Artificial intelligence (AI) has swiftly transitioned from being a speculative future advancement to a pivotal component of today’s chemical process industries (CPI). Recent findings suggest that over 80% of CPI executives anticipate substantial impacts from AI within the next three years. Companies are increasingly deploying AI across various functions, including research and development (R&D), manufacturing, risk management, and forecasting, aiming to cut costs, enhance product quality, and accelerate innovation.
TotalEnergies stands out as an exemplary case of this transformative shift. The French multinational has embraced AI by launching AI-powered assistants at its Antwerp refinery. Collaborating with Sinequa, a leader in enterprise search technology, TotalEnergies has developed tools known internally as MILAa (My Intelligent Learning Application) and JAFAR (Generative AI for Return of Experience). These innovations address significant challenges in refinery knowledge management and root cause analysis, utilising natural language processing and machine learning to streamline operations and enhance decision-making.
Prior to the implementation of these AI solutions, engineers at TotalEnergies grappled with fragmented access to vital operational data. Root cause analysis documents, maintenance records, and technical manuals were stored in disparate systems and often presented in inconsistent formats. This lack of coherence not only delayed the identification of failures, leading to prolonged downtime, but also resulted in inconsistent decision-making across teams. The company estimates that repeated operational incidents stemming from these inefficiencies cost millions in lost productivity and repairs.
In response, MILAa was crafted to amalgamate over a thousand root cause analysis documents into a centralised knowledge framework. By leveraging Sinequa’s enterprise search capabilities, MILAa allows engineers to query information in natural language, significantly reducing the time and effort required to locate data. This initiative fosters cross-site learning, essential for standardising operational responses and preventative strategies across TotalEnergies’ global operations.
JAFAR complements MILAa by converting static documents into interactive dialogue, thereby enhancing usability. By automatically translating technical RCA documents into multiple languages, JAFAR maintains the integrity of industry-specific terminology through a custom-built dictionary. As Pierre Jallais, the lead architect for Smart Search Engines at TotalEnergies, emphasised, such a sophisticated integration allows for a more nuanced understanding of the unique language used within the company, facilitating better interaction with critical operational knowledge.
Beyond TotalEnergies, the broader CPI landscape is witnessing significant AI-driven advancements. In R&D, AI is being harnessed to optimise chemical formulations and accelerate the identification of promising molecules. With investments surging in AI technologies in both the UK and US, enhanced market research, prototyping, and customer personalisation have become the new norm, promising to push product development cycles forward.
Moreover, AI’s influence extends into manufacturing processes, significantly improving quality control and safety. Predictive maintenance systems analyse data from sensors to foresee potential hazards, which is critical for ensuring that quality standards are upheld and operational efficiency is maximised. Recent reports have highlighted instances where predictive maintenance models have enabled companies to halve their unexpected downtimes, thereby solidifying AI’s role as a game-changer in enhancing operational reliability.
AI is also transforming supply chain management within the chemical sector, where advances in predictive analytics lead to improved forecasting accuracy, enabling companies to manage raw material procurement more efficiently and reduce inventory waste. With AI-driven tools improving anticipatory capabilities regarding pricing and demand fluctuations, CPI firms are better positioned to enhance profitability and logistics agility.
In conclusion, the integration of artificial intelligence into the chemical process industries is not merely a trend; it represents a significant evolution in operations management. Through pioneering applications such as those exemplified by TotalEnergies, the sector is not only addressing historical challenges but also setting the stage for a future characterised by greater efficiency, enhanced safety, and sustained innovation.
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Source: Noah Wire Services
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