SMART DECISION SUPPORT TOOLS FOR ROBOTICS AND AUTOMATION SYSTEMS

For decades, companies have been trying to develop and deploy predictive maintenance and prognostics technologies with ad hoc and trial-and-error approaches. These efforts have resulted in limited success, due to the fact that it lacks a systematic approach in deploying the right prognostics tools for the right applications. The presentation will introduce the intelligent maintenance systems methodology as well as advanced decision support tools for product life cycle management and maintenance scheduling. Special emphasis on the use of toolbox of prognostics algorithms to convert machine condition data to useful information for real-time decision making and closed-loop product life cycle system will be examined. A number of case studies will be used to demonstrate the lessons learned from industry testbeds, including Toyota, GM, Komatsu, P&G, GE Aviation, etc. In addition, trends on service design using Dominant Innovation tools will be presented with case studies.