Practical Road Map for Implementing Industry 4.0 and Big Data Analytics Using Cu...
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Practical Road Map for Implementing Industry 4.0 and Big Data Analytics Using Custom SQL Databases With Standardized Workflows for Analytics and Dashboards Implemented via JMP(R)14 ( 2019-EU-45MP-053 )
Feb 11, 2019 4:32 PM
| Last Modified: Mar 14, 2019 2:42 PM
Level: Intermediate Job Function: Analyst / Scientist / Engineer Joseph Beauchemin, Director of Quality, LAI International Philip J. Ramsey, Owner, North Haven Group; and Professor, University of New Hampshire
LAI International, a manufacturer of highly engineered products, is implementing Industry 4.0 and associated data analytics using a Standard Work roadmap. Standard Work is used to identify data requirements and collection strategies to 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 machine data, product information, fringe data and process changes, while also integrating various JMP data analyses. LAI has reduced the time spent on formatting, importing and cleaning up data from 90 percent to less than 10 percent of project time. This allows LAI personnel to focus much more effort on data analytics to drive continuous improvement and solve difficult manufacturing problems. With Standard Work, LAI has become a statistics-driven company going from near 0 percent to greater than 95 percent yields on many products, becoming a preferred supplier for key customers. Using LAI case studies, we will discuss the Standard Work paradigm and demonstrate how JMP is central to its successful implementation.