Data science and analytics is such an evergreen field that finds its use in every industry. Today the world is moving towards automation, and even the chemical industry is starting to adopt such practices and thus the use of data science in the chemical industry has increased significantly. Every experiment starts from a simulation of a process in the laboratory and data science and modeling helps in scaling it from the lab scale to a plant scale. So, let us dive deep into understanding how data science can be applied to chemical engineering.

For example, a lot of times, the chemical industry is full of recording errors. Error in recording parameters may hamper various simulations and processes. In such cases, data science and analytics in the chemical industry provides a significant advantage. A few major advantages of using industrial data science techniques are:

  • It helps in quickly identifying trends and patterns, which is an essential requirement for the chemical industry to recheck an observation.
  • It leads to reduced human effort, which means fewer chances of errors and reduced cost.
  • As data Science handles multi-dimensional and multi-variety data, things can be done in a dynamic and uncertain environment.
  • Observing calculations to estimating the number of chemicals required for a reaction, holds the capacity to benefit the industry.

Considering the above points in mind, we can clearly state that analytics can not only boost production but can also reduce and cut-off unprofitable production lines that are not of any use, helping in both – reduced energy consumption and reduced wastage of valuable resources like labor and time.

Stan Higgins, the retired CEO of the North East of England Process Industry Cluster (NEPIC), who currently is a non-executive director at the Industrial Technology Systems (ITS) and also a senior adviser to Tradebe, which is waste management and specialty chemical company, says that miracles can be done using analytics in chemical industry. He describes that his work accompanied by data analytics led him to win the Officer of the Order of the British Empire (OBE) for the work promoting the UK’s process manufacturing industry. He describes that in production, the challenges are never-ending.

 

The key to any successful venture is maintaining quality production and maximizing output within health, safety, and environmental goals. Every day, new chemicals, and intermediates are being developed in chemical industries, and it requires a lot of attention for a human being, considering all processes like cost, availability, quantity, and then being able to decide the most suitable chemical product and alternative on a daily basis. The chances of error are very high, and it can be crucial to the industry.

What are some of the other uses of data science and analytics in the chemical industry?

  • Use for checking the overall value of an alternative chemical, over the currently being used chemical.
  • It can help in determining precise and essential measurements for the reactivity of chemicals, checking for their optimum conditions that are favorable.
  • It can help in understanding the best reactivity of a catalyst for the different conditions of temperature, pressure, and other conditions.
  • It helps in guessing a pre-determined result after a reaction.

Concluding, it won’t be inappropriate to say that there isn’t a field where data science and analytics can’t find its application. For large industries, business intelligence plays a key role in promoting growth. So, analytics and BI in chemical industries can bring about huge improvements over a period of time.

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