The quest for zero downtime

Intelligent sensor networks could let production equipment notice maintenance problems before they happen. A Watchdog Agent today physically takes the form of a computer platform that installs on a machine or process or interest. IMS Center researchers set it up to run algorithms from its toolbox that gauge the health of the machine, monitor degradation, and predict when service will become necessary. In one test bed, IMS Center researchers installed the Watchdog Agent on a Grob Inc. aluminum-cutting machine at Harley-Davidson. The Watchdog Agent automatically converted sensor data to health information and predicted how the machine operation would degrade. Imagine a machine that can tell you its current state of health — whether key parts are about to fail, whether it needs lubrication, and so forth. Further imagine the machine can tell you the degree to which its operations are likely to deviate from the norm in the near future, though it is producing in-spec parts today. Of course, a machine with this level of intelligence could truly change a product's life cycle for the better. Moreover, the ability of machines to assess themselves could raise the field of maintenance to more than a low-level topic of study. Machine self-assessment could winnow whole industries away from a reliance on predetermined intervals of preventative maintenance: Checking performance, replacing parts, and lubricating on a set schedule whether there's a true need for these activities or not. Is there a realistic alternative for scheduled maintenance? This is the question that drives the National Science Foundation Industry/University Cooperative Research Center for Intelligent Maintenance Systems (IMS). Over the last six years, IMS Center researchers developed a toolbox of algorithms, collectively dubbed the Watchdog Agent, capable of converting sensor data and operating conditions to useful information. This information is indicative of a machine's level of performance and