials for Next-Generation Defense Applications: Cost, Performance, and Mass Production
In the evolving landscape of global defense, the demand for innovative materials that deliver superior performance, cost-efficiency, and scalability is pressing. Next-generation defense applications rely heavily on cutting-edge materials that offer a strategic edge. These materials must meet the requirements for strength, durability, thermal stability, and weight reduction while also being feasible for large-scale production and integration. Balancing performance with cost-effectiveness and manufacturability presents a critical challenge, driving research into composites, nanomaterials, and manufacturing techniques. This exploration of emerging materials may redefine the future capabilities of defense systems. Innovative Materials for Next-Generation Defense Applications: Cost, Performance, and Mass Production explores advanced materials designed for modern defense technologies. It examines the properties required for these materials to meet the rigorous demands of defense applications, including high strength, corrosion resistance, wear resistance, thermal stability, and lightweight construction. This book covers topics such as material science, mass production, and biotechnology, and is a useful resource for business owners, engineers, biotechnologists, academicians, researchers, and material scientists.
Computational Intelligence based Optimization of Manufacturing Process for Sustainable Materials
The text comprehensively discusses computational models including artificial neural networks, agent-based models, and decision field theory for reliability engineering. It will serve as an ideal reference text for graduate students and academic researchers in the fields of industrial engineering, manufacturing engineering, computer engineering, and materials science. Discusses the development of sustainable materials using metaheuristic approaches. Covers computational models such as agent-based models, ontology, and decision field theory for reliability engineering. Presents swarm intelligence methods such as ant colony optimization, particle swarm optimization, and grey wolf optimization for solving the manufacturing process. Include case studies for industrial optimizations. Explores the use of computational optimization for reliability and maintainability theory. The text covers swarm intelligence techniques including ant colony optimization, particle swarm optimization, cuckoo search, and genetic algorithms for solving complex industrial problems of the manufacturing industry as well as predicting reliability, maintainability, and availability of several industrial components.