This article aims at reviewing the advancement of smart manufacturing, also referred to as, Industry 4.0., as an index among the global industrial players. This paper explores a literature review of recent trends in smart manufacturing, the use of smart manufacturing technologies, and their impact on using the Creativity Index to measure productivity, quality nowadays, and the environmental impact of different industries adoption. This, therefore, means that besides large manufacturers that are currently more inclined to the concept of smart manufacturing, small and medium enterprises are gradually beginning to realize the importance of its application. The use of IIoT, Big Data Analytics, AI, and DT has brought about changes that have been rewarding regarding productivity, which has improved by 15–20% and the defect rate has cut by approximately 50%. However, some disadvantages are still being experienced; higher initial capital investment, lack of proper skills among employees, and last but not least, security threats. The study focuses on aspects of proper implementation of strategies like pilot testing and gradual rollout and examines success ratios. Linear regression for predictive modeling and K-means clustering for anomaly detection are the two mathematical models that are explained with the help of making the readers familiar with the actual implementation in smart manufacturing. The paper also responds to the question of ethics and society, which refers to workforce dynamics and digital divide issues in this new industrial revolution. Therefore, this study contributes to the knowledge of the area of smart manufacturing by presenting a comprehensive vision of the subject that incorporates the technology itself, the application methods, and the effects of smart manufacturing on society to lay the foundation for future research and business uses.