Design Principles for Shared Maintenance Analytics in Fleet Management
Pages 236 - 247
Abstract
Many of today’s production facilities are modular in design and therefore to some degree individual. Further, there is a variety of differing application contexts that impact the operation of machines as compared to the manufacturer’s test cases. However, knowledge for their maintenance at the place of operation is typically limited to the manufacturer’s (digitally) printed technical documentation delivered with the product. Even with local knowledge, this requires extensive time and fault data to understand and prevent machine failures. Thus, there is a need for shared maintenance analytics, a scalable, networked learning process that address these issues in fleet management. Despite partial success, which mainly stems from individual use cases, there is no generalizable architecture for a broader adoption or practical use as of yet. To address this issue, we derive design requirements, design principles, and design features to specify a system architecture for shared maintenance analytics in fleet management.
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Published In
Aug 2021
407 pages
ISBN:978-3-030-82404-4
DOI:10.1007/978-3-030-82405-1
© Springer Nature Switzerland AG 2021.
Publisher
Springer-Verlag
Berlin, Heidelberg
Publication History
Published: 04 August 2021
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