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  1. Inspired by the natural intelligence of humans and bio-evolution, Artificial Intelligence (AI) has seen accelerated growth since the beginning of the 21st century. Successful AI applications have been broadly reported, with Industry 4.0 providing a thematic platform for AI-related research and development in manufacturing. This paper highlights applications of AI in manufacturing, ranging from production system design and planning to process modeling, optimization, quality assurance, maintenance, automated assembly and disassembly. In addition, the paper presents an overview of representative manufacturing problems and matching AI solutions, and a perspective of future research to leverage AI towards the realization of smart manufacturing. 
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  2. Manufacturers today are increasingly connected as part of a smart and connected community. This transformation offers great potential to deepen their collaborations through resource and knowledge sharing. While the benefits of artificial intelligence (AI) have been increasingly demonstrated for data-driven modeling, data privacy has remained a major concern. Consequently, information embedded in data collected by individual manufacturers is typically siloed within the bounds of the data owners and thus under-utilized. This paper describes an approach to tackling this challenge by federated learning, where each data owner contributes to the creation of a global data model by computing a local update of relevant model parameters based on its own data. The local updates are then aggregated by a central server to train a global model. Since only the model parameters instead of the data are shared across the various data owners, data-privacy is preserved. Evaluation using sensor data for machine condition monitoring has shown that the global model produced by federated learning is more accurate and robust than the local models established by each of the single data owners. The result demonstrates the benefit of secure information sharing for individual manufacturers, especially Small and Mid-Sized Manufacturers (SMMs), for improved sustainable operation. 
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