Artificial Intelligence in Chemical Industry - II : Quality

Part I 

Quality

Another area where AI can contribute immensely is quality. Many quality parameters are not possible to be measured online and need the intervention of a laboratory. The granulometry of a prilled product, for example. Or the Iodine Value of oil; or the opacity of a pigment. Any measurement in a laboratory is riddled with three problems: sampling error, contamination during sampling and time-lag. Oftentimes, if the results are not as per expectation, there is no alternative but to recycle the product or label it as off-spec. Now compare this with the scenario in a kitchen, a veritable chemical plant, where quality requirements are equally stringent and complex, if not greater. Corrections to perceived shortfall in quality are instantaneous and intuitive in the kitchen. If AI systems be taught to replicate such actions in a chemical plant, laboratories will be rendered redundant.