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DEMAND FORECASTING IMPROVEMENT
Background
Objectives
Relevant tools and literature
Methodologies
Improvement
Result
Forecast Accuracy is one of based key on business growing performance. The low forecast accuracy will give wrong result for supply planning and an impacted on the company’s business losses.
This project aim is to improve and control lag-2 forecast accuracy by 35% from 56% to 75%.
Stephen Crane World Class Forecasting Accuracy, January 25, 2009
Heizer/Render, Operations Management, Prentice Hall, Inc, 2008
1. Implementation template2. Put Statistical Forecasting3. Sales Adjustments to Statistical
Forecast through market insight4. Forecasting Segmentation base on
forecast ability and volume impact5. Management reporting
1. Process, & Tools2. Statistical Forecasting3. Sales Adjustments to
Statistical Forecast4. Forecasting Segmentation5. Measurement Reporting
Forecast accuracy improve to the level of >75%
CUSTOMER CLAIM HANDLING LEADTIME REDUCTION
Background
Objectives
Relevant tool/Methodologies
Improvement
Initial Result
Customer claim handling lead-time process is a one of critical process in our business. Besides it will be impacted to our customer satisfaction, also directly impacted to our operation processes and cost such as:• Hidden actual cost (hidden company)
of claim cost due to a lot of outstanding claim not be resolved on time.
• Cost of Compensation value due to late claim handling
• Other cost incur due to incorrect claim handling
This project aim is to improve Customer claim handling lead-time process from 93 days to 30 days
To streamline the customer claim process through VSM analysis, simplify logging process, investigation, approval process, weighing, returning process.
1. Lean six sigma DMAIC methodologies.
2. Value Stream Mapping (VSM)
1. Customer claim handling improve by 65% from 93 days to 27 days.
2. Potential cost saving USD 60 K /year
YIELD IMPROVEMENT
Background
Objectives
Relevant tool/Methodologies
Improvement
Result
Market share of SUC & DSC continue to decline and strong growth for MPC market.
In order to expand the business, XYZ has to extend the capability to produce smaller lamp diameter, used in the MPC.
Business Impact : To acquire MPC market to gain
potential USD 1.5M lamps revenue & USD 20 M Flash Module(FM) revenue in Y2008
To continue technological leadership of PFL by offering smallest lamp to the market.
Improve 1.3 mm CP2 yield in mass production from 61% to >85%
1. Lean six sigma DMAIC methodologies.
2. Measurement System Analysis (MSA)
3. Fishbone diagram 4. Design Of Experiment (DOE)
1. Sealing process optimization through Screening DOE with 7 factors & 2 level (1/8 fractional, 2 reps) Reduced to 32 runs
2. Pill pressing pressure experiment
145
0.74
0.72
0.702015 145
145
0.74
0.72
0.702017 991985
52505225
0.74
0.72
0.70
Heat1Time
Mean
Hold1Time Xe1Time
Heat2Time Hold2Time Hold2Temp
Xe2
Main Effects Plot for ResponseData Means
CP2 yield improve to the level of >85%
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500
1,000
1,500
2,000
2,500
3,000
Glass
Saw
ing
Raw
Pin
Was
hing
Glazing
Glass
Was
hing
Glaze
d Par
tW
ashing
Pres
sing
Sealing
KERRY
WASH
ING CVD
50 S
tatio
nTes
ter
Pin
Cut
ting
Vibr
ation
San
dblast
ing
FINSO
NIC
Tinning
FINSO
NIC
The
rmos
ock
ProcessUP
S -K
Pc
Before ImprovementAfter Improvement
LOAD CHART (M/C CAPACITY) KUNIT/WEEK)
PRODUCTION CAPACITY IMPROVEMENT
Background
Objectives
Relevant tool/Methodologies
Improvement
Result
Market demand for Digital Still Camera (DSC) and Mobile Phone Camera (MPC) has been increasing strongly. This trend presents opportunity to increase revenue and gain market share. This project aims to improve production capacity XYZ line from 1.4 Mpcs to 1.9 Mpcs/week
Business Impact :1. Cost Avoidance of investing in new
equipment of US$600K2. PQP hard savings of US$150K/year3. Productivity improvement Labour
Hr/unit by 15% or US$150K
Improve Capacity by 30% line from 1.4 Mpcs to 1.9 Mpcs/week
1. Lean six sigma DMAIC methodologies.
2. Value Stream mapping3. Fishbone diagram 4. Takt Time5. Hypothesis Testing
1. Jig and Fixture Modification
Before after2. Testing Process improvement
1,957
K/week
Value = 0.983, Fail to reject null hypothesis. It means evaluation lot is comparable with control lot statistically
Capacity improve to the level of >1.9 M/week
LABOR PRODUCTIVITY IMPROVEMENT
Project Selection
Objectives
Relevant tool/Methodologies
Improvement
Improve Labor Productivity by 30% from 0.14 Hour/unit to 0.1 hour/unit
1. Lean six sigma DMAIC methodologies.
2. Value Stream mapping3. Fishbone diagram 4. Takt Time5. Solution Development6. Layout
A B C D E1 High Black Stain Defect at Glazing
Process2 5 3 3 2 15(+) 5
2High External Dirty Rate for Device STY 1413 2 5 1 2 2 12 8
3High Scrap Cost at Photo Flash Lamp (PFL) Assembly 3 3 5 3 2 16 4
4 High Chip Off rate at Sawing Process 3 2 4 3 2 14 65 Low Production Capacity for IF IPL
Device5 5 5 2 2 19 2
6 Low Conversion Cost at PFL Line 2 3 2 3 3 13 77 Low MP Productivity at CP3 Cell 5 5 5 5 4 24 1
8High frequency of Long Freeze at Sealing MC 2 3 2 4 4 15 6
9 High Rate of Broken Tray at Sealing 2 2 3 2 2 11 910 High Pre-fabrication Scrap at PFL line 5 4 5 2 2 18 3
SELECTION CRITERIASCORE RANKPROJECT TOPICNO.
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
0
5
10
15
20
25
30
CVD Process Cutting Process 200 Station process
Perc
enta
ge
# O
F O
PERA
TOR
Process
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
0
5
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35
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50
CVD Process Cutting Process 200 Station process
Perc
enta
ge
# O
F O
PERA
TOR
Process
Before improvement
After improvement
36 %
Headcount reduce from 50 Person to 32 person
1. Manufacturing layout with “birdcage” shape.
Result
2. Jig and fixture improvement
