Optimal Allocation of Decision-Making Authority in IoT-Based Manufacturing Enterprises
Xinbao Liu,
Jun Pei,
Lin Liu,
Hao Cheng,
Mi Zhou and
Panos M. Pardalos
Additional contact information
Xinbao Liu: Hefei University of Technology
Jun Pei: Hefei University of Technology
Lin Liu: Hefei University of Technology
Hao Cheng: Hefei University of Technology
Mi Zhou: Hefei University of Technology
Panos M. Pardalos: University of Florida
Chapter Chapter 2 in Optimization and Management in Manufacturing Engineering, 2017, pp 35-61 from Springer
Abstract:
Abstract Global economic integration and information network have brought radical changes to the operational management of business processes. Emerging information technologies, such as the Internet of Things (IoT) and big data, have fostered customers’ changing personalized demands and accelerated the product updating speed, thereby impacting traditional production patterns. Empirical studies found that the IoT infrastructure can effectively support information systems of next-generation manufacturing enterprises [28]. More specifically, the requisition and sharing of a product’s life cycle (e.g., market demand, usage, and recycling) information in an IoT-based manufacturing enterprise have the following advantages over traditional manufacturing scenarios: (1) more comprehensive acquisition of product life cycle information, which would be impossible in a traditional manufacturing environment, (2) precise detection and analysis of on-site data through the perceptual and application layers of the condensed sensing network, and (3) faster information transmission in an intelligent manufacturing environment, so different hierarchies can conveniently access the needed information.
Date: 2017
References: Add references at CitEc
Citations:
There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:spr:spochp:978-3-319-64568-1_2
Ordering information: This item can be ordered from
http://www.springer.com/9783319645681
DOI: 10.1007/978-3-319-64568-1_2
Access Statistics for this chapter
More chapters in Springer Optimization and Its Applications from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().