1. Premium Reduction & Delivery Improvement
Champion –Sponsor –

2. Project Title: Premium Reduction
Contract

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

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

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

6. Data was obtained from the Premium Web Site
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. Appraiser # Inspected # Matched % Percent 95.0% CT 21 30 100
Gage R & R Study
Repeatability
Within Appraisers
Appraiser
# Inspected
# Matched
% Percent
95.0% CT 21 30
100
(90.5 , 100) 2 29
96.7
(82.8 , 99.9)
Appraiser agrees with him / herself trials
Reproducibility
Between Appraisers
# Inspected
# Matched
% Percent
95.0% CT 30 29
96.7
(82.8 , 99.9)
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. Analyze Take - Aways
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

29. Continue in the Improve Phase
Next Steps
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

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

31. Tool & Die Repair Time Solutions
Develop Solutions
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
PC&L notifies maintenance when a part goes on back order
Maintenance Supervisor copied on all critical parts

32. Test Solutions - Pilot
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

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. Timeline for Full Solution Implementation
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)

35. Our implemented solutions improved our process by 30 %
Financial Impact
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 110x Non-Improved Depts
March % % (1119)
April % % (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, per year.

36. Need to determine responsible person (s) to monitor these issues
Control Plan
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

37. Excellent job by IT support to provide accurate real time data.
Intangibles
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.

38. Back-up

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

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