Everybody believes in predictive maintenance, but most of us are reluctant to spend money on repair bills before we absolutely have to. Not surprisingly, many things break before they should get fixed.
Engineers at SKF want to change that mindset, and plan to do it by leveraging nearly 100 years of operating data gleaned from hundreds of thousands of machines in the field. These machines share a common element in that they employ bearings from SKF, which claims a 20% market share of the worldwide bearings market. Add in data obtained from modern equipment monitoring systems, and product design engineers could stand to gain a better understanding of the failure modes of machines than they have in the past.
"It's all about identifying when a failure is about to occur, that point right before the knee in the curve," says Eric Huston, vice president of Technology Ventures for SKF Service.
For the past two years, Huston has been involved with SKF's Reliability Systems Unit in the development of a decision support system called @ptitude. It harnesses both real-time machine condition monitoring and historical data to link the world of failure modes to how the parts of a machine are assembled and how they could potentially fail in service.
Avoiding machine downtime and premature maintenance costs are two obvious benefits, but Huston says that a major strength of @ptitude is the ability to extend its intelligence across the entire design process.
"By feeding this information to a design engineer, he or she can focus on those key elements that have the largest impact on life cycle costs and thereby increase machine reliability," says Huston.
Knowledge-based systems are nothing new. But Heinz Bloch, a consulting engineer with expertise in machine reliability improvement, says that SKF takes things a step further. "In early efforts with knowledge-based systems, engineers were supposed to sit behind a keyboard and input all the data they knew about something like a leaking seal, for example. But the engineer often didn't have the data necessary to answer all the questions," says Bloch. "So the system would then come up with some ridiculous conclusion like, "You have a seal problem."
SKF introduced @ptitude earlier this year at a press event at its headquarters in Sweden. In tandem, SKF launched the official @ptitude website, www.aptitudeXchange.com, which includes a host of interactive services. The subscription-based website features an interactive decision-support tool, articles on machine reliability and maintenace, best practice information, and benchmarking data.
Currently, SKF is in the process of introducing the product to customers here in the U.S. Gene Sabini, director of research at Gould Pumps, a maker of fluid power products for the process and chemical industries, says that his company plans to roll @ptitude out to its field service engineers. "Knowing how and when components have failed in service is a powerful tool that will enhance both our maintenance and engineering efforts," he adds.
For more information on knowledge-based systems from SKF, enter 535 at www.designnews.com/info.