Chemical Industry in the Age of Big Data Analytics

by December 20, 2017 0 comments

According to the Economist, chemical industry is now in the golden age of materials. The global chemical industry employs nearly 20 million people and has annual sales amounting to nearly US$5 trillion. Almost every manufactured product is derived from intermediate materials having its roots in petroleum and natural gas. Agriculture, automotive, pharmaceuticals, and construction industries are served by the chemical industry and any changes in this industry will surely produce an effect on the others.

Earlier the demand was for certain chemicals sold in high volume and well-margined markets. But now with digital transformation promoting strategic growth and streamlining the industry, both commodity and specialty chemicals are now being tailored to their end application because of technologies like IoT, artificial intelligence, robotics, additive manufacturing and advanced analytics.

Industry 4.0 combines all the above-mentioned technologies to drive the physical act of manufacturing. The physical – digital – physical cycle is completed using these connected technologies. ‘Operating the business’ and ‘growing the business’ are two business imperatives for manufacturers. There are certain areas within the manufacturing value chain in which manufacturers can apply Industry 4.0 to achieve business imperatives.

Focus on business operations improves productivity and reduces risk whereas a focus on growth generates new revenue and adds incremental revenue. Prediction of phase diagrams, preventative maintenance and asset management, intelligent chemical processing are some of the manufacturing techniques with which productivity of chemical plants can be improved upon. Risk reduction, on the other hand, involves safety management and demand forecasting techniques.

Smart manufacturing can benefit chemical companies in several ways like:

1. Phase Diagram Prediction: Phase diagram showing conditions at which thermodynamically distinct phases occur and coexist at equilibrium can be predicted using computer codes.

2. Preventative Maintenance and Asset Management: Sensors on equipment like turbines, compressors, bring in a continuous stream of data which analytics makes use of to identify patterns and predict potential breakdowns and prevent machinery failures. Also, data comparison from similar equipment can be used for performance optimization.

3. Detection Alarms: Lower explosive levels of gases, like hydrogen sulfide, oxygen, nitrogen dioxide, carbon monoxide and sulfur dioxide are continuously monitored.

4. Energy Management: In a chemical plant with multiple dynamic operations being performed simultaneously, it is difficult to select optimal operating conditions. Industry 4.0 makes use of technologies like soft sensors that can process a number of data points and enable control of nonstandard process variables to improve energy efficiency.

5. Load Forecasting: It is basically the ability to load forecast for raw materials (oil, natural gas, air, water, metals, minerals, etc.) to meet demand and supply of power and energy.

6. Safety Management: Traditional safety methods employed the collection and testing of samples whereas Industry 4.0 technologies make use of methods that monitor real-time data. For instance, mechanical vibrations or cracks in a chemical tank can be sensed by piezoelectric composite paints thereby reducing production risks.

Chemical companies have historical data sets related to products and processes which can be used to uncover patterns. First operations that are simple and have more visibility like the supply chain should try and build capabilities. Once this is done, the more complex operations should be targeted. Chemical companies should build diverse capabilities in big data related applications and create a cross-functional Industry 4.0 team that can work together towards the common goal of the company. With strategic steps including digitization, this industry can once again look forward to profitable growth.

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