Predictive Maintenance Leads to Higher Production Output and Lower Maintenance Costs: New Resource From Info-Tech Research Group

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Oct 04, 2023, 12:00 ET

In a newly published resource, the global IT research and advisory firm explains that predictive maintenance can help organizations make the most of their data to increase production operations' uptime, improve safety, reduce maintenance costs, and identify hazardous situations before they occur.

TORONTO, Oct. 4, 2023 /PRNewswire/ - As production operations continue to grapple with the need to streamline processes and reduce overhead costs amid economic uncertainty, an increased need for transparency and predictability surrounding maintenance management has become evident. Info-Tech Research Group has published new research, Operational Efficiency Through Predictive Maintenance, to provide support and guidance for the industry. As many operations organizations lack visibility throughout the production process, there is a demand for the enablement of better technology support to reduce downtime, avoid run-to-failure, and mitigate the ripple effects of catastrophic outages when equipment or assets go down. The firm's resource will support operations leaders in their endeavors to improve maintenance planning.

Info-Tech Research Group’s Future of Maintenance and Maturity Model acknowledges a variety of maintenance approaches, all of which play a role as we evolve to predictive maintenance and beyond, including prescriptive maintenance, predictive maintenance, condition-based maintenance, preventive maintenance, and reactive maintenance. The important challenge is deciding on which method to use and at which point in time. No single method is right for all situations. (CNW Group/Info-Tech Research Group)

"Predictive maintenance is a powerful addition to a thorough, all-encompassing strategic plant maintenance program," says Kevin Tucker, principal research director of manufacturing research at Info-Tech Research Group. "It is revolutionizing maintenance by avoiding unexpected and catastrophic failures that impair productivity, lower customer satisfaction, and drive up costs for services such as repairs and quality problems."

The new resource explains that predictive maintenance uses data analysis tools and procedures to enable proactive management of technology, foreseeing issues before they arise. Enabling this maintenance management method also prevents unscheduled reactive maintenance and incurring costs for excessive amounts of preventive maintenance.

Info-Tech provides a breakdown of the tools to employ in the data collection and analytics of predictive maintenance in the resource, highlighting that the key to success lies within using the right tools to capture the correct real-time conditions and provide predictive monitoring data. The suggested tools are outlined below:

Infrared thermography includes cameras that detect heat spots and provide a thermal image warning.
Acoustic monitoring uses sonic and ultrasonic levels of monitoring for sounds of liquid and air leaks.
Motor condition relies on real-time early condition monitoring for defects.
Eddy inductive current condition involves monitoring for eddy currents in conductors, which cannot be touched. Monitoring must be precise because the current may be moving at a rapid pace.
Vibration analysis offers pattern readings that can signify early onset imbalances.
Temperature monitoring refers to holistic tolerance-based temperature management.
Oil and grease analysis monitors for viscosity and foreign contaminants as well as leaks.
Internet of things (IoT), extended internet of things (xIoT), industrial internet of things (IIoT), and supervisory control and data acquisition (SCADA) are systems that provide data from a wide variety of proprietary meters.
Computerized maintenance management systems (CMMs) are used to track and service assets.

As operations organizations work to make the most of their data to increase production operations' uptime, reduce maintenance costs, and identify hazardous situations before they occur, Info-Tech advises operations leaders that the more established and historical maintenance management techniques cannot be replaced by predictive maintenance in all situations. While conventional run-to-failure and preventive programs must still be used in some capacity, the firm's research shows that the implementation of predictive maintenance alongside IIoT will help organizations optimize their data to provide a host of organizational benefits, including saving both time and money, increased safety, and improved workflows.

To access the full resource, including a variety of case studies, download Operational Efficiency Through Predictive Maintenance.

For media inquiries on the topic or to get exclusive, timely commentary from Info-Tech analysts, please contact PR manager Sufyan Al-Hassan at [email protected].

For information about Info-Tech Research Group or to access the latest research, visit infotech.com and connect via LinkedIn and X.

About Info-Tech Research Group

Info-Tech Research Group is one of the world's leading information technology research and advisory firms, proudly serving over 30,000 IT professionals. The company produces unbiased and highly relevant research to help CIOs and IT leaders make strategic, timely, and well-informed decisions. For 25 years, Info-Tech has partnered closely with IT teams to provide them with everything they need, from actionable tools to analyst guidance, ensuring they deliver measurable results for their organizations.

Media professionals can register for unrestricted access to research across IT, HR, and software and over 200 IT and industry analysts through the firm's Media Insiders program. To gain access, contact [email protected].

SOURCE Info-Tech Research Group