Level: Intermediate
Joseph Beauchemin, Jr., Director of Quality, Hitchiner Manufacturing
Philip 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 much hype, there is confusion as to what is I4.0. Actually, I4.0 encompasses a number of parallel initiatives and is broader in scope than manufacturing. Despite confusion about I4.0, one consequence is the proliferation of large amounts of data within organizations. Few organizations have a coherent strategy to deal with the data deluge and lack the skills to analyze the data. We present a framework to manage the many data streams resulting from I4.0 and propose standardized workflows for analytics on the data to drive process improvement utilizing Six Sigma tools. We propose JMP statistical software as a solution for data analyses and intranet reports. 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. Using a case study we show how an advanced manufacturing company reduced the time spent on formatting, importing and cleaning up data from 90% to less than 10% of project time. With Standard Work, the company went from near 0% to greater than 95% yields on many products and become a preferred supplier for key customers. In this talk we will discuss Standard Work and demonstrate live how JMP is central to its successful implementation using a case study. Standard Work requires an educated workforce and the JMP online course Statistical Thinking for Industrial Problem Solving provides a free solution.