AI in Water: 10 Ways AI is Changing the Petrochemical Industry

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February 23, 2021 | Javier Cantu

Artificial intelligence (AI) is making its mark on the Petrochemical industry. It is powering intelligent operations using machine learning to optimize resource use and operational budgets for organizations, as well as delivering truly intelligent built systems. Provided below are 10 ways that AI is changing the industry.

1. AI will drive a decade of technology investment in refinery operations

Water and wastewater operations are investing in artificial intelligence (AI). Recent market research is forecasting $6.3 Billion of investment in AI solutions by the year 2030. This investment is a part of a growing trend for the water industry to “go digital” with smart infrastructure solutions.

2. AI will deliver significant OPEX savings

Where refineries are spending millions to meet more stringent regulations and overcome aging infrastructure challenges. The potential for savings is significant. AI can save 20-30% on operational expenditures (OPEX) by reducing energy costs, optimizing chemical use for treatment, and enabling proactive asset maintenance.

3. AI will predict emergency events and learn from them at an accelerated rate

Equipment failures can be costly – in both financial and social capital. AI and machine learning can “fingerprint” the data patterns that indicate an event may be imminent and learn from these patterns so that alerts become more accurate over time.

4. AI will provide sophisticated decisioning intelligence to support operators

Operators no longer need to analyze complex variables for important decision-making by themselves. Whether it’s turning pumps on or off, determining chemical dosages, or deciding when to maintain assets, AI enables the Operator 2.0 – empowered by intelligent recommendations driven by machine learning.

5. AI will optimize for scope 1 and scope 2 emissions while reducing cost

According to the USEPA, energy consumption makes up 25-30% of total operation and maintenance (O&M) costs. AI can optimize pump runtimes so that they are only using energy when they need to. This is a quick cost-reduction win for many early adopters of AI.

6. AI will support compliance requirements, cost-effectively

Meeting compliance standards is a requirement for many organizations – both public and private. AI learns from the unique characteristics of your site to ensure that standards are met and that compliance fees are avoided.

7. AI will simplify data integrity

An explosion of available data for operations managers has brought along a challenge of data management. SCADA systems, CMMS, and even weather data sets hold a wealth of knowledge to improve operations. AI can take this heterogeneous data and process it so that it is clean, useful, secure, and drives high-fidelity recommendations.

8. AI will retain institutional knowledge

How do you ensure that a veteran operator’s valuable knowledge is retained after they leave the workforce? AI-powered dashboards will keep institutional knowledge documented and standardized.

9. AI will accelerate the move to value-based asset maintenance

Early adopters of AI are quickly leaving reactive asset maintenance behind. Time-based maintenance is easy to manage but results in unnecessary uptime and deterioration. Let AI tell your team what assets need to be serviced, and when.

10. AI will power truly smart refineries

The journey to AI adoption empowers organizations to pursue data-driven, intelligent management systems. The result is resilient, sustainable, and cost-effective operations for years to come.

Tags: ai, artificial intelligence, petrochemical, refineries, optimization, machine learning

About the Authors

Javier Cantu

Javier Cantu

Director of AI and Process Optimization

 

Javier is process optimization engineer at Innovyze and is responsible for client service and engineering solutions for industrial applications. He has 10+ years’ experience in the water and wastewater industry designing, managing, and creating optimization strategies and is currently based out of Los Angeles region.