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Azima DLI, the leader and premier provider of predictive machine condition monitoring and analysis services, on April 1 announced the results of a survey aimed at gaining insight into the state of predictive maintenance and condition monitoring programs among U.S. plants. Overall findings show that while a majority (76 percent) of respondents is satisfied with current programs, more than half of those surveyed agree that it’s difficult to know exactly what solutions and tools are needed to maintain a successful program. Combined with insufficient staff, limited in-house expertise and poor training as the top factors negatively impacting results, plants must re-examine existing programs now in order to ensure sustainability and the ability to meet long-term productivity and reliability goals.
The findings of Azima DLI’s inaugural “State of the Condition Monitoring Industry” report are based on a survey conducted among engineers and plant managers. Of those surveyed, 65 percent have a machine condition monitoring/predictive maintenance program in place. The top three components of those programs are vibration analysis/monitoring, lube oil analysis and thermography. Of those who don’t currently have a program in place, 16 percent plan to start one this year.
Reaching the C-Suite
While the majority of respondents agree that predictive maintenance programs directly impact the bottom line, when queried about barriers to success, difficulty demonstrating ROI was one of the top factors. This could be directly related to other issues such as insufficient staff and limited budget support, but nonetheless, ROI remains an important measure of program traction that resonates with the C-suite. Therefore, plants must adopt the right technology and partner services to enable managers to better capture and report the benefits of condition monitoring programs, focusing on metrics such as decreased downtime, improved productivity, and cost savings related to improved equipment health and reliability.
Outsourcing Predicted to Rise
For those with a condition monitoring/predictive maintenance program in place, just over half of the respondents use a combination of in-house and outsourced solutions. While only 8 percent currently outsourcing data collection and analysis, based on this survey, outsourcing may be on the rise. Of those handling programs in-house, 53 percent responded that they believe there are benefits to outsourcing the program.
In considering a partner for third-party support, the following factors were ranked, in order of importance, as most influential in making that decision:
“While the benefits of an effective condition monitoring and predictive maintenance program are clear to plant personnel and management, many programs have been left on auto-pilot during tight economic times,” said Burt Hurlock, CEO, Azima DLI. “We believe one of the keys to long-term success is greater visibility among the C-suite regarding the quantifiable impact these programs can have on productivity and plants’ ability to comply with important industry standards for reliability. For example, by investing in cost-effective data collection analysis capabilities, plants can make informed maintenance decisions and generate results in terms of cost-avoidance related to unscheduled downtime and unnecessary repairs.”
About Azima DLI
Azima DLI is the leader and premier provider of predictive machine condition monitoring and analysis services that align with customers’ high standards for reliability, availability and uptime. Azima DLI’s WATCHMAN Reliability Services utilize flexible deployment models, proven diagnostic software and unmatched analytical expertise to deliver sustainable, scalable and cost-effective condition-based maintenance programs. The company’s bundled solutions enable customers to choose comprehensive, proven programs that ensure asset availability and maximize productivity. Azima DLI is headquartered in Woburn, Mass., with offices across the U.S. and international representation in Asia-Pacific, Central America, Europe and South America.