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they are indirect. AI makes computers capable of performing tasks that would traditionally depend on the cognitive abilities of humans, such as observation, learning, decision making and problem-solving. Now imagine that all the computers and control systems involved in a factory process, say a chemical plant producing petrochemicals, are armed with AI capabilities. One wouldn’t need a human opFOUNDER & CEO, erator to perform basic process-control ALGO8 INC. operations such as observing and maintaining parameters such as processpressure, fluid flow rates, temperature and so on. The computer reporting the process parameters like pressure, speed or temperature itself is aware of these values. It is no longer simply measuring and displaying them for the operators. Rather, they have been trained to know AI-powered solutions have unlocked predictive asset which values of process parameters are desirable, which are safe, and which maintenance capabilities, process tracking and optimization are not. So, effectively the workflow for several process control functions can easily be simplified from Process out of bounds > The control device registers he pace at which our industries are getting digi- change > Operator registers change > tized is ever-increasing; I mean, it’s pretty intui- Operator decides the course of action tive if you think about it. The more digitization > Operator uses the control panel to fix we have, the more digital information we have change > Process rectified. To a much access to, and that just make making digital busi- more concise and faster workflow: Proness models easier. For the last couple of decades, we have cess out of bounds > Computer registers had widespread computer infrastructures installed in large change > AI-based corrective measure > and process-driven industries such as chemicals, manufacProcess rectified. turing, oil & gas, etc. And they have been in place, So clearly, one of the prigathering massive volumes of process and indusmary advantages of smart trial data over the years. The problem however factories will be the fact “AI-powered remained, that we did not have the means to that several processes solutions have utilize these data-stores to their full potential. will be completely auunlocked predictive However, with the advent of advanced Artomated. Without the asset maintenance tificial Intelligence (AI) and Machine Learnneed to depend on percapabilities, process ing (ML), we finally can make our computer sonnel to carry out these tracking and systems intelligent and do the work for us. Estasks, computers can optimization” sentially, digitization technologies have reached a achieve far superior results stage of sophistication where we can equip indusand much snappier response trial setups with ‘self-conscious’ computer systems; this times, since their action is instanwill be the next iteration of Industry 4.0, where we will see taneous. Any scope for inefficiencies in Smart Factory setups become commonplace. the operations due to oversight or huChemicals play a crucial role in the industry as well as a man error gets eliminated, workflows society since they can be found in a wide variety of everyday become more streamlined with fewer products from automobiles and medicines to toys and clothes moving parts, and well, the computer which means the impact that AI will have on the chemical in- core can simply handle far more infordustry, will greatly impact us all via multiple channels, even if mation than a human mind is capable
NANDAN MISHRA
AI PLAY IN CHEMICALS
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