ss overview
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overview of six sigma and its basic conceptsTRANSCRIPT
4 Sigma Process Capability 99.38% Current Standard
6 Sigma Process Capability 99.99966% World-Class
Long-Term Yield
3 Sigma Process Capability 93.32% Historical Standard
The Classical View of Performance
• Six-Sigma is a philosophy: • Why isn’t “99% acceptable” good enough...??
– 20,000 lost articles of mail every hour.– 15 minutes each day of unsafe drinking water.– 5,000 incorrect surgical procedures per week.– 4 or more accidents per day at major airports.– 200,000 wrong drug prescriptions each year.– 7 hours each month without electricity.
History of 6 Sigma• 6 Sigma manufacturing philosophy came from Motorola
They recognised that sufficient process improvement would not occur using a conventional approach to quality. It was developed to help them reduce variation within a process by focusing effort on improving inputs to a process rather than reacting to outputs.
• The process was failing the customer expectations– Traditionally, processes aimed for process capability of 3 to 4
sigma (Cpk=1.0 to 1.33 or 93% to 99.3% acceptable)– The customer received 6200 defective product per million at best– Processes now aim for 6 sigma (Cpk=2)– The customer would receive 3.4 defective product per million
On target, minimum process variation
6 sigma Process Capability “What is it (CPK)”
• 3 Sigma ( Process capability of 1 CPK )
– if the process (lorry) slightly varies then the scrap or damage will occur
• 6 Sigma ( Process capability of 2 CPK )
– if the process (lorry) varies, there will be no scrap or damage
Curbs = required
process tolerances
CPK of 2 (6 sigma)
CPK of 1 (3 sigma)
Variation exists in everything. Even the best machine cannot make every unit exactly the same.
Improved capability, becomes a necessity, due to the need of :
• improved designs• lower costs• better performance
All of this leads to the need of tighter tolerances
This means that the ability to operate to a tight tolerance, without producing defects becomes a major advantage
Understanding Variability
Improvement methodology
On target, minimum process variation
KPIV
Key
Process
Input
Variables
The Process
X1 X2 X3
Controllable Inputs
N1 N2 N3
Inputs:
Raw materials,
components, etc.
Uncontrollable Inputs
Y1, Y2, etc.
Quality
Characteristics:
Outputs
Define
Improvement methodology
• Define terms of reference (Charter the project)– Team / customer / project charter – Brain storming– Mind maps – Affinity diagrams– High level Process Maps – Systematic diagrams / Fault tree– Business Process Mapping
• Define customer requirements (Voice of the customer)– QFD Quality Function Deployment
•To develop a team charter. •To define the customers and their requirements (CTQ Critical to Quality). •To map the business process to be improved
Characteristics
Importance out of 10
Product / customers
Define
• Define terms of reference (charting a project)– What you can deliver to the customer and the support you need from the
customer to facilitate a successful improvement (contract of engagement)
• Brain storming, Mind maps, Affinity diagrams, High level Process Maps, Systematic diagrams / Fault tree, Business Process Mapping– Tools to explore a problem, project or current thinking.– Tools to group those ideas logically.– Then define a route map to improvement, the risk involved and how to
mitigate that risk.
• Define customer requirements (Voice of the customer)– QFD Quality Function Deployment, is a method of defining what the
customer needs, what is critical to there business success & prioritise objectives to meet the customer need.
Measure
Improvement methodology • Voice of the process
– Data Collection - 7 quality tools– Tally charts– Bar charts– Pareto– Run charts– Control charts– Cause & effect– Check sheets
– Evaluate measurement systems• Gauge R&R
• Select measures of performance – Quality Function Deployment
•To measure and understand baseline performance for the current process
Measure
• Voice of the process (7 quality tools)– Tally charts, Bar charts, Pareto, Run charts, Control charts, Cause & effect,
Check sheets.
• Evaluate measurement systems Gauge R&R – Every process has variation and measurement system, tools & cmm are no
exception.– Typical your measurement process needs to be ACCURATE,
REPEATABLE & REPRODUCIBLE to less than 10% of the tolerance you are trying to measure to & proven to be so.
• Select measures of performance – QFD Quality Function Deployment is a method of defining what the
customer needs and what is critical to there business success and prioritising performance measures to support the customers need.
Analyze
Improvement methodology
• Investigate source of variation
(Special cause / Common causes)
– Stratification of data to get information
– Cause & effect
– CP & CPK
– Fault tree
– Contingence analysis
– FMEA (Failure Mode Effect Analysis)
– Design of experiments (DOE)
– Detailed process maps
Seek to:-PrioritiseUnderstandCluesCausesMonitor improvementsLook for signals
Lost
Shoe
Lost
Nail
Lost
Horse
Lost
Soldier
Lost
Battle
Why Battles are LostWhy Battles are Lost
Current Window of Consideration
Cause FailureMode
Effect
FMEA
•Identifies the ways in which a product or process can fail
•Estimates the risk of specific causes with regard to these failures
•Prioritizes the actions that should be taken to reduce the chance of failure
FMEA (failure mode effect analysis)
factors which shift the average
factors which affect variation
factors which shift the average and affect variation
factors which have no effect
A1 A2
D1=D2
B1
B2
C1C2
DOE - (design of experiments)will help us identify...
DOE - (design of experiments) Measure the Process
The Process
X1 X2 X3
Controllable Inputs
N1 N2 N3
Inputs:
Raw Materials,
components, etc.
Uncontrollable Inputs
Y1, Y2, etc.
Quality Characteristics:
OutputsLSL USL
Establish the performance
baseline
Process Step/Input
Potential Failure Mode Potential Failure EffectsSEV
Potential CausesOCC
Current ControlsDET
RPN
Actions Recommended
Load DMF/DMF Load Accuracy Mischarge of DMF Viscosity out of spec 7 SOP not Followed 5
Operator Certification/ Process Audit
5 175Fool proof this process using input from TQL Team
Steam to DICY/Scale Accuracy
Scale Not Zeroed Mischarge DMF 3 Faulty Scale 2 None 9 54Include Daily sign-off of Scale funtion in Shift set-up verification.
Load DMF/DMF Load Accuracy Mischarge of DMF Viscosity out of spec 7 Equipment Failure 2
Maintenance Procedure (SOP 5821)/Visual Check
3 42
Steam to DICY/Scale Accuracy
Scale > 0 Low DMF Charge 3 Water in Jacket 2 Visual Check of Jacket (SOP 5681) 4 24
Steam to DICY/Scale Accuracy
Scale Inaccurate High DMF Charge 3 Tank Hanging Up 2 Visual Check (SOP 5681) 4 24
DOE - (design of experiments) Analyse the Process
The Process
X1 X2 X3Controllable Inputs
N1 N2 N3
Inputs:
Raw Materials,
components, etc.
Uncontrollable Inputs
Y1, Y2, etc.
Quality Characteristics:
OutputsLSL USL
Key Outputs: Variable How Measured When Measured
123
Noise Variables: Variable How Measured When Measured
12345
Controllable Inputs Variable How Measured When Measured
12345
Overall Sampling Plan:
Run Temperature Pressure
1 Hi Hi
2 Hi Hi
3 Lo Hi
4 Lo Hi
5 Hi Lo
6 Hi Lo
7 Lo Lo
8 Lo Lo
3 .52 .51.5
Capab ility Histog ram
4321
3 .0
2 .5
2 .0
1.5
Xbar and R Cha rt
S u b g r
Mea
ns
M U =2 .3 7 6U C L =2 .5 6 8
L C L =2 .18 3
0 .9
0 .6
0 .3
0 .0
Ran
ges
R =0 .5 16 2
U C L =0 .9 6 2 1
L C L =0 .0 7 0 2 7
4321
Last 4 Subg roups
3 .0
2 .5
2 .0
1.5
Subgroup N um ber
Val
ues
41
2 .9 19 5 81.8 3 17 5
Cp: 2 .76 CPU: 2 .99 CP L: 2 .53 Cpk : 2 .53
Capab ility P lo tProc ess To le ranc e
Spec if ic a t ions
StD ev : 0 .181306
III
III
3 .52 .51.5
Norm a l P rob P lo t
C ap ab ility us ing P o o le d S tand ard D e via tio n
DOE - (design of experiments) Improve the Process
Uncontrollable Inputs
The Process
X1 X2 X3Controllable Inputs
N1 N2 N3
Inputs:
Raw Materials,
components, etc.
Y1, Y2, etc.
Quality Characteristics:
OutputsX
X
XLSL USL
LSL USL
ScrewRPM
PrimWdth
Nip FPM
Three Factor Design
DOE - (design of experiments) Control the Process
The Process
X1 X2 X3Controllable Inputs
Inputs:
Raw Materials,
components, etc.
N1 N2 N3Uncontrollable Inputs
Y1, Y2, etc.
Quality Characteristics:
Outputs LSL USL
Check
Lists
Error
Proofing
Work
Instructions
5 C’s
Analyze
• Investigate source of variation (Special cause / Common causes)
– Special cause variation are the one off, occasional and obvious cause of a process / quality problems.
– Common cause variation are the day in day out causes of process problems, because the process is not stable enough, they are hidden (these form 80% of process problems)
– Conventional non-conformance management systems seek to solve special cause variation (e.g. concessions) - but these only represent 15 - 20% of the total variation.
– 6 Sigma addresses all variation.
Improve
Improvement methodology
• Prioritise improvements– Impact Vs Effort
– Brainstorming
– Affinity diagrams
– Solution selection matrix
• Tactical implementation plans– Deliver improvements (reduce variation
systematically)
Customer protectionGet controlImprove process
Improve
• Prioritise improvements – Tool commonly in uses are, Impact Vs Effort, Brainstorming,
Affinity diagrams, Solution selection matrix. – These tools help define the best method to meet the customer
need (as defined in the QFD)
• Tactical implementation plans– Deliver improvements to reduce variation systematically i.e.
make a change, note the improvement and make the next improvement.
– Critical we need to establish that any change is a change for the good.
Control
Improvement methodology
• Control the process– Recover
• Control plans
• Escalation process
– Prevent• Poke yoke (mistake/ error proof)
– Monitor• Control charts
• Checksheets
• Documentation and Standardisation
Control
• Control the process
– Recover, Control plans, Escalation process.
– Prevent by Poke yoke (fool proof the process) to fundamentally remove the rood causes of process variation.
– Monitor, Control charts, Checksheets, Documentation and Standardisation, to ensure that stable process is maintained and that the process does not degrade.
• The objective is to remove the root causes of process variation, management are only left with a few critical input variables in the process that need controlling and not all inputs as before.
Where does 6 Sigma fit with Lean
Lean improvements
6 Sigma improvements
• Lean and 6 Sigma both seek to deliver business improvement
• They are different in the methods used and tools employed– Lean typically address the total
manufacturing environment – 6 sigma typical address the root
cause of process variation
• There is significant benefit from using the most appropriate tools and improvement methodology to meet the customer requirements