Predictive Maintenance aims to revolutionize the manufacturing industry by leveraging key manufacturing process data to make proactive decisions rather than reactive decisions related to key processes.

Whether your organization is discarding significant chunks of critical data or is unable to assess the significance of data that they house in repositories, predictive maintenance may provide the needed enhancement to an existing manufacturing strategy to leverage critical data and use it to limit challenges that stifle critical business processes.

Predictive Maintenance: A Brief Introduction

Anyone who belongs to or hails from a manufacturing ecosystem will always vouch that there isn’t a single day in this field that doesn’t witness failures and breakdowns. As a field that deals exclusively with equipment and machinery programmed to carry out a repetitive task, the malfunction’s scope is inevitable. Thus, most manufacturing industries’ objective is not to eliminate this margin of error but to instead minimize it to such an extent that it helps them achieve high-efficiency standards and deliver quality products in the process.

Thanks to the rapid evolution of science and technology, companies no longer need to rely on rudimentary techniques such as importing data to spreadsheets and analyzing insights manually to track their operations’ progress. With the rise of tools such as the Internet of Things and Big Data, organizations now have the ability to leverage machine data to limit the costs and impacts of the odd downtime, irrespective of whether it is planned or unplanned. This protocol of crisis management is, in a nutshell, referred to as predictive maintenance.