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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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Presentation Transcript
slide2

Contract

Project Title: Premium Reduction

slide3

Plant Premium 200x Detail

Data was obtained from the Premium Web Site

slide4

Plant Premium 200x Detail

Data was obtained from the Premium Web Site

slide5

Plant – 200x Internal IPM

Data was obtained from the Premium Web Site

slide6

Plant 200x – Internal IPM

Data was obtained from the Premium Web Site

gage r r study
Gage R & R Study
  • Repeatability
    • Within Appraisers
  • Appraiser agrees with him / herself trials
  • Reproducibility
    • Between Appraisers
  • All appraisers assessments agree with each other
descriptive statistics
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%

descriptive statistics15
Descriptive Statistics

Our process is stable with no clustering, mixtures, trends, and oscillations

identify variation sources17
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

identify variation sources18
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

identify variation sources19
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

identify variation sources20
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

identify variation sources21
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

identify variation sources22
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!!

identify variation sources23
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

identify variation sources24
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

identify variation sources25
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

identify variation sources26
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

identify variation sources27
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

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

Analyze Take - Aways
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

Next Steps
slide30
Plant Premium Reduction

& Delivery Improvement

Improve / Control

Date: 05 / 05 / xx

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

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
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

Test Solutions - Pilot
slide33

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.

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)

Timeline for Full Solution Implementation
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 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
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

Control Plan
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.

Intangibles
slide39

Plant xx- Dept. xxxx Premium in 200x

Data was obtained from the Premium Web Site

slide40

Plant xx- Dept. xxxx Premium in 200x

Data was obtained from the Premium Web Site