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A Perspective on Artificial Intelligence in ManufacturingArtificial Intelligence in Manufacturing Systems

A Perspective on Artificial Intelligence in Manufacturing: Artificial Intelligence in... [A manufacturing system is assumed to be comprising a combination of machines, cells, intra-logistics devices and other peripheral devices, used on the factory floor as well as on logistics. This chapter focuses on AI at the manufacturing system level. At system level, the volume and a variety of relevant data increase, activities are characterized by a higher degree of uncertainty and stochasticity, with several interdependencies among the parameters in non-linear relations. All these inherited attributes make transparency, predictability and adaptability more challenging tasks for AI. More specifically, the chapter examines (i) AI for the design of a manufacturing system that relates the design to process and the machine selection, the system layout as well as the capacity planning, (ii) AI for the operation of manufacturing systems that require planning and control of the material and the information flows and (iii) digital platforms and ICT technologies for the development and deployment AI applications in manufacturing systems. For each category, the scope and theoretical background are provided and then, selected cases of AI applications are discussed.] http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png

A Perspective on Artificial Intelligence in ManufacturingArtificial Intelligence in Manufacturing Systems

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Publisher
Springer International Publishing
Copyright
© The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2023
ISBN
978-3-031-21827-9
Pages
79 –135
DOI
10.1007/978-3-031-21828-6_4
Publisher site
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Abstract

[A manufacturing system is assumed to be comprising a combination of machines, cells, intra-logistics devices and other peripheral devices, used on the factory floor as well as on logistics. This chapter focuses on AI at the manufacturing system level. At system level, the volume and a variety of relevant data increase, activities are characterized by a higher degree of uncertainty and stochasticity, with several interdependencies among the parameters in non-linear relations. All these inherited attributes make transparency, predictability and adaptability more challenging tasks for AI. More specifically, the chapter examines (i) AI for the design of a manufacturing system that relates the design to process and the machine selection, the system layout as well as the capacity planning, (ii) AI for the operation of manufacturing systems that require planning and control of the material and the information flows and (iii) digital platforms and ICT technologies for the development and deployment AI applications in manufacturing systems. For each category, the scope and theoretical background are provided and then, selected cases of AI applications are discussed.]

Published: Jan 1, 2023

Keywords: Production scheduling; Manufacturing systems design; Shop floor control; Information flows; Digital Platforms in manufacturing; Supply chain management

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