The idea of a smarter world where systems with sensors and local processing are connected to share information is taking hold in every industry. In oil and gas, this idea has many names — from the Digital Oilfield to preventive maintenance and condition monitoring to the Industrial Internet of Things. The ideas are the same and offer distributed connectivity, intelligence, and analytics to improve efficiency. Taking this approach to a maintenance strategy is one of the most prominent implementations today.
Many costs, including capital expenditures, unplanned purchases, and operational costs, are associated with maintaining equipment. However, these pale in comparison to the true loss of a machine going down, which may result in a significant shortfall in production. In the oil and gas industry, equipment uptime is directly correlated to the company’s bottom line. For example, when drilling stops at a well site, virtually all cash flow associated with the well stops. This is further compounded when you consider operational costs for fracturing crews on-site. At risk is not only money, but also jobs and reputations. A new, more efficient maintenance strategy is needed to go beyond the typical preventive maintenance and condition monitoring strategy.
The need for change is necessitated by the amount of money wasted on preventive maintenance. According to Forbes Magazine “one out of every three dollars spent on preventive maintenance is wasted.”
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The Electric Power Research Institute (EPRI) also found similar results. By comparing maintenance costs for different maintenance techniques, researchers found that a scheduled (or preventive) maintenance strategy is the most expensive to run. The following list provides three key steps for implementing and improving predictive maintenance programs.
1. Gain Insight Through Vibration Monitoring—To improve the efficiency of the machine, you must first gain insight into its health through vibration monitoring. Through proper analysis, vibration monitoring can serve as a core element to a predictive maintenance strategy and offer many advantages. For example, in the EPRI study mentioned above, researchers found that this new option costs about a third per HP, and all but eliminates the risks of secondary damage from catastrophic failures. Operators can predict when equipment is going to fail, schedule maintenance without affecting production, and ultimately extend the life of the machine.
2. Go Beyond Vibration Analysis—Vibration analysis measurements act as leading indicators of health, but they are not the only ones. Measurements like temperature, strain, power quality, pressure, and deflection also give insight into the health of the machine and, when combined, can paint a much clearer picture. These measurements are typically parts of the second phase of condition monitoring; however, if not planned for upfront, can become difficult and expensive to add later. Through proper planning, companies can avoid this mistake by taking an integrated platform-based approach that is flexible enough to adapt to changing requirements.
3. Complete the Solution by Integrating with Control—The final step to regain control of your assets is to completely integrate this monitoring solution with your control platform. By choosing a flexible platform in Step 1, you can use all of the elements you measure in Steps 1 and 2 to adjust the control algorithms in real time, based on the operating conditions to improve efficiency and extend the life of the equipment. In addition, operators need to learn only one system, further improving operational efficiency.
Brian Phillippi is a product marketing manager for the Embedded Control and Monitoring team at NI (ni.com/mcm), Brian Phillippi helps manage the I/O modules for the company’s industrial, embedded and data acquisition platforms.