5 Common Obstacles to Condition Monitoring & Predictive Maintenance Success

There are a few common obstacles, that if directly addressed, can help organizations move forward successfully with their condition monitoring and predictive maintenance systems.


When it comes to condition monitoring and predictive maintenance, there are a few common pitfalls. National Instruments has compiled a list of five obstacles, that if directly addressed, can help organizations move forward successfully with their condition monitoring and predictive maintenance systems.

1. Lack of Vibration Analysis Know-How—Lack of training in vibration analysis for operations, maintenance operators and technicians. Technicians need training to be able to consistently diagnose the condition of equipment based on their individual experience.

2. Not Analyzing Data—Organizations are capturing the data, but no one is looking at the data. In “Q&A: Next Steps in Condition Monitoring” we highlighted the transition from paper readings to handheld electronic devices. In one case NI has seen maintenance personnel collecting up to 60,000 measurements per month, leaving approximately 20 percent of their time left to analyze data. We expect this means that most operators’ time is spent walking throughout a plant collecting data. For a highly experienced operator, industrial organizations would prefer to reverse the 80/20 rule to ensure an operator is spending the majority of their time focused on high-value tasks like analyzing the data to bring business insights back to the organization. Consistently reviewing and analyzing data is critical to a condition monitoring program’s long-term success.

3. Not Acting on Data—Organizations review the data, but no one is acting on the data. An installed condition monitoring system is of little value if operations and maintenance personnel are not identifying and eliminating future trouble spots.

4. Lack of Commitment to Predictive Maintenance—Whether this stems from management or technicians doing the work, a commitment to a predictive maintenance approach must be ingrained into the fabric of the organization.

5. Lack of Standardization—Often plants adopt tools that are tied to equipment, so O&M Management needs platforms to solve three key challenges:

a. Integrating technology that is independent of equipment and capable of integrating with legacy equipment
b. Bridging technology to internal IT infrastructures to enable real-time decision making across the enterprise
c. Connecting disparate technologies in a plant to provide visibility beyond critical assets.

Kamalina Srikant is responsible for product management and market development for Condition Monitoring Solutions at National Instruments (NI). Ms. Srikant’s work experience extends to the energy, Big Data, consumer goods, and machine vision markets. She holds a bachelor’s degree in mechanical engineering from McGill University in Montreal, Canada.

Theresa Woodiel plays a lead role in advancing the reputation of National Instruments (NI) embedded systems platform and trends within the industry. She holds a master’s degree in technology commercialization from The University of Texas McCombs School of Business.


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