As processors and storage become cheaper and more efficient, more and more companies want to analyze increasing amounts of data and use artificial intelligence to support Risk Based Decision Making; and refineries are no different.
Predictive Maintenance offers refineries an opportunity to determine the current condition of equipment to predict when a failure will occur. This gives refineries a potential to reduce Operating Expenses by performing preventative maintenance only when it is warranted and by reducing the costs associated with Reactive Maintenance. Predictive Maintenance programs are high CAPEX and, unfortunately, most refineries do not have adequate processes and quality data available to make this transition worthwhile. Trindent provides refineries with low to no CAPEX solutions that build the fundamentals required to make the first step towards Predictive Maintenance.
Foundations for Success
Before a refinery can implement a holistic Predictive Maintenance program, they first need to establish a pilot program. Creating the right foundation allows the refinery to plan for success and implement a program using data-driven decision making to determine where the initiative will have the most impact. Proper foundations also allow for improved refinery operations and a reduction in Operating Expenses in the interim.
- Proper Preventative Maintenance: Preventative maintenance reduces the likelihood of equipment failure by performing routine checks or interventions on the equipment. A proper maintenance program will occur frequently enough to detect failures but not be unnecessarily burdensome to maintenance personnel. As part of this, it’s important to understand correct Preventative Maintenance tasks, durations, and crafts people allow for refinery management to focus predictive maintenance efforts on the equipment that cost the most to maintain. Without proper Preventative Maintenance tasks in place, there will be inadequate follow-up action from predictive maintenance findings.
- Data Quality – During the work management process there are many opportunities to collect the right data; however, refineries often lack the processes and training to collect data that is sufficiently detailed. Improving maintenance programs for instruments and sensors allows the refinery to identify whether the quality of the data is adequate or if the right sensors are even in place. Better data quality allows for management to focus predictive maintenance efforts on specific failures that result in process interruptions. Furthermore, the use of Defect Elimination programs can give the refinery insights into the conditions that cause failure, allowing for a more effective predictive maintenance program.
- Culture – Without building a proactive culture, a predictive maintenance program is destined to be an expensive, but short-lived endeavor. Establishing the right training, tools, dashboards, and communication methodologies allows for results to be sustained. Once the refinery has shifted from a reactive to a proactive culture then the predictive maintenance program can be successful.
At Trindent, we focus on tangible results and showing improvement through data. This data-driven approach links our results to financial or other key performance indicators. In addition, we make sustainability a key part of each engagement, and train your employees to sustain results.
The author of this article – James Greey is a Senior Consultant at Trindent. To learn more about how Trindent can Make it Happen™ in your company, reach out to our team on LinkedIn or through our Contact Us page.