The primary purpose of Predictive Maintenance (PdM) is to enable more convenient scheduling of corrective maintenance and to prevent unexpected equipment failures. Knowing that up to 30% of failures occur after planned maintenance, how can you be confident that reinstating a machine or device is safe or improving efficiency? By using machine learning and comparing good signatures with after maintenance performance! With high degrees of confidence asset owners and operators can be extremely sure that going back online means reduced downtime and that they can sleep at night.
By creating and then intelligently processing empirical information about asset data performance, there are savings in terms of stock holding, resource planning, people, a reduced risk profile, capital deferment and operational cost reduction. There are many other benefits to shifting from planned/calendar based maintenance.