Process heating is vital in hydrocarbon processing. While conventional methods involve burning fossil fuels, an increasing number of plants are transitioning to electric process heaters. One of the key advantages of this shift is the capability to achieve highly precise control over both the heating element surface temperature and the power consumption of the system. This level of control now extends to predictive control, made achievable through actionable insights derived from data. In this article, Chelsea Hogard, engineering team leader at thermal systems provider Watlow, explores the role that data plays in predictive maintenance.
Electrification
Process heating is a significant source of energy use and greenhouse gas emissions in the industrial sector, and so replacing fossil-fuel based heaters with electric ones running on green energy should yield significant progress towards decarbonisation goals. Adopting solutions for the first time will naturally bring about questions for process end user engineers regarding process variation, network loads, as well as component failure. Modern data collection technology, along with sophisticated data analysis, can monitor processes and allow these kinds of questions to be answered in real time.
Common challenges
Petrochemical refining operations often use heat exchangers in processes that are conducive to coking and fouling. Fouled heaters can contaminate or disrupt processing, and must be cleaned and/ or replaced when issues arise.
Another challenge is that heater elements can occasionally fail. Continued failure of an element eventually leads to an inability to produce enough heat to reach the intended outlet temperature. This can cause further issues with the process in question, including incomplete processing, fouling or film boiling. Being able to detect when an element has failed can avoid more serious problems that lead to unscheduled maintenance.
The right data, in real time
Having accurate data concerning the operation and health of systems and components is crucial in reducing the risks associated with new technology. For example, identifying temperature fluctuations in a process can serve as an early indication of potential coking or fouling, which could lead to maintenance issues in the future. By enabling process end users to recognise patterns of drift that signal impending problems, unplanned downtime can be averted through timely planned maintenance cycles.
Watlow’s new WATCONNECT panels, integrated with Data Insights, continually gather a wide range of data including system power, process values, set points, panel environment and wiring terminal temperatures. This comprehensive data allows the panel to perform the following key functions. This includes monitoring power and temperature controller health to prevent unplanned downtime to enable maintenance, detecting failed elements, facilitating pre-ordering of replacements and scheduling maintenance activities. Additionally, Data Insights also enhances system reliability and prompts maintenance activities to avoid unplanned downtime, while monitoring panel environmental data and providing alerts for changes in environmental conditions that could lead to system failure.
These panels afford an integrated solution that includes heaters, sensors, temperature controllers and power controller products, all in a complete thermal loop solution. The WATCONNECT L and XL sizes are particularly suitable for large industrial applications, specifically in the petrochemical industry.
Implementing predictive control in process heating can effectively address common challenges in petrochemical processing such as coking and fouling, heater failure and the gradual pace of electrification. This approach necessitates the integration of cutting-edge technology, alongside expertise in thermal systems and data analysis. When both elements are combined, they facilitate the development of environmentally friendly and more efficient systems and processes.
To learn more about WATCONNECT integrated with Data Insights, visit watlow.com
