The current industrial production model faces major environmental, economic, and social challenges due to resource depletion, increasing energy demand, and climate change. Manufacturing significantly contributes to emissions, material consumption, and waste, making sustainable manufacturing (SM) essential for transitioning toward more resource-efficient, circular, and socially responsible systems. This study provides a structured overview of SM, focusing on enabling technologies and emerging research trends. Sustainability is analyzed through approaches such as sustainable development, cleaner production, eco-efficiency, and the circular economy. The role of key technologies—including additive manufacturing, artificial intelligence, big data analytics, the Internet of Things, digital twins, and cyber-physical systems—is examined in improving efficiency, reducing waste, and supporting circular production. A scoping review was conducted following the PRISMA-ScR guidelines using the Web of Science database, focusing on recent publications. The results highlight a growing integration of digital technologies, energy-efficient systems, and circular strategies, alongside the increasing importance of data-driven decision-making. A strong convergence between artificial intelligence, energy transition, circular economy approaches, and digital transformation is also identified. Overall, achieving sustainable manufacturing requires an integrated approach addressing environmental, economic, and social dimensions. This review maps the field and identifies key directions for future research and practice.
Martı́nez et al. (Wed,) studied this question.