Case Study: How Digital Transformation Paved the Way for One Refinery's Predictive Maintenance Strategy

Abstract

Abstract Across the energy industry, leading companies are eager to embrace digital innovation and all the predictive benefits it offers. Yet some of the largest companies still rely on sporadic, manual inspections to ensure the smooth operation of their machinery, equipment, instrumentation and systems. One international oil and gas company realized even the most skilled plant technicians could miss certain warning signals. If equipment like heat exchangers, pumps or critical valves are checked only periodically, manufacturers can risk equipment failure, outages or worse — health and safety incidents. Thanks to advancements in the quality and affordability of sensors as well as wireless technologies and cloud-based applications to gather and analyze data being streamed from devices in the field, companies like this one can gain better insights from equipment and take proactive measures to prevent failures and plant shutdowns. Methods, Procedures, Process The company worked with third-party technology vendors to implement a predictive reliability and maintenance program that will save millions of dollars a year in operational costs by instrumenting and monitoring heat exchangers in one of the company's refineries. The program is designed to digitally transform the company's heat exchanger maintenance activities and free refinery personnel from laborious manual monitoring, enabling them to focus on other functions and operational needs. A typical refinery will have 200-400 heat exchangers, the majority of which are manually monitored, with months passing between inspections. If undetected, heat exchanger fouling can cause degraded performance, reduced energy efficiency, process slowdowns and unscheduled shutdowns. Installation of more sensors to drive plant monitoring applications is an option, but the cost and disruption of installing new, conventional wired temperature sensors to an existing facility is prohibitive. One of the vendors developed and installed unique cost-effective sensors to provide accurate measurements from the refinery's heat exchangers without thermowell process penetration. These sensors allow for remote monitoring of heat exchanger data in real time. As part of the ongoing program, the data is transmitted through a secure, wireless architecture and transferred to the cloud using cloud-computing technologies. Using advanced analytics, the data is then interpreted to provide plant personnel with actionable data to optimize operational performance. Results, Observations, Conclusion There have been significant savings in sensor installation (a fraction of the cost of conventional sensors) and commissioning time (one week versus the typical six weeks). The plant has also seen savings in staff time. The company can detect small variations well before any fouling issues start. The program is proving that, by understanding the health of the heat exchangers, the company can help prevent unplanned outages and reduce the number of scheduled repairs. Facilities can reduce energy and capacity loss due to fouling by up to 10 percent. For a 250,000-barrel-a-day refinery, that could translate to a savings of as much as $3.5 million or more annually. Wireless sensors and secure, cloud-based condition monitoring can be expanded to other equipment, such as pumps and cooling towers throughout the plant. Ultimately, these predictive maintenance programs will improve and transform operations, and the data analytics and insights will accelerate business decisions. Cloud-based hosting of these monitoring systems allow monitoring by any personnel, anywhere, including the option of having a third-party vendor provide the service.