CHENNAI: Scientists at IIT-Madras have written a code that can help factories spot performance-dragging parameters -or why the output shot up suddenly on a particular day -by just studying patterns from large, unstructured historical data sets and producing analyses that offer rare insight to help improve productivity and quality at the plants of automotive majors like Tata Motors . The algorithms can learn at work, too.With iterations, their intelligence grows to the point where the inferences, in some test cases, have astounded the professors with uncanny predictions. Taking into account hundreds of variables from weather patterns to attendance data to acidity levels (pH) in input raw material, the software, say professors, has drawn cause-effect relations that have missed the eye of experienced plant operators. “I would draw a parallel to how computers get to beat the Grandmasters at chess. While it is humans who are making software more and more intelligent, their capacity for growth can outstrip our own,“ said R Raghunathan Rengasamy , professor at the Chemical Engineering department at IIT Madras, and a director at Gyan Data, the startup that licenses this technology to be used by corporations.The algorithm was originally fed notions of high-performance, based on which it will scrounge the data sets for parameters that are indispensable for high output and accuracy in manufacturing.The software, built on general-purpose computing languages like Python and Java, has mathematical models as driving fundamentals. It will find application wherever control valves -used widely in industrial machinery -are used. It can detect malfunctions in control valves effectively by studying frictional data and flag discrepancies. Internet of Things (IoT) will add another dimension to the algorithm as plants would analyse historical data along with real-time feed from IoT-enabled electronics placed inside the factories.Gyan Data is a data mining startup incubated at IIT-Madras to turn research into products. It holds the technology which has been licensed out for royalty. As of now three foundries including Ashok Leyland and Tata Motors, four cement manufacturers, and one fertiliser plant of The Murugappa Group have benefitted from the algorithm, according to Rengasamy, who said two US-based manufacturers have begun dialogue to explore utilising the software.At the Tata Motors Jamshedpur plant, said foundry head Amiya Singha, any refinement in manufacturing had always been made on pure instinct.“In a foundry, there are no direct equations available for any change one would make in the process. There is an error rate of about 20%. Now, this technology has stabilised our process parameters. This has helped bring down costs and the casting moulds have even surfacing.“Data has transformed many internet-based industries like ecommerce. Analytics and predictive modelling are key to modern retail and other industries -an ecommerce site can prioritise brand visibility based on search data -but they are still uncommon in core manufacturing.“The smart machines, required to provide data necessary for analytics, are just arriving. Manufacturing can have great transformations as more and more data gets captured, “ said Madhavan Mukund, Professor and Dean of Studies at the Chennai Mathematical Institute, who also runs AlgoLabs, a think-tank offering predictive analysis.