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Data Science in Industry 4.0

  • Shirley Y. ColemanEmail author
Conference paper
Part of the Mathematics in Industry book series (MATHINDUSTRY, volume 30)

Abstract

Data science is piquing the interest of many large and small organisations and managers are asking universities for information and advice. Typically, the query is: I have many sensors and many measurements, what shall I do with all this data, and how can I get ready for Industry 4.0? The so-called fourth industrial revolution refers to automation and control based on data exchange in a digital environment where measurements are available on all aspects of production. Data science plays an intrinsic role in this scenario and is focused on understanding and using data. Data science requires a challenging mix of capability in data analytics and information technology, and business know-how. Statisticians need to work with computer scientists; data analytics includes machine learning and statistical analysis and these extract meaning from data in different ways. Moving towards increased use of data requires buy in from higher management and board members. Although serious progress involves a holistic approach, exemplars demonstrating potential value are also beneficial. This talk considers the implications for mathematicians and statisticians of the growing industrial demands and discusses examples from ongoing research projects with industrial partners where data visualisation, multivariate statistical process control charts and funnel plots have made an important contribution.

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Industrial Statistics Research Unit School of Mathematics, Statistics and PhysicsNewcastle UniversityTyneUK

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