Germano Lambert-Torres

Gnarus Institute, Brazil

Germano Lambert-Torres received his Ph.D. in Electrical Engineering from the École Polytechnique de Montreal, Canada, in 1990. Currently, he is the director of research and development at PS Solutions and a member of the Scientific-Technical Council at Gnarus Institute, Brazil. Dr. Lambert-Torres has led research in intelligent systems, management of maintenance, and power system operation for many power industries in Brazil and South America. He has also taught seminars and short courses in many countries worldwide at the Institute of Electrical and Electronics Engineers (IEEE), International Council on Large Electric Systems (CIGRÉ), and International Federation of Automatic Control(IFAC) conferences, universities, and research centers. He has supervised more than 120 MSc and Ph.D. theses and published more than 700 journal and technical conference papers. He is also the author/editor of ten books. Dr. Lambert-Torres is a fellow of the IEEE.

Germano Lambert-Torres

1books edited

6chapters authored

Latest work with IntechOpen by Germano Lambert-Torres

The management of maintenance processes and their integration with production processes is one of the significant challenges faced by industries today. It is known that maintenance must be carried out to guarantee the quality and continuity of production processes. Thus, manufacturing routines, production bottlenecks, and the criticality of each component or subsystem in the overall process should be considered not only by production management but also (and increasingly) by maintenance management. The latter should consider repair (or replacement) costs and miscellaneous expenses, plan to work on maintenance effectively, reduce repair times, and establish clear repair procedures and instructions. Maintenance process management can be deployed in several ways and following several strategies depending on the type of industry, its size, and the criticality of its processes. However, even being a unique company, it is always possible to take advantage of the experiences of other industries and their implementations. The advent of new technologies (such as automation, the Internet of Things, and cloud computing), along with new statistical and artificial intelligence techniques, has created an environment referred to as Industry 4.0, of which maintenance management systems are a part. This book presents aspects of predictive maintenance in industries and shows the possibility of reaching the creation of prognostic maintenance. It offers techniques for managing maintenance processes theoretically and practically as examples of possible industrial implementations.

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