The Nature of Predictive Maintenance
Global interest in Predictive Maintenance technologies is on the rise, owing to its immense potential for Industry 4.0. Benefits such as reduction in costs and time while predicting future failures that might occur are readily evidenced. It owes its existence to the advent of Internet of Thing (IoT) devices and platforms, and advanced analytics.
With the current industrial scenario being extremely competitive, organizations are aiming to reduce the operational costs and improve processes to help achieve competitive advantage. Predictive Maintenance increases product quality by iteratively using the insights gained by analytics in the design phase. Further benefits observed include higher machine availability, a better understanding of product operation, and influence of external factors.
As with every other modern technology, Predictive Maintenance also holds its disadvantages such as lack of training for operators, data volume and security issues and reduced awareness of top providers.
The study titled “Customers’ Voice: Predictive Maintenance in Manufacturing, Western Europe”, was commissioned by Frenus, in partnership with T-Systems to help bridge the lack of information clarity between providers and the industry. It provides a comprehensive overview regarding the adoption and future potential of Predictive Maintenance technologies based on insights from the customers’ standpoint. It consists of consolidated insights from more than 300 interviews with industry experts in Western Europe.
Predictive Maintenance primarily consists of 5 different individual key components, similar to a classical IoT value chain: sensors, gateways, connectivity, IoT platforms, and analytics solutions. IoT sensors and devices are installed on machines for monitoring and data collection, gateways help pre-process and transmit the collected data via an appropriate connectivity technology to an IoT platform. IoT platforms function as intelligent data aggregators. Analytics solutions are deployed on the IoT platforms to help analyze patterns or anomalies in historical and real-time datasets. Identification of asset failure and key predictors of impending failures constitute some of the important insights desired.
In addition to the explanation regarding the technicalities of Predictive Maintenance, Customers’ Voice provides the reader with high-quality information gathered over the span of 250 hours of professional interviews with mid and top management level experts within large companies, one-third with a revenue above EUR 1 bn.
Frenus will have its own stand in the Digital Factory hall at the Hannover Messe 2018. Visit us in Hall 7 Stand E13 between the 23rd and 27th of April for further discussions regarding the topic over a warm cup of coffee.