Buch, Englisch, Band 952, 544 Seiten, Format (B × H): 155 mm x 235 mm, Gewicht: 850 g
Proceedings of SOHOMA 2020
Buch, Englisch, Band 952, 544 Seiten, Format (B × H): 155 mm x 235 mm, Gewicht: 850 g
Reihe: Studies in Computational Intelligence
ISBN: 978-3-030-69375-6
Verlag: Springer International Publishing
The scientific theme of the book concerns “Manufacturing as a Service (MaaS)” which is developed in a layered cloud networked manufacturing perspective, from the shop floor resource sharing model to the virtual enterprise collaborative model, by distributing the cost of the manufacturing infrastructure - equipment, software, maintenance, networking - across all customers.
MaaS is approached in terms of new models of service-oriented, knowledge-based manufacturing systems optimized and reality-aware, that deliver value to customer and manufacturer via Big data analytics, Internet of Things communications, Machine learning and Digital twins embedded in Cyber-Physical System frameworks. From product design to after-sales services, MaaS relies on the servitization of manufacturing operations such as: Design as a Service, Predict as a Service or Maintain as a service.
The general scope of the book is to foster innovation in smart and sustainable manufacturing and logistics systems and in this context to promote concepts, methods and solutions for the digital transformation of manufacturing through service orientation in holonic and agent-based control with distributed intelligence.
The book’s readership is comprised by researchers and engineers working in the manufacturing value chain area who develop and use digital control solutions in the ‘Industry of the Future’ vision. The book also addresses to master and Ph.D. students enrolled in Engineering Sciences programs.
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Weitere Infos & Material
Cloud networked models of knowledge-based intelligent control towards Manufacturing as a Service.- About the applicability of IoT concept for classical manufacturing systems.- An open-source machine vision framework for smart manufacturing control.- Using cognitive technologies as cloud services for product quality control. A case study for greenhouse vegetables.
