Making The Most Out Of Machine Learning

Cement manufacturers today face many complex challenges. Amid technological disruption and an intensely competitive landscape, their world has become more regulated and less predictable. As part of an industry highly connected to the environment, cement manufacturers are under rising pressure to lower their carbon impact and meet increasingly complicated environmental regulations.

It is clear that manufacturers in this space need a solution – something to help them make progress on their goals and sift through the noise to find the most effective actions to take. Are tools such as artificial intelligence and machine learning the answer?

How could AI and ML be the answer to cement manufacturers’ problems?

Looking at manufacturing in general, the science shows that AI-driven tools can help solve problems, cut both costs and waste, and squeeze out efficiencies in difficult times. According to a 2022 report by McKinsey & Company, 42% of organisations that adopted AI in 2021 decreased their manufacturing costs, and 61% saw an increase in revenues.

What about cement manufacturers specifically? AI and Machine Learning (ML) technology can help them get through the specific challenges the industry is facing.

Consider supply chain disruptions. The cement industry involves the large-scale transportation of materials; as such delays and disruptions – such as those seen since the pandemic and its associated crises began – can wreak havoc on production schedules. ML and AI bring higher levels of data capture and automation to the process, making supply chains more transparent and adaptable. Manufacturers can see ahead, spot problems in the pipeline, and reduce costly downtime.

Improving supply chains is just one example of how AI and ML tools will be able to streamline production, environmental regulations are another. The cement industry is a major producer of carbon dioxide emissions, but new technologies can show cement manufacturing companies where they can perform carbon capture and where, precisely, they can reduce their carbon footprint and comply with regulations.

However, manufacturers might hesitate as they approach adopting complex technologies. The perceived costs of implementing new AI and ML technologies, at a time when the costs of manufacturing are already perilously high, can turn companies away from technology that could help them. Risk aversion has historically made sense in such a capital-intensive industry, and using new tools at scale could require significant investments in equipment, infrastructure, and training before their benefits appear.

The key for cement manufacturers will be to do their due diligence and only select technologies that make the most sense for their operations.

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Read the article online at: https://www.worldcement.com/special-reports/28122023/making-the-most-out-of-machine-learning/