Image Processing Reference
In-Depth Information
Another noteworthy trend in manufacturing networked systems will be the integration of
traditionally separate industrial systems, such as diagnostics and safety [,]. For example a
diagnostics system can raise safety alarms when a process variable is outside the expected range of
safe operations. Advancements in network partitioning allow the networked safety system opera-
tion to leverage networked diagnostics information into improved safety decision making, without
degradation of overall safety network performance. This capability opens the door to a number of
opportunities for improving safety, control, and diagnostics in manufacturing systems.
In summary, as the industry moves forward in networked communications, many among the
dozens of protocols that have been developed for industrial networks over the last few decades will
fall out of favor, but will not die overnight due to the large existing installed base and the long life-
time of manufacturing systems. In addition, new protocols may continue to emerge to address niches,
where a unique QoS balance is needed. However, it is expected that Ethernet and wireless will con-
tinue to grab larger and larger shares of the industrial networks installed base, driven largely by lower
cost through volume, the Internet, higher availability of solutions and tools for these network types
(e.g., Web-enabled tools), and the unmatched flexibility of wireless. Indeed, it is not unreasonable
to expect that, in the next decade, the next major milestone in industrial networking, namely, the
“wireless factory,” will be within reach, where diagnostics, control, and safety functions at multiple
levels throughout the factory are enabled utilizing wireless technology.
Acknowledgments
The authors would like to acknowledge support from the NSF ERC for reconfigurable manufactur-
ing systems (ERC-RMS) grant EEC-. We would also like to thank the many students of the
ERC-RMS who did much of the work on which much of this chapter is based, and Feng-Li Lian for
his extensive research on NCSs.
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