Can AI optimize Fire Protection in the chemical industry?

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AI can optimize fire protection in the chemical industry! It is an exciting new idea that brings hope to an industry that has dealt with accidents so many times in the past. The lives that were lost and the environmental damage that remains is a reminder to constantly look for optimal solutions for the fire problem in the chemical industry.

The chemical industry is packed with substances that are both beneficent and maleficent for society and that is why extreme safety measures should be applied to prevent fire hazards. But they should also be the most recent technologies that are available.

AI is the simulation of human intelligence, armed with the fastest computer processors, seems capable of solving fire problems once and for all. The features are remarkable and still growing rapidly so the possibilities are endless.

In this article, we will explore how AI can optimize fire protection in the chemical industry considering the root causes. We hope that HSE professionals will gain new knowledge about modern technology solutions that will make their job much easier and safer.

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AI and Root Causes of fire in the chemical industry

Fire starts when a flammable substance is near an ignition source. In the chemical industry, both are abundant in different forms and shapes. The industry data is fed to an AI system that incorporates machine learning or deep learning capability to build models. Depending on the root cause, artificial intelligence runs a risk evaluation first to define the required protection level which is constantly updated with R&D data. It makes different scenarios based on the location, chemical property, and other conditions, to predict and prevent fire accidents. And that is how AI can optimize fire protection in the chemical industry!

According to AIDIC report, the following root causes are the most common in the chemical industry, some of which might even go unnoticed:

  • Self-ignition

22% of fire accidents are caused by self-ignition which is really due to the chemical reactions that occur inside certain substances. It could be the oxygen, pressure, and temperature that initiate the reaction. Either way, some rules control such events as determining autoignition temperature, maximum pressure point, exact largest individual quantity (LIQ), boiling points, or toxicity levels for each substance.

AI can optimize fire protection in the chemical industry by being involved with determining chemical properties and setting the storage conditions to match those properties. It uses data predictively to determine at which point fire accidents may occur for each substance.

Another danger relating to chemical storage is the flashover event in which flammable materials in one space ignite simultaneously leading to blazing depending on the available oxygen. Using heat detectors in real-time which only operate at temperatures below 150 degrees Celsius (302 Fahrenheit), the machine learning algorithm can continue monitoring the temperature beyond that point to predict its increase to 600 degrees Celsius (100 Fahrenheit) at which flashover occurs.

Self-ignition is a major root cause of fire in the chemical industry
Self-ignition is a major root cause of fire in the chemical industry
  • Hot running engines

17% of fire accidents are caused by a nearby hot running engine that can be a vehicle or generator.

Having access to operation schedules from one side, security cameras from the other side, and also equipment lifespan data, AI can prevent and alert the proximity of hot running engines to chemical storage.

  • Welding operations

15% of fire accidents occur due to welding operations which are common maintenance operations in chemical facilities such as the oil and gas industry. They are required to keep the structure and equipment working properly. But they produce a spark which is a highly dangerous nearby substance.

AI can be involved with the right timing but it can also watch the actual operation in real-time for the smallest sparks that might lead to a fire. There are also heat detectors that can help read the temperature around welding operations and sound the alarm before it even gets close to dangerous points.

  • Electrostatic

14% of fires are caused by electrostatic charges that are present in every chemical facility due to the abundant use of electrical appliances. The charges often cause sparks that are visible through certain cameras and detectors.

And that is how AI can optimize fire protection in the chemical industry by monitoring electrostatic levels and sending notifications when it is beyond safe points.

  • Drying process

10% of fires are caused by the drying process which deprives the air of moisture and sets the condition for a fire in presence of flammable chemicals. Drying powders are also combustible that makes the situation worse.

AI, having access to all detectors and sensors can monitor the moisture level in the air and send notifications when the level is too low from a safety standpoint. In addition, it can detect any small fire that might lead to explosions.

  • MRO operations

8% of fires are caused by MRO (maintenance, repair, and overhaul) operations that are routine in the chemical industry. They can be major overhauls that are performed every 3 to 5 years when the facility is closed or they can be ongoing small fixes that are done during the operation. Either way, they use external contractors and utilize many substances and procedures that can be explosive.

AI can optimize fire protection in the chemical industry by predicting the worst-case scenario and planning for it. But it can also monitor the whole process through CCTV cameras, detectors, and sensors and sound the alarms when dangerous behaviors are observed or the level of temperature, moisture, and electrostatic in the environment is too close to dangerous zones.

Drying process can ignite a fire in the chemical facility
Drying process can ignite a fire in the chemical facility

AI for maintenance safety

In oil refineries, artificial intelligence (AI) can reduce accidents during overhaul and overcome the limitations of current safety systems. For more information:
  • Leaks

7% of fires occur due to leaks which are common where there is liquids or gas chemical, some of which are odorless and invisible. This property increases the likelihood of fire because there is always a source of spark in each space that might ignite a fire in a room full of leaks.

AI having learned from massive training data can detect any liquid leak through cameras or read a gas leak through detectors. The alarms will be sound and notifications will be sent to prevent any kind of operation nearby until the leak is fixed safely.

  • Electric short circuits

7% of fires are caused by electric short circuits that are not unusual considering many wirings and appliances that might overload. This leads to sparks that can ignite a room full of odorless gas.

AI is capable of integrating with all systems in the facility can monitor and control electricity load in appliances for their optimal operation and also shut down the systems when leaks are detected.

Conclusion

AI can optimize fire protection in the chemical industry due to the many features it has such as data predictive and preventive analytics. It is capable of predicting the danger point for any kind of root cause such as self-ignition of chemicals, the proximity of running engines or welding operations, increased electrostatic or drying, MRO operations, the possibility of leaks, and electric short circuits. It can also monitor all operations in real-time through CCTV cameras, detectors, and sensors to notify the HSE team of any possible hazards it has learned from training data.

Intelligent HSE is the nexus approach for workplace safety in the chemical industry. AI-based HSE management system is the transformative solution to fire protection in the chemical industry that will revolutionize the HSE profession to save the lives of humans and the whole ecosystem.

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