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Aug 19, 2014

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An Example of Visual Six Sigma for Automation With JMP® Scripting

Laura Zambianchi, Six Sigma Black Belt, Fresenius Kabi

Sara Bergonzini, Process Control and Senior Validation Specialist, Fresenius Kabi

Alessandro Girotti, IT Manager, Fresenius Kabi

Emma Caiazzo, Process Control and Validation Specialist, Fresenius Kabi

Luca Ferraresi, Process Engineer Filter Assembling, Fresenius Kabi

Sebastian Hoffmeister, Trainer and Statistical Consultant, STATCON

Automated manufacturing processes make it possible to reduce costs and to enhance quality. Real-time visual management of process and product data is a key added value for operational excellence. Large output throughputs, especially in highly regulated fields like the pharmaceutical or medical devices industries, require a change in the approach toward quality, which has to be integrated into the process and oriented toward preventing defects, rather than detecting non-conforming items (goalpost mentality). In most companies, integrating the existing QC data structure with manufacturing information is a challenge, since often process (Xs, collected as online time-series measurements) and product data (Ys, recorded offline for single item or batch traceability) are disconnected. With a six-week project of JMP scripting following a 2+2-days formal training session, our team developed a tool for supervising the newest automated filter manufacturing line. Connecting dynamically to an SQL data server and multiple databases, Ys and Xs are simultaneously monitored and visually analysed. The new tool is cheap, simple and flexible, and allows a complete, real-time picture of what is happening on the shop floor – useful at every level, from shift engineer to financial control to process validation to preventive maintenance.

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