Dec-2024

Digitalisation solution for monitoring and improving performance

Development of a collaborative platform for monitoring, enhancing decision-making, and improving operational efficiency within various aspects of plant operations.

Pierre-Yves Le-Goff, Philippe Mege, Yannick Gelie, Marie Duverne and Connor Knight
Axens

Article Summary

Refining and petrochemical industries are facing several complex challenges related to operational performance imperatives, environmental standards, and skills shortages. Increased data volumes offer one lever for responding to these issues by enabling insights based on key performance indicators (KPIs), but too much data also carries its own analytical difficulties.

Harnessing the power of data: Data has long played a pivotal operational role in many businesses, and petrochemical and refining industries are no exception. Numerous sensors measure and monitor a wide range of parameters, from pressure and temperature to the content of various compounds. This has produced an abundance of data that exceeds the analytical capacity of most industrial companies. In this context, new technologies based on artificial intelligence (AI) and machine learning (ML) are poised to revolutionise the way companies utilise the growing wealth of data at their disposal while simultaneously transforming what data can do for these companies.

Within the ever-evolving landscape of business and technology, industrial companies are now expecting numerous benefits from digital transformation. Indeed, the real-time business management enabled by advanced data analytics will unlock a host of operational efficiencies, improved safety and sustainability (for example, through lower CO₂ emissions and the maximum usage of catalysts), as well as profitability through operational guidance.

Transforming operations
In petrochemical and refinery complexes, process licensors and catalyst suppliers play a key role in accompanying this transformation. They provide digital tools that complement their proprietary technologies while also implementing new features such as diagnostics and alerts, predictive functions, and improvement suggestions.

While data flows certainly facilitate problem identification and diagnosis, they can also represent an additional source of errors, as more data often results in more noise. Specifically, data cleansing and treatment are the first steps to ensure the reliability and accuracy of KPI calculation in addition to model building.

Thus, verification and correction methodologies have been developed, including algorithms for a better and more accurate closing of mass balance and principal component analysis to check data consistency. These tools ensure the relevance and quality of data, resulting in more pertinent recommendations.

Petrochemical and refining industry challenges
The oil and gas industry is facing a problem of skills loss. This is due to both a high number of retirements and the difficulty of attracting young engineers and data scientists, which can result in lower levels of productivity and efficiency.

The economic stakes of this situation are considerable: performance gaps and non-compliance with regulatory standards have the potential to disqualify part of a production from a sale, leading to earnings losses. Inefficiency can also have significant environmental impacts, notably through excessive consumption of resources or unnecessary greenhouse gas (GHG) emissions.

For this reason, oil and gas industries at large will need to identify and implement solutions for eliminating inefficiencies, even within a tightening labour context.

Digitalisation solutions can help overcome this challenge, not only by automating certain efficiency operations but also by improving the technological appeal of these professions for young engineers and data scientists.

Digital solution benefits
By integrating real-time data display and operating status viewgraphs for individual units or entire complexes, the technology provider is in an ideal position to assist operators in maximising the efficiency of their processes, which benefits users and technology providers alike. The Group does this through its digital offer, known as Connect’In.

Technology experts, technical services engineers, and data scientists work closely with end users to capture improvement opportunities via increased operational awareness. In concrete terms, Connect’In is a digital supervision tool and interface of exchange for all aspects of customer installations. It delivers real-time performance data for these installations, enabling Axens experts to:
- Identify any discrepancies between observed and expected performance
- Diagnose the causes of these discrepancies
- Propose corrective measures to customers.

This solution is designed for process engineers and operations managers, who have major responsibilities in terms of the continuity of operations, product quality, and productivity. The solution also simplifies the monitoring of all these parameters and gives team members the peace of mind of knowing that any performance deviation will be detected quickly and that they will receive corrective action from experts just as quickly.

Enabled by real-time secure data transfer and automated KPI calculations, technical service engineers remotely monitor unit performances via Connect’In and supply operational guidance to increase unit profitability. Using a combination of high-fidelity models and innovative ML techniques, teams convert data into timely operational recommendations to help customers achieve the best performance from their range of products.

Corrective measures can also be proposed continuously through the dedicated interface. For instance, for some units, the best set of operating conditions for a given performance target is continuously suggested to the customer. This is made possible using a hybrid model, which combines Axens’ high-fidelity first principle model with ML.

Collaboration is also key to achieving operational excellence in this area. Leveraging advances in web and data-sharing technologies, customers are provided with continuous and direct access to process expertise, catalyst and process know-how, and data analytics capabilities.

Benefits
Digital tools such as high-speed data networks, cloud-based systems, and advanced data techniques are rapidly changing how the refining industry monitors and optimises its operating assets. Refineries that adopt real-time unit monitoring tools, integrating on-demand, advanced modelling of process performance, immediately gain a competitive advantage.

By monitoring a core set of KPIs, Connect’In allows unit troubleshooting through the continuous comparison of actual and normalised performances, which are calculated based on reconciled data (see Figure 1) and Axens’ high-fidelity models. In addition to its advanced digitalisation efforts for increasing data quality and technical advice relevancies, catalyst usage and lifespans can be optimised, improving unit economics and, therefore, lowering the CO₂ emissions associated with catalyst manufacturing.