Research Topic

Intelligent Sustainable Manufacturing Solutions to Process Planning and Production Scheduling

About this Research Topic

A new scale of greenization, digitization and industrialization has been driving changes in our world more profoundly than ever before. Achieving material and energy efficiency has become a major mission for manufacturers to stay globally competitive. With the increasingly rich production data from the wide implementation of Computer Numerical Control (CNC) machines, ubiquitous sensors, and smart equipment, this mission can be better achieved through the Internet-of-Things (IoT) and artificial intelligence (AI) for optimization and control in manufacturing systems. The idea of “Integrated Service Management (ISM) solutions” applies to all levels of the manufacturing system, from process-related decisions to multi-company activities. This Research Topic focuses on Process Planning and Production Scheduling for ISM.

Process planning and production scheduling provide a link between product design and manufacturing and are two of the most important functions in the modern ISM system. A process plan specifies what manufacturing resources and technical operations/routes are needed to produce a product. With the process plans for all the products to be produced as input, production scheduling seeks to schedule operations on machines, while preserving the precedence relationships embedded within the process plans. It is well recognized that both process planning and production scheduling affect such traditional manufacturing system performance measures as throughput rate and cost, but there is growing recognition that such performance measures as waste stream size, and amount of energy and material consumed, are also dependent on the production schedule and the process plan. With the rapid development of machine intelligence, including deep learning, swarm intelligence and cognitive science, it plays a more and more important role to utilize the machine intelligence models and algorithms in process planning and production scheduling towards ISM.

The goal of this Research Topic is to explore scientific models, methods and technologies, with both solid theoretical development and practical importance to reshape manufacturing systems, transform production modes and enrich products. The central theme of the proposed Research Topic is on ISM Solutions to Process Planning and Production Scheduling, where information technology-based modeling, analysis, control, and optimization are the focus areas, and broad aspects and issues will be well discussed. Topics to be covered include, but are not limited to, the following:

• Process planning in ISM
• Process parameters optimization in ISM
• Job shop/flow shop/open shop scheduling in ISM
• Dynamic/Real-time scheduling in ISM
• Flexible scheduling in ISM
• Integrated process planning and production scheduling in ISM
• Process planning and production scheduling with multi-criteria in ISM
• Parallel computing for process planning and production scheduling in ISM
• Intelligent remanufacturing process planning
• Integrated Intelligent process planning for manufacturing and remanufacturing
• Energy and carbon footprint in intelligent process planning and production scheduling
• Other relating research topics


Keywords: Intelligent Manufacturing, Sustainable Manufacturing, Process Planning, Production Scheduling, Materials Efficiency, Energy Efficiency


Important Note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.

A new scale of greenization, digitization and industrialization has been driving changes in our world more profoundly than ever before. Achieving material and energy efficiency has become a major mission for manufacturers to stay globally competitive. With the increasingly rich production data from the wide implementation of Computer Numerical Control (CNC) machines, ubiquitous sensors, and smart equipment, this mission can be better achieved through the Internet-of-Things (IoT) and artificial intelligence (AI) for optimization and control in manufacturing systems. The idea of “Integrated Service Management (ISM) solutions” applies to all levels of the manufacturing system, from process-related decisions to multi-company activities. This Research Topic focuses on Process Planning and Production Scheduling for ISM.

Process planning and production scheduling provide a link between product design and manufacturing and are two of the most important functions in the modern ISM system. A process plan specifies what manufacturing resources and technical operations/routes are needed to produce a product. With the process plans for all the products to be produced as input, production scheduling seeks to schedule operations on machines, while preserving the precedence relationships embedded within the process plans. It is well recognized that both process planning and production scheduling affect such traditional manufacturing system performance measures as throughput rate and cost, but there is growing recognition that such performance measures as waste stream size, and amount of energy and material consumed, are also dependent on the production schedule and the process plan. With the rapid development of machine intelligence, including deep learning, swarm intelligence and cognitive science, it plays a more and more important role to utilize the machine intelligence models and algorithms in process planning and production scheduling towards ISM.

The goal of this Research Topic is to explore scientific models, methods and technologies, with both solid theoretical development and practical importance to reshape manufacturing systems, transform production modes and enrich products. The central theme of the proposed Research Topic is on ISM Solutions to Process Planning and Production Scheduling, where information technology-based modeling, analysis, control, and optimization are the focus areas, and broad aspects and issues will be well discussed. Topics to be covered include, but are not limited to, the following:

• Process planning in ISM
• Process parameters optimization in ISM
• Job shop/flow shop/open shop scheduling in ISM
• Dynamic/Real-time scheduling in ISM
• Flexible scheduling in ISM
• Integrated process planning and production scheduling in ISM
• Process planning and production scheduling with multi-criteria in ISM
• Parallel computing for process planning and production scheduling in ISM
• Intelligent remanufacturing process planning
• Integrated Intelligent process planning for manufacturing and remanufacturing
• Energy and carbon footprint in intelligent process planning and production scheduling
• Other relating research topics


Keywords: Intelligent Manufacturing, Sustainable Manufacturing, Process Planning, Production Scheduling, Materials Efficiency, Energy Efficiency


Important Note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.

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Submission Deadlines

26 June 2020 Manuscript

Participating Journals

Manuscripts can be submitted to this Research Topic via the following journals:

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Topic Editors

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Submission Deadlines

26 June 2020 Manuscript

Participating Journals

Manuscripts can be submitted to this Research Topic via the following journals:

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