{"version":1,"type":"rich","provider_name":"Libsyn","provider_url":"https:\/\/www.libsyn.com","height":90,"width":600,"title":"7. Big Data for Big Decisions in Maintenance ","description":" Guest: Mukund Subramaniyan, PhD student, Chalmers University of Technology \u201cThe data speaks about the behavior of the production system\u201d Instead of defining big data in terms of \u201cwhat\u201d and \u201chow\u201d, Mukund Subramaniyan invites us to asks: \u201cwhy\u201d big data? In this episode, Mukund Subramaniyan shares his adventure and precious knowledge as cross-disciplinary PhD student, bridging the gap between computer science and production engineering. His motto? Big data for big decisions. Mukund sees the potential of data in the production system, and uses his mathematical skills, combined with his knowledge about production systems\u2019 operations, to find the most efficient and effective way to transform data into knowledge. His mission is to help managers and engineers in the production and maintenance departments to make more accurate decisions with higher degree of confidence. Mukund\u2019s position in terms of balance between automation and human\u2019s contribution is that algorithms should be giving an augmented intelligence to humans as opposed to be the representatives of an artificial intelligence that does all the job, simply put. Mukund argues that 60-70 % of the work can be done by algorithms, and the remaining part of the work is up to the humans, who judge the results according to their experience, and make the final decision.  Check out Mukund\u2019s publications: Subramaniyan, M., Skoogh, A., Salomonsson, H., Bangalore, P., Gopalakrishnan, M., & Sheikh Muhammad, A. (2018). Data-driven algorithm for throughput bottleneck analysis of production systems. Production & Manufacturing Research, 6(1), 225-246. https:\/\/doi.org\/10.1080\/21693277.2018.1496491 Subramaniyan, M., Skoogh, A., Gopalakrishnan, M., Salomonsson, H., Hanna, A., & L\u00e4mkull, D. (2016). An algorithm for data-driven shifting bottleneck detection. Cogent Engineering, 3(1), 1239516. DOI: 10.1080\/23311916.2016.1239516 ","author_name":"DigiTalk Pod","author_url":"http:\/\/digitalkpod.libsyn.com\/website","html":"