How AI and ML can accelerate decarbonization in the chemical industry?

Industry 4.0 is swiftly making its substantial presence in sectors such as manufacturing, construction, and shipping. Industries and companies are accountable to the environment, to the future generation, and most importantly, to the people of the geography they operate in. With stricter norms for being carbon-neutral, ESG compliant, green process-driven enterprises have turned to new-age technologies such as Artificial Intelligence (AI), Internet of Things (IoT), and data analytics to remain compliant and ensure sustainability.

Chemical companies too, have had a long way from being one of the highest carbon producing industries to announcing 10-year plans of being carbon-neutral or even carbon-zero. To put things in a perspective, industries such as Oil and Natural Gas, Pharmaceuticals, and Chemicals whose core business models are based on producing and processing hydrocarbons have been facing significant challenges to implementing ways to lead the change towards decarbonization. Nonetheless, several companies are now seizing upon the transition to a low-carbon economy as a means to transform not only how they function but also what they offer.

Similarly, several multinational chemical companies have launched transformational initiatives centered upon sustainability. A prominent American chemical giant, for instance, has committed to integrating circular economy principles into its business models; designing 100% of its products and processes using sustainability criteria including the principles of green chemistry; and reducing GHG emissions by 30% by 2030, including sourcing 60% of its electricity from renewable energy.

A transformational shift

While going green, using renewable energy sources is a great leap, one of the most significant contributors to making industries carbon-neutral and accelerating decarbonization has been technology. Decarbonization involves heavy lifting.

Companies pursuing these goals require a transformational shift in the way they operate: From how they source, leverage, consume, and think about energy and feedstocks to how they engage with multiple stakeholders. Moving to this new way also requires a significant financial commitment from investors and governments. With the advancement in technology and tools such as AI, ML, IoT, data analytics, it’s pretty streamlined for businesses to lead the transformational journey.

Some of the ways that technology has played a massive role in accelerating this journey are encapsulated below:

• Optimized Product cycle using AI and ML: In the chemical industry, some of the most toxic materials and resources are bundled in the early stages of product development/manufacturing. With effective AI and ML mechanisms and research, companies can opt for manufacturing processes that are cleaner, greener, and sustainable in the long term. In international markets, AI has already made significant breakthroughs. With the invention of cutting-edge processes such as advanced molecules, companies already have started their journey on the decarbonization front.
• Reduce wastage and maintain high efficiency: An unintentional event in a Chemical production process often leads to the batch getting wasted and completely scraped off. A common practice for chemical manufacturers is to avoid inefficiencies and craft consistent batches of products. With the development of AI and ML, the whole production is automated, and product consistency is optimal. This increases efficiency and less wastage of chemical compounds, which would eventually account for the carbon footprint in the environment.
• Use of data analytics to check the carbon-out: Today, companies are accountable to over a dozen environmental and governmental bodies on account of their pollution and carbon- footprint. Today, with the use of Data analytics and sophisticated ML apps, engineers can keep track of the company’s carbon output on a real-time basis. A higher output variance triggers an alarm, and the whole manufacturing is stopped before the variance can be addressed. Additionally, there are AI-based tools that predict the carbon flow and out in a production process and suggest alternative means of resources that can reduce carbon production considerably.
• Evolution and breakthroughs in Research and Innovation: Chemical industry is a production-heavy industry with much scope for permutations and combinations. With ground-breaking research using AI and predictive analysis AI, ML tools computerized permutations and combinations help in advanced research to recognize molecules, generate formulas and ascertain quantity and mixtures of chemicals. This coupled with AI and ML’s ability to process millions of combinations which could lead to a process breakthrough, which will not just be efficient but also  help in accelerating decarbonization.

The development of AI, ML, data analytics, and other technologies is happening drastically. However, the adoption of these technologies in the chemical sector has been slow. With more and more focus on climate change, carbon-neutrality, sustainability, going green, and ESG compliances, chemical companies too will step up and realize that the utilization of tech to drive a fruitful balance between productivity and the environment is the only solution.

The author is CMD, Meghmani Finechem