How is AI Lending a Helping Hand in the Chemical Manufacturing...

How is AI Lending a Helping Hand in the Chemical Manufacturing Industry

Laura Davis, Manufacturing Technology Insights | Tuesday, January 12, 2021

Over the past decade or so, the chemical industry has implemented or developed AI to increase operational efficiency, decrease expenses, and enhance customer satisfaction. Today, a growing number of firms are using AI in the manufacturing process to cut greenhouse gas emissions and advance their operations’ energy efficiency.

FREMONT, CA: Chemicals play a significant role in society. From medicines and automobiles to clothes and toys, they can be found in numerous everyday products. The production of these materials can have adverse effects on the environment, including releasing greenhouse gases into the atmosphere.

Providentially, the chemical manufacturing industry has a new tool to reduce its environmental footprint, Artificial intelligence (AI). Over the past decade or so, the chemical industry has implemented or developed AI to increase operational efficiency, decrease expenses, and enhance customer satisfaction. Today, a growing number of firms are using AI in the manufacturing process to cut greenhouse gas emissions and advance their operations’ energy efficiency.

Research shows that the chemical sector accounts for about 10 percent of global total final energy consumption and 7 percent of greenhouse gas emissions. According to one agency in the U.S., the chemical industry has produced over 800 million tons of greenhouse gas emissions since 2011.

Greenhouse gases (carbon dioxide, nitrous oxide, methane, nitrous oxide, etc.) trap solar radiation in the earth’s atmosphere and make the planet warm enough to withstand life. Following the industrial revolution of the 1700s and 1800s, people have been releasing more massive amounts of these gases into the atmosphere, increasing global surface temperature and climate change.

AI shows excellent potential in plummeting the energy consumption and environmental footprints for the chemical industry. For example, an Austrian chemical company, one of the largest polyethylene and polypropylene producers, has deployed an AI program to develop dynamic target values for the plant’s energy consumption, enhancing the facility’s energy usage and consequently cutting emissions and budgets. Unfortunately, regardless of increasing awareness and exploration of AI in the chemical industry, it is challenging to compute these emerging technologies’ benefits and effects due to the lack of reliable performance data.

Most companies also struggle to match suitable assessment methods and performance indicators with different and complex AI tools in the chemical industry. This aspect can prevent policymakers and early adopters; whose investments are vital for accelerating AI deployment.

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