Amid rising demands for efficiency and sustainability, the integration of Artificial Intelligence (AI), Machine Learning (ML), and the Internet of Things (IoT) is proving to be a game-changer, driving unprecedented advancements in operational efficiencies and predictive maintenance. These technologies are the key to staying ahead, ensuring that petrochemical operations are not only efficient and reliable but also resilient and future-ready. 

In this context, the leading experts from petrochemical industry shared the latest trends at the second session of second edition of PetroChem Summit 2024 titled ‘Applications of AI, ML, and IoT for Improving Operational Efficiencies and Predictive Maintenance’ organized by the Indian Chemical News in New Delhi on December 18, 2024. 

Manish Grover, Former Executive Director (Strategic IS & IS), IOCL moderated the panel discussion. Outlining the importance of implementing smart technologies, Grover said, “As we navigate this industry 4.0, the petrochemical industry is uniquely positioned to harness the transformative power of AI, ML and IoT. These technologies are not only reshaping the traditional manufacturing paradigms but also setting new benchmarks for operational excellence, efficiency, and predictive maintenance; and safety and sustainability.” 

Vimal Goel, Head – IT, HPCL Mittal Energy Limited said, “It is sometimes hard for the IT person to convince the refineries and petrochemical engineers about the use of data and digital technologies as they are confident about the best outcomes from existing set up. You have to give them a use case to show that the output of the system is much better than what they have been doing earlier.

“For example, we have a CPP 165 megawatt captive power generation plant that runs on pet coke. There were problems. Every day there was a deviation of 6-7 times in the SOx levels. Using the classical AI-ML, we were able to develop a model which was able to predict 30 minutes in advance what is going to the SOx level. To control the Sulfur oxides (SOx) emission level, the operator uses the lime and accordingly adjusts the dosing of the lime. Since the operator might not have the permission, we created this application in a controlled loop. Depending on the reactivity and quality of lime, AI-ML adjusts the level of dosing. In this exercise, we solved the three problems.

“One is the conviction that it can solve the problem. Second is that the deviation in the SOx was zero, and third is that we optimized the lime and thus saved around Rs 20 crore. This is the power of data and the benefits it comes with. While the oil and gas industry has had the same set of products in the last 150 years, the petrochemical industry comparatively has a lot of complexities. There we are using the AI-ML to try to optimize the steam consumption.” 

Gaurav Vyas, Lead Strategy-Director’s office/AVP, RIL said, “Data was always there but now how we are harnessing the manufacturing data carries a strategic importance. Not only is this bringing agility in decision making but also a change in how we integrate the supply chain with manufacturing. It also helps to identify the bottlenecks impacting the supply chain impact and vice versa.

“For example, in the polyester business, the PTA was mostly sourced from China and we explored through the data analytic whether it was feasible for us to produce it ourselves. However, based on the cost of production and other factors, we concluded that it is prudent to buy it rather than producing it. We harnessed the data and thus highlighted the strategic use of data.

“Most companies found out that most of the accidents happen near the crane area and the tanker where there was a fire due to electricity. The CEO decided that the entire company must go through the training on static electricity. However, instead of that it should have been the driver who should have been given training. Similarly for crane, the maintenance team and crane operator need to be trained. A governance and mindset change is important. In terms of transition, the change management has to develop a culture as with data we have to demonstrate the benefits followed by scaling up.

“We have to create a digital dashboard where we know the users and we track the usage. We should not create just a digital dodo that stops working once the management turns the attention away. The duplication should be avoided as it will hamper the entire system and because we don’t have a single source of truth."

Anamika, DGM – ERP (Digital Applications), HPCL said, “We started the digital transformation around the year 2018 with the Project Parikalp. In the beginning we thought of demand forecasting as we are a downstream company. It did wonders as we were able to predict the demand with 95% accuracy.

“After that we started many more digital initiatives. In case we are not able to market our solution or reach the businesses, they either don’t use it or we start shadow use. The basic thing is that if we are in a data driven culture we have to reach the people and show them what kind of insights they are getting for the growth. We used predictive maintenance for most of the equipment in our refinery.

“Currently the second phase is in the progress but in the beginning there were questions about how could it better the operations. It took 7-8 months to convince the refinery teams for adopting AI-ML solutions. The equipment is very expensive and we had to convince the committees about saving maintenance. For demand forecasting, we did a POC and were able to give 98% accuracy. 

“Being first digital implementation, management gave us a huge budget but the vendor quoted double the budget that was allocated to us. It took us a month to calculate the benefits that will come. In terms of Generative AI, we started using it in November 2022, initially with in-house GPT. After a successful demonstration, we are now scaling it up." 

The PetroChem Summit 2024 themed ‘Identifying New Opportunities For Value Creation’ was supported by the industry associations including Alkali Manufacturers Association Of India (AMAI) and Chemicals & Petrochemicals Manufacturers' Association (CPMA). The Platinum Sponsor was Somaiya Vidyavihar University and Gold Sponsor, Tubacex Group.