Why Do Predictive Maintenance Programs Fail?
by Alan Friedman In the past few years we have witnessed a marked change in predictive maintenance (PdM) practices whereby more and more companies are choosing to outsource their programs. While many facilities routinely calculate 20:1 return on investment metrics, others cynically refer to aging data collectors as “dust collectors” or use them as bookends. Although the concept of PdM is now widely known, and its potential benefits generally accepted, many plants have failed to successfully exploit the available techniques and technologies in practice. This state of affairs begs the question: “Why do some programs succeed while others fail?” As we enter a recession and maintenance staffs are cut, we will once again be asked to do more with less. This means that now we need to think about how we conduct maintenance and determine how to do it more efficiently and intelligently in the future whether that is through new internal processes or outside help. As we rise to meet the challenges
