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Premium Reduction & Delivery Improvement Champion –Sponsor –

Premium Reduction & Delivery Improvement Champion –Sponsor – . Contract. Project Title: Premium Reduction. Plant Premium 200x Detail. Data was obtained from the Premium Web Site. Plant Premium 200x Detail. Data was obtained from the Premium Web Site. Plant – 200x Internal IPM .

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Premium Reduction & Delivery Improvement Champion –Sponsor –

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  1. Premium Reduction & Delivery Improvement Champion –Sponsor –

  2. Contract Project Title: Premium Reduction

  3. Plant Premium 200x Detail Data was obtained from the Premium Web Site

  4. Plant Premium 200x Detail Data was obtained from the Premium Web Site

  5. Plant – 200x Internal IPM Data was obtained from the Premium Web Site

  6. Plant 200x – Internal IPM Data was obtained from the Premium Web Site

  7. SIPOC

  8. Plant Premium Reduction & Delivery Improvement Measure Date: 01 / 06 / 0x

  9. Cause & Effect Diagram

  10. Data Collection Plan

  11. Data Collection Plan

  12. Gage R & R Study • Repeatability • Within Appraisers • Appraiser agrees with him / herself trials • Reproducibility • Between Appraisers • All appraisers assessments agree with each other

  13. Plant Premium Reduction & Delivery Improvement Analyze Date: 03 / 24 / xx

  14. Descriptive Statistics The median time for parts on backorder is 2.3 days. With a target of 2 days our process defect rate is 53%

  15. Descriptive Statistics Our process is stable with no clustering, mixtures, trends, and oscillations

  16. Identify variation Sources

  17. Identify variation Sources X1 - Uptime Data analysis shows that machine uptime and time to fill a backorder do not have a strong correlation – not statistical root cause

  18. Identify variation Sources X2 – Set Up / Change Over Data analysis shows that Set Up / Change Over Time and time to fill a backorder have no correlation – not statistical root cause

  19. Identify variation Sources X3 – Tool Availability No difference in either the center (median) or spread (variation) between tool Available yes vs. no – not statistical root cause

  20. Identify variation Sources X4 – Press Availability The p values are greater than .05; we accept the null hypothesis ~ there is no difference in backorder time when a press is available – yes vs. no

  21. Identify variation Sources X5 – Spare Tooling Part Availability Although the medians appear different, there is not enough data to statistically conclude there is a difference – there were only six samples when spare tooling was not available

  22. Identify variation Sources X6 – Maintenance Response Time Statistical Root Cause – with a p-value of .004 we reject the null hypothesis; there is a difference in times. When the maintenance call takes over 4 hours then the backorder time goes up significantly!!

  23. Identify variation Sources X7 – Tool & Die Repair Time Statistical Root Cause – with a p-value of .001 we reject the null hypothesis; there is a difference in times. When the maintenance call takes over 4 hours then the backorder time goes up

  24. Identify variation Sources X8 – Orders vs. Pulls No difference in either the center (median) or spread (variation) when we ask If the pull was greater than the order, yes vs. no – not statistical root cause

  25. Identify variation Sources X9 – Low Volume No difference in either the center (median) or spread (variation) when we ask If the part is low volume, yes vs. no – not statistical root cause

  26. Identify variation Sources X10 – Red Tag or Care No difference in either the center (median) or spread (variation) when we ask If the material had any pieces in redtag, yes vs. no – not statistical root cause

  27. Identify variation Sources X11 – Start/Stop Part No difference in either the center (median) or spread (variation) when we ask If this PN was a start/stop part, yes vs. no – not statistical root cause

  28. Maintenance Response Time is a significant contributor to Time to Fill Back Order (Y) Tool & Die repair time is a significant contributor to Time to Fill Back Order (Y) Both Maintenance Response Time and Tool & Die Repair Time impact Uptime but Uptime alone is not a significant factor Other potential causes (X’s) did not show significant impact to Time to Fill Back Order This statistical data indicates that in order to reduce the Time to fill a Back Order, which potentially leads to premium, we must reduce the Maintenance Response Time and the Tool & Die Repair Time Analyze Take - Aways

  29. Continue in the Improve Phase Develop solutions to improve Maintenance Response Time and Tool & Die Repair Time Collect Data from the Recommended improvement plan Evaluate if corrective actions reduce or eliminate the impact of Maintenance Response Time and Tool & Die Repair Time on the Time to Fill a back Order / Premium Next Steps

  30. Plant Premium Reduction & Delivery Improvement Improve / Control Date: 05 / 05 / xx

  31. Tool & Die Repair Time Solutions Dedicated Tool & Die support on all Shifts Use the Andon System to improve call priorities Die Maker inspects and releases parts in place of a traditional release person Document all Die changes in the log book Dedicated tool makers for different die families Maintenance Response Time Solutions Dedicated Machine and Maintenance Repair support and on all shifts Use the Andon System to improve call priorities PC&L notifies maintenance when a part goes on back order Maintenance Supervisor copied on all critical parts Develop Solutions

  32. The p values are less than .05; we reject the null hypothesis ~ there is a difference in backorder. The solutions have impacted both variation and median Test Solutions - Pilot

  33. New Capability Analysis Applying the goal of less than 2 days on backorder the solutions implemented improvement our process from 1.4 sigma to a 2 sigma process.

  34. Department 11xx was the first module installed. Implementation of the remaining modules that will utilize these solutions are as follows: Department 11xx will be completely installed by 5/15/xx Department 11xx will be completely installed by 6/1/xx Department 11xx will be completely installed by 8/1/xx Department 11xx (Low Volume) will be completely installed by 10/xx Department 11xx will be replaced by 11xx (8/1/xx) Department 11xx will be replaced by 11xx (6/1/xx) Timeline for Full Solution Implementation

  35. January – April of 200x compared to January – April 200x indicates a reduction in premium of 16%, 80%, 84.5% and 31.4% respectively. This equates to a 61.9 % reduction in premium over the same four month period. Over the last two months departments without the improvements have accounted for significantly more premium than department 110x. Dept 110xNon-Improved Depts March 18.0 % 52.0 % (1119) April 27.8 % 58.9 % (1116) Our implemented solutions improved our process by 30 % From 1.4 Sigma to a 2.0 Sigma Our implemented solutions reduced our median time to fill a back order by 41.6 % From a median of 2.4 to a median of 1.4 Based on these improvements we conclude that the plant 11 premium will be reduced by approximately 34.0 % Based on 200x premium of $308,940, the financial impact will be a reduction in premium of $105,040.00 per year. Financial Impact

  36. Plant xx team should monitor Maintenance Response Time and tool & Die Repair time. This should be monitored on a monthly basis. If Maintenance Response Time or Tool & Die Repair Time is greater than 4 hours, plant should investigate root cause Need to determine responsible person (s) to monitor these issues System generated reports for Maintenance Response Time and Tool & Die Repair Time will support in this effort Control Plan

  37. Breaking down “old” barriers and avoiding finger-pointing by using real data collected by a true cross-functional team Excellent cross functional team that was represented by manufacturing, PC&L, tool engineer, Quality, IT, Terminal Store Supervisor and Manufacturing & PC&L Master black belts Dispelled many theories about causes for premium and allowed us to focus on real root cause Provided additional data for the manufacturing team to focus on the real causes for premium and other machine down time / Uptime issues Processes across all functions are interrelated but not all controlled by the plant manager Good cross functional support is required for the plant to be successful Excellent job by IT support to provide accurate real time data. Every black belt project should have an IT person on the team Excellent data collection and support by all team members. Intangibles

  38. Back-up

  39. Plant xx- Dept. xxxx Premium in 200x Data was obtained from the Premium Web Site

  40. Plant xx- Dept. xxxx Premium in 200x Data was obtained from the Premium Web Site

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