Terms like Smart Manufacturing, Industry 4.0 and Digital Transformation are now commonplace and reflect the increased importance of advanced technologies in manufacturing and elsewhere. In the process industries, while it can be argued that the evolution of advanced digital technologies started in the past 40 years, it still has the potential to unlock billions of dollars of operating profit across the chemical and biochemical industries.
Smart Manufacturing is the use of technologies and processes which maximize data and connectedness to optimize safety, reliability and efficiency in the process industries. While there are many advanced technologies that fall into the umbrella of Smart Manufacturing, Artificial Intelligence (AI), Machine Learning (ML) and Industrial Internet of Things (IIoT) have made great progress in recent years, and now consist strong pillars of Smart Manufacturing in the Chemical Industry.
This Research Topic aims to highlight original research articles, perspectives, industrial applications, advances, and reviews on all aspects of Smart Manufacturing, including but not limited to AI, ML and IIoT. We welcome authors to present articles on theory, proof of concepts, and applications related to industrial operations in the chemical and biochemical areas. Areas of interest may include, but are not limited to:
• Applications of AI, ML, Big Data and IIoT in the chemical and biochemical industries
• AI and ML theory, reviews, advances, and applications, including deep learning, reinforcement learning, statistical learning, and fault detection.
• ML theory and applications for equipment monitoring, failure prediction and prognosis
• ML theory and applications for plant-wide monitoring, failure prediction and prognosis
• Industrial Applications of IoT, including solutions utilizing modern sensors, wireless technologies and 5G
• AI closed-loop process control
• Process and unit optimization, including plant-wide and real-time optimization
• AI, ML in safety monitoring and risk assessment
• Applications of AI, ML in process safety and reliability
• IIoT and Cybersecurity
• Applications of AI & ML in Cybersecurity
• AI and ML for plant operations and troubleshooting
• Smart visualization for manufacturing
• Applications of AR and VR in design, reliability, and process operation
• Inferential Modeling and soft sensors.
Dr. Jesus Flores-Cerrillo is an Associate Director working within the private company Linde Inc. The other Topic Editors declare no conflict of interest.
Terms like Smart Manufacturing, Industry 4.0 and Digital Transformation are now commonplace and reflect the increased importance of advanced technologies in manufacturing and elsewhere. In the process industries, while it can be argued that the evolution of advanced digital technologies started in the past 40 years, it still has the potential to unlock billions of dollars of operating profit across the chemical and biochemical industries.
Smart Manufacturing is the use of technologies and processes which maximize data and connectedness to optimize safety, reliability and efficiency in the process industries. While there are many advanced technologies that fall into the umbrella of Smart Manufacturing, Artificial Intelligence (AI), Machine Learning (ML) and Industrial Internet of Things (IIoT) have made great progress in recent years, and now consist strong pillars of Smart Manufacturing in the Chemical Industry.
This Research Topic aims to highlight original research articles, perspectives, industrial applications, advances, and reviews on all aspects of Smart Manufacturing, including but not limited to AI, ML and IIoT. We welcome authors to present articles on theory, proof of concepts, and applications related to industrial operations in the chemical and biochemical areas. Areas of interest may include, but are not limited to:
• Applications of AI, ML, Big Data and IIoT in the chemical and biochemical industries
• AI and ML theory, reviews, advances, and applications, including deep learning, reinforcement learning, statistical learning, and fault detection.
• ML theory and applications for equipment monitoring, failure prediction and prognosis
• ML theory and applications for plant-wide monitoring, failure prediction and prognosis
• Industrial Applications of IoT, including solutions utilizing modern sensors, wireless technologies and 5G
• AI closed-loop process control
• Process and unit optimization, including plant-wide and real-time optimization
• AI, ML in safety monitoring and risk assessment
• Applications of AI, ML in process safety and reliability
• IIoT and Cybersecurity
• Applications of AI & ML in Cybersecurity
• AI and ML for plant operations and troubleshooting
• Smart visualization for manufacturing
• Applications of AR and VR in design, reliability, and process operation
• Inferential Modeling and soft sensors.
Dr. Jesus Flores-Cerrillo is an Associate Director working within the private company Linde Inc. The other Topic Editors declare no conflict of interest.
