usage of six sigma six sigma is not only a learning tool. process improvement refers to a strategy...
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Usage of Six Sigma
• Six Sigma is not only a learning tool.
• Process improvement refers to a strategy of finding solutions to eliminate root causes of performance problems.
--Project --Manufacture
Actuality of Chinese Manufacture
• Defects in Manufacture Process• Assembly Line Defects• Sourcing Defects• Random Defects• Etc.
• Defects in Supply Chain• Transportation Inefficiency• Information Blocking
Defects and Six Sigma Levels
• Defect: anything that does not meet customer requirements.
e. g: a rude reception clerk is providing defective service.
• By measuring customer requirements.• By calculating defective opportunities:
DPMO
Critical ingredients
1. Continuous focus on customer2. Data and Fact-driven *3. Process focus
*get rid of unfounded assumptions.
Asking question: what data I need?
Why data is important?
• The company is growing more complex and the need for information on how things are operating is becoming more critical.
• The more complex of constraints the process have, the more difficult to identify problems by experiences.
Concise and exact way to evaluate process:
DATA
How to implement Six Sigma Project in Chinese Manufacture?
• The initiative of Six Sigma Project• Requirements of Quality by Vendor• The list of Six Sigma projects to fix
defects will be given by Vendor.• Supplier: Chinese manufacturer
• Methodology • Vendor will identify defect in
manufacturing supply chain using SIPOC model.
Identifying and Documenting the Process
• SIPOC
“Big Picture” perspective, additional detail can be added
supplierRaw
materialProcess Output Customer
Heading ThreadingHeat
treatmentDecarburization
Surface Discontinuities
Quality Inspection
N
Y
SIPOC
• Focus on the step (s) where the suspected causes of the symptoms in the Problem Statement
• Process: heading, threading, heat treatment, dec
arburization…
DefineDefine Measure Analyze Improve Control
• Customer requirements: quality of product keep a consistent level.
• e. g: bolts; packaging labels
• Chinese manufacturer should guarantee their products sustain that level
• e. g: take defect rate of 1,100(3 sigma) to 100(6 sigma) level.
Case A:
• Our goal: Find out weaknesses which hidden in the
process then improve it to meet the tolerance requirements.
• Two categories have to be identified: Load tests of bolts Tensile strength requirements
DDefineefine MeasureMeasure Analyze Improve Control
• Studying manufacturing process capability and quality characteristics
• Step 1: Collect data some variations?• Step 2: Make plot graph and diagram increase the power of data analysis
efforts. (EXCEL;MINITAB)
X-Bar chart for subgroup1,2
Sample
Sam
ple
Mean
121110987654321
35000
30000
25000
20000
15000
__X=24640
UCL=34101
LCL=15178
Sample
Sam
ple
StD
ev
121110987654321
10000
7500
5000
2500
0
_S=3559
UCL=11625
LCL=0
Xbar-S Chart of subgroup1, ..., subgroup2
Process capability chart
• Variation in process. It presents some defective samples below the lowest specification
2800024000200001600012000
LBProcess Data
Sample N 12
StDev(Within) 1528.21StDev(Overall) 3853.02
LB 24000
Target *USL *
Sample Mean 22214.2
Potential (Within) Capability
CCpk *
Overall Capability
Z.Bench *
Z.LB *Z.USL *
Ppk
Z.Bench
*Cpm *
*
Z.LB *Z.USL *
Cpk *
Observed Performance
PPM < LB 666666.67
PPM > USL *
PPM Total 666666.67
Exp. Within Performance
PPM < LB *
PPM > USL *
PPM Total *
Exp. Overall Performance
PPM < LB *
PPM > USL *
PPM Total *
WithinOverall
Process Capability of subgroup2
• Qualified bolts (all of samples)
290002800027000260002500024000
LBProcess Data
Sample N 12
StDev(Within) 624.678StDev(Overall) 850.571
LB 24000
Target *USL *
Sample Mean 27065.8
Potential (Within) Capability
CCpk *
Overall Capability
Z.Bench *
Z.LB *Z.USL *
Ppk
Z.Bench
*Cpm *
*
Z.LB *Z.USL *
Cpk *
Observed Performance
PPM < LB 0.00
PPM > USL *
PPM Total 0.00
Exp. Within Performance
PPM < LB *
PPM > USL *
PPM Total *
Exp. Overall Performance
PPM < LB *
PPM > USL *
PPM Total *
WithinOverall
Process Capability of subgroup1
Define Measure AnalyzeAnalyze Improve Control
• Recall the SIPOC diagram, identify areas where the process steps, responsibilities, or outcomes are unclear or produce no-value-added work.
• Pay attention on the first several procedures or work stations. (Bull-whip effect)
Variables in Process
• Z Value:
• Crossing Assembly Line and Transportation Process
• Information and Product Flow
4321 ,,, zzzz
Data/Material flow chart
manufacture
Process 1 Process 2 Process 3
Transportation Process 4customer
Information flow Information flowZ1 Z2 Z3
Product flow Product flow
Z4
• Final inspection data Find data to analysis and calculate.
• We could figure out the defects in every process, for example, in heat treatment .
• Have a hypothesis (Brainstorm), even their theories are wrong, have to be open to the possibility which supported by data.
• Hint: document all the case in process using table, graph, statistic software (MINITAB)…
Define Measure Analyze ImproveImprove Control
• Manufacturer transition diagram.
Customer vendor Chinese manufacture
Raw material supplier
Order
1Order
2order
3
Product
0Product
1Product
2
Supply chain (Markov Model)
Supply Chain Six Sigma Improvement
• Order/Information Flow and Product Flow
• Markovian queue--combine information and product flow
The customer, vendor, Chinese manufacturer and raw material supplier are in the chain where the external environment is a continuous time Markovian chain using data communication networks by order or product flow
Define Measure Analyze ImproveImprove Control
• Profit Margins • Continual Six Sigma improvement to str
eamline and cut the cost out of a supply chain.
Define Measure Analyze Improve ControlControl
• Go back to control chart (X-chart, R-chart ) and review it.
• Control limit recalculation.• Recording all the defective
opportunity.• Keep using control chart within
whole process.
Conclusion
• Six Sigma in manufacture process influences the decision making
• The first step:• Reducing DPMO based on the actual circum
stances by using statistic knowledge• Factors and Results
• The Second Step: • The Markovian model used in Supply Chain
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