Machine Learning for Optimized Additive Manufacturing: Challenges, Opportunities, and Sustainability
摘要
The Industrial Revolution marks substantial commutes and metamorphosis in manufacturing and industrial processes with contemporary innovative technologies. Industry 1.0 (IR 1.0) 1784 saw the use of steam engines helping improve travel and manufacturing. Industry 2.0 during 1870 IR2.0 saw a major use of electricity, steel and iron industries, and the genesis of real production at scale. The third industry manufacturing paradigm shift during 1969 saw the utilization of circuitry or electrotechnology and automation, and parturition of the computer. The industry manufacturing paradigm shift 4.0 began to see the use of computerized security frameworks and machine integration, and the elimination of human labor to utilize advanced robots. Most companies in Industry 4.0 put emphasis on profit and production at scale. Industry manufacturing paradigm shift 5.0 bases its stance on human-centric design, environmental sustainability, social sustainability, and the metaverse. Additive manufacturing AM is key to IR 5.0 due to its ergonomic advantages, reduction in waste, possible environmental-centric advantages, its socially sustainable and, thus, meets key characteristics of a major IR 5.0 technology. Additive manufacturing has evolved since the first patent of Stereolithography by Charles Hull, its adoption by different companies like Shipway. This book chapter covers the role of additive manufacturing enhanced with machine learning AM-ML fused technologies in industry 5.0, advantages, limitations, possible solutions to the limitations, its application in aerospace, civil and architectural works, prototyping, automotive, and myriad other industries.