Statistical Thinking to Improve Quality

This posting describes the final phase of the resin output variation example that illustrates the Hoerl-Snee process improvement strategy.   This example appears in Britz et al (2000) and in Hoerl and Snee (2002).   The Ricoh team is focusing on reducing the variability in resin output quantity.   The previous post stated that the next step for the team was to investigate the weighing processes.

The overall process had two weighing processes.  The first was an in-process manual method, and the second method was a final, automatic scale.   The manual method had individuals reading a line on a scale.  They observed that individuals of different heights read the line from different viewpoints.  Thus, they produced different readings.   The team changed the presentation of the line so people of different heights had the same view point.   This change reduced in-process measurement variation.

Next the team investigated the automatic scale and found significant measurement errors.   They reduced these errors by:

1.     Redesigning the scales protective cover.

2.     Establishing procedures for checking the alignment on a periodic basis.

The following figure presents a control chart showing the results for this project.  The difference between the final upper and lower control limits was less than the team objective of ± 5 kg.  However, the resulting average was 4292 kg which is less than the original target of 4300 kg.   Given the reduction in output variability, management regarded the results as more than adequate.   The improvement also resulted in reduction in the variation of resin viscosity.   This verified the team’s motivation to reduce variation of finished product quality by reducing the output quantity variation. To maintain the results, the team created procedure manuals and established a schedule adjusting the automatic weighing process.

The overall improvement process consisted of four Plan-Do-Check-Act (PDCA) cycles.   This posting describes the last one, the previous post describes two of them and the posting on March 21 (Hoerl-Snee Example) describes the first one.   That one focused on finding and correcting special causes.   This process is different than that suggested by a serial DMAIC process.   Our next posting will present the Hoerl-Snee process improvement strategy which has an overall PDCA approach.

References
1.     Britz, G. C., D. W. Emerling, et al. (2000). Improving Performance Through Statistical Thinking. Milwaukee, WI, ASQ Quality Press.
2.     Hoerl, R. and R. D. Snee (2002). Statistical Thinking - Improving Business Performance. Pacific Grove, CA, Duxbury.