A Practical Road Map for Implementing Industry 4.0 and Data Analytics Using Cust...
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A Practical Road Map for Implementing Industry 4.0 and Data Analytics Using Custom SQL and JMP(R) (2020-EU-45MP-429)
Jan 30, 2020 7:56 AM
| Last Modified: Mar 24, 2020 8:54 AM
Joseph Beauchemin, Jr., Director of Quality (Non-Ferrous), Hitchiner Manufacturing Philip J. Ramsey, Professor, University of New Hampshire
Industry 4.0 (I4.0) is an initiative to transition organizations to the digital revolution and guide the creation of smart factories. Despite confusion about I4.0, one consequence is the proliferation of large amounts of data within organizations. We present a framework to manage many data streams resulting from I4.0 and propose standardized workflows for analytics to drive process improvements. JMP statistical software is a solution for data analyses and reporting. Standard Work and JMP are used to: Identify data requirements and collection strategies; create custom SQL databases; perform standardized analyses in JMP via custom scripts; and create dashboards with JMP for management reviews. The range of analytical capabilities and scriptability of JMP make it key to Standard Work. The JMP Query Builder is essential in accessing SQL databases that link all of the relevant data sources, while automatically integrating various JMP data analyses. A case study using JMP and Standard Work shows an advanced manufacturing company reduced data correction and formatting time from 90% to less than 10% of project time and increased yields from 10% to over 90%. JMP platforms used are: Query Builder, Process Screening, Predictor Screening, Response Screening, Model Driven Multivariate Control and Functional Data Explorer.