Increasing Asset Reliability for Sustainability

At the 2023 Emerson Exchange Immerse Conference, Emerson’s Manuel Arroyo presented, The Path to Net Zero Based on Asset Reliability. Here is the presentation abstract:

The transition to a net-zero carbon future requires a comprehensive strategy that includes not only decarbonizing energy sources but also ensuring the reliability of the infrastructure that delivers that energy. The concept of asset reliability provides a framework for achieving this goal by maximizing the uptime and efficiency of energy assets while minimizing downtime and repair costs. The path to net zero based on asset reliability involves a holistic approach that considers the entire lifecycle of an asset, from design to decommissioning. This requires a shift towards a data-driven, predictive maintenance approach that leverages advanced technologies such as machine learning and artificial intelligence.

Manuel opened by showing a possible path to Net Zero.

Large investments need to happen in renewable power sources, electrification, and increased operational efficiency. Today, the manufacturing energy and carbon footprint is 4,519 TBTU and 275 MMTCO2e. The challenge is to maintain profitability on the path to more sustainable operations. Digitalization is required as a foundation. Data only is no guarantee of hitting sustainability targets. Improved process design, optimization and ongoing monitoring to approach targets.

Some common sustainability challenges include excess energy consumption, process fouling, scrap or rework with off-spec production, and margin losses from lower-grade production. The amount of data available and the combination of contributing factors makes traditional analysis impossible for highly complex process issues, especially without data science expertise.

Identifying and addressing reliability issues with process equipment saves costs, production efficiency, and quality. Here is a look at the impact of reliability on emissions.

Monitoring assets to enable early identification of issues improves overall reliability and reduces emissions. Ongoing alerts and guidance help to maintain product/process health and correct issues. While all the assets are performing well, monitoring data is collected to establish a multi-variate baseline of operation. Changes in the flow of this monitoring data combined with a production decrease indicate a possible problem with an asset. If the issue is addressed in this timeframe, excessive component wear and unplanned downtime can be avoided.

Manuel shared some examples to drive sustainability improvements. Aspen ProMV analyzes and correlates what operating conditions on an ethylene furnace minimize energy consumption. This real-time monitoring solution maintains efficiency, and deviations are corrected rapidly upon an alert.

Another example is to reduce propane flare events due to pressurization from an unknown cause. The debutanizer production was lost to the flare system. ProMV analysis by the process engineering group identifies optimization opportunities. They created real-time alerts indicating when process changes are required. With these actions, propane losses were reduced by $1 million annually.

Another example was to determine the optimal balance between steam needs and electricity imports and exports while minimizing capital costs. Using Fidelis simulations, each case explored gas turbine, boiler, and steam turbine combinations. It assesses scenarios using Monte Carlo simulations, including energy penalties, emergency discharge, maintenance expenses, and production levels. Using this analysis, the team met their objective for a powerhouse revamp design to optimize steam needs and electricity import and export.

Visit the Reliability Solutions section on for more on ways to improve reliability and drive more sustainable operations.

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