In industrial settings, using modern technology, machinery, and integrated systems to their maximum potential often depends on well-designed automation software. As tech-nologies continually develop and evolve, practicing engineers and academic researchers must continually develop the software to run these technologies. Modern Industrial Automation Software Design offers readers the critical tools needed to create software that meets today's dynamic industrial challenges.
This up-to-date resource first lays out the knowledge base that allows purposeful and disciplined automation software development. Then, moving from general knowledge to its specific use, the authors discuss five typical applications in real-world industrial automation software design. These include:
- An object-oriented reconfigurable software design
- A flexible measurement point management system
- An automatic blending system using multithreaded programming
- A flexible automatic test system for rotating turbine machinery
- An Internet-based online real-time condition monitoring system
Using this practical, hands-on approach, Modern Industrial Automation Software Design covers important new software innovations, such as:
Modern software engineering * Object-oriented methodology * Visual/graphical programming platforms * Graphical user interfaces * Virtual instrumentation * Component-based systems * Systematic database management * Dynamic data exchange * Software performance testing
Modern Industrial Automation Software Design brings together multiple disciplines into a cutting-edge reference suitable not only for students and practitioners of industrial measurement and control, but also for the general reader interested in new prospects for industrial production and management.
About the Author
L. F. Wang received his B.Eng degree in measurement and instrumentation from Zhejiang University, China in 1997, a M.Eng degree in instrumentation science and engineering from Zhejiang University, China in 2000, and a M.Eng degree in electrical and computer engineering from National University of Singapore, Singapore in 2002. Currently he is a researcher in the Electrical and Computer Engineering Department at the University of Virginia, U.S.A. He has published over 40 technical papers in the fields of industrial measurement, testing, and supervision, fault-tolerant control, and autonomous agents.
K. C. Tan received the B.Eng. degree with first class honors in electronics and electrical engineering and the Ph.D. degree from the University of Glasgow, Glasgow, Scotland, in 1994 and 1997, respectively. He was with the Center for Systems & Control and the Evolutionary Computing Group, Glasgow, Scotland, before joining the Department of Electrical and Computer Engineering, National University of Singapore, as an Assistant Professor in 1997.
