Prioritizing Process Improvements
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Transcript of Prioritizing Process Improvements
Prioritizing Process Improvements
Govind RamuJDS Uniphase CorporationASQ World Conference on Quality and ImprovementW07
How effective is your engineering meeting?-
Are you discussing the appropriate topics?
-
Do you have the right audience?-
Do you have actionable discussions?
-
Do you leave the meeting knowing exactly what you need to do?
-
Would you consider your time spent productive and worthwhile?
Group Interaction(3 to 5 minutes)
Meetings -
Are they productive?• Overwhelming information.• Tons of presentations.• Information unrelated to agenda.• Attendees not well prepared.• Delegated attendees.• Too many side conversations.• Blackberry/laptop usage during discussions.• Working on next meeting while listening.• Engaging in arguments on “how to.”• No clear conclusions as to “what to do.”• No clear “actionable”
discussions.
Productivity Survey•
People work an average of 45 hours a week; they consider about 17 of those hours to be unproductive (U.S.: 45 hours a week; 16 hours considered unproductive).
•
People spend 5.6 hours each week in meetings; 69 percent feel meetings aren't productive (U.S.: 5.5 hours; 71 percent feel meetings aren't productive).
•
The most common productivity pitfalls are unclear objectives, lack of team communication and ineffective meetings – chosen by 32 percent of respondents overall (U.S.: procrastination, 42 percent; lack of team communication, 39 percent; ineffective meetings, 34 percent).
Source: The Microsoft Office Personal Productivity Challenge (PPC)Responses from more than 38,000 people in 200 countries
http://www.microsoft.com/presspass/press/2005/mar05/03-15ThreeProductiveDaysPR.mspx
Typical Engineering Meeting
Product by volume
Product volume by year by part #Product yield by part #Product volume and yield
Any actions?
What really matters at the engineering meeting?
Engineers want to know:•
How the process health is doing.
•
What the risks are for internal/external customers.
•
What process parameters to fix.•
What actionable intelligence exists.
The eight-step model for process improvement:
•
Step 1: Identify CTQs and CTPs.•
Step 2: Create a CTQ-CTP relationship matrix.
•
Step 3: Conduct a process FMEA.•
Step 4: Develop a control plan.
•
Step 5: Conduct gage R&R studies.•
Step 6: Set up statistical process control.
•
Step 7: Use process capability & gage R&R to identify improvements.
•
Step 8: Prioritize improvement efforts.
need
VOCI want…
CTQ
CTQ
CTQ
CTQ
CTQ
CTP
CTP
Customer Needs
Business Needs
Product CTQs
Need Drivers CTQs
General Specific
Hard to measure Easy to measure
Customer Drivers
Business
Drivers
CTP
CTP
CTP
Primary Needs
Secondary Needs
Tertiary Needs
CTPs
With right participants, engineering meetings to focus heavily here for improved effectiveness
Currently engineering
meetings may be spending more time
at this level
Step 1: Identify CTQs and CTPs
Some Definitions•
Customer drivers –
quality, cost, delivery, response.
•
Business drivers –
first-pass/rolled throughput yields, work in progress material cost, inventory cost, cycle time, etc.
•
Primary, secondary and tertiary needs –
customer needs from abstract to tactical.
•
CTQ –
critical to quality characteristics of products that customer expects from the product or service.
•
CTP –
critical process parameters that have cause and effect relationship to one more CTQ.
need
VOCI want…
Need Drivers CTQs/ CTCs
General Specific
Hard to measure Easy to measure
CTPs
Product quality
Delivery
Cost
Servicequality
I want tasty pizzaI want hot pizza
I want my pizza to be crispyI want my pizza to have fresh toppings
I want my pizza to be quickerEvery time I get either the wrong pizza or wrong toppings! Not so expensive
Taste
Average order-deliverytime
Selling price
Quantity &right product
Customerrecovery
Complaint handlingtime
Oven process Controltempr. X1 deg +/- 5 deg F
Raw material aging (days)
Vegetable aging (days)
Oven process controltime. X2 min +/- 2 min
Order processing time
Order handling time
Order delivery time (By type & volume)Material cost
Processing cost
Yield %
Margin %
I want to get a replacement for the mistake
Order check
Response time
Replacement time
Step 1: Identify CTQs and CTPs
CTP Vs
CTQ
Screening DOE
EngineeringJudgment
Step 2: Create a CTQ-CTP Relationship Matrix
CTP Vs
CTQExplore InteractionsInterrelationships
Similar idea referenced by Mikel Harry : http://www.isixsigma.com/forum/ask_dr_harry.asp?ToDo=view&questId=82&catId=11
Step 2: Create a CTQ-CTP Relationship Matrix
Step 3: Conduct a Process FMEA
Establish severity,
occurrencedetection scales
Identify process steps
to perform FMEA
Identify failure modes, causes,
effects, current controls,
& risks
FMEA
Identify critical process
variables tomonitor, assign
RPN
Developcontrol
plan (CTQ,CTP)
Creating customized severity, occurrence, and detection scales for the nature of your business or industry can make a difference – one size does not fit all!
Identify the critical process flow of the product lineand hold a team brainstorming session to identify allprobable failure modes, causes, and interim and endeffects.
Document current controls as you would in standardFMEA practice.
Further develop the FMEA to include the severity,occurrence, and detection ratings from your customizedscales.
Calculate risk priority numbers (RPNs) by multiplyingthe severity, occurrence, and detection ratings.Prioritize risks based on RPN values.
(See more detailed flow next slide)
Reference: http://www.qualitytrainingportal.com/resources/fmea/index.htm
Brainstorming all potential causes for failure modes.
Inputs: Process flow charts, manufacturing work instructions,historical process defect Pareto, lessons learned, etc.
Reference: March 2009 QP article, “FMEA Minus the Headache.”
Reference: March 2009 QP article, “FMEA Minus the Headache.”
Populating the FMEA table with discussion outputs.
Step 4: Develop a Control Plan
Inputs from Step 1 (Identify CTQs and CTPs) and FMEA recommended actions corresponding to CTQ, CTP merge here.
Measurement system that may require R&R –
ensure if adequate before
proceeding with SPC.
Back to Basics•
Let us refresh our memory on some basic definitions:–
Repeatability: Variation in measurements obtained with one measuring instrument when used several times by an appraiser (operator) while measuring the identical characteristic on the same part.
–
Reproducibility: Variation in the average of the measurements made by different appraisers (operators) using the same gage when measuring a characteristic on one part.
–
Process capability compares the output of an in-control process to the specification limits by using capability indices (Cp, Cpk). The comparison is made by forming the ratio of the spread between the process specifications (the specification "width") to the spread
of the process values, as measured by 6 process standard deviation units (the process "width").
–
Process performance indices (Pp, Ppk) basically try to verify if the sample generated from the process is capable to meet customer CTQs (requirements). Process performance differs from process capability and is only used when process control cannot be evaluated.
Step 5: Conduct Gage R&R Studies
SGage
5.15 SGage
Gage repeatability
0.5%0.5%
Standard deviation of gage (one appraiser)
= =
∑i 1
n
Sn - 1
f i −( )X Xi
2
Definition of standard deviation:
Width
99% of measurements fall in the gage repeatability
range
X
Appraiser 1Appraiser 3
Appraiser 2
Standard deviation of gage (more than one appraiser)
(Back to Basics)
Measurement Systems Analysis (MSA)
Step 5: Conduct Gage R&R Studies
Sources of Variation
PartOperatorBy2
Operator2
ityRepeatabil2
Product2
Total2 σσσσσ +++=
100.00%
Overall Part to Part Repeatability Operator Operator by Part
Reproducibility (Back to Basics)
Reference Minitab Help: GR & R Study (Crossed)- ANOVA Method
Step 5: Conduct Gage R&R Studies
How can a measurement system contribute in accepting BAD product and rejecting GOOD product ?
LSL USL
True measurement of the product
Accepting BAD product Rejecting GOOD product
Operator variation(E.g., reading from analog panel)+/-
10 Deg F
Oven instrument variation+/-
5 deg F
True measurement of the product
(Back to Basics)
Step 5: Conduct Gage R&R Studies
Effects of Sources of Variation
Product
Overall production variation
Target
What wasproduced
What wasobserved
Process adjustment
Operator variation—reading from analog panel
Oven instrument variation
(Back to Basics)
Step 5: Conduct Gage R&R Studies
Step 6: Statistical Process Control (SPC)
Assign Unique ID XXX Man
Machine
Material
Method
Environment
+
+Extended free text about
Special cause
OCAPData base
Inputs from FMEABrainstorming
Short-term Vs Long-term Capability
LSL USLTarget
Time 1
Time 2
Time 3
Time 4
Over long term conditions, a “typical” process will shift and drift by approximately 1.5 standard deviations*.
“Short-term capability” (Cp, Cpk)
“Long-term performance” that includes changes to material, multiple shifts, Operators, environmental changes (Pp, Ppk)
(Back to Basics)
Step 6: Statistical Process Control (SPC) – Calculate Cp, Cpk if the process is stable.
Baseline Capability
Oven temperature
Oven time
Raw material aging Vegetable aging
Order processing time
Order handling time
Order replacement time
Order handling time
Order response time
Pp= 0.8 Ppk= 0.6 Pp= 1 Ppk= 0.93 Pp= 1 Ppk= 1
Pp= 0.8 Ppk= 0.7 Pp= 0.8 Ppk= 0.8 Pp= 0.6 Ppk= 0.6
*Pp= 0.9 Ppk= 0.7 *Pp= 1.2 Ppk= 1.1 *Pp= 1.3 Ppk= 1.2* Data transformed
Baseline GR&R
Step 7: Using Process Capability and GR&R to Identify Improvements
Capability & GR&R Grid
% G
R&
R*
Cpk/Ppk*
Low
High
Low High
>24%
<24%
<1.1 >1.1* GR&R 24%, Cp, Cpk 1.1 are an example. Decide what is acceptable for your organization.
Step 7: Using Process Capability and GR&R to Identify Improvements
Scenario — High GR&R + Low Cp/Pp & Cpk/Ppk
LSL USL
True value of the part
Accepting BAD product Rejecting GOOD product
Instrument variationrepeatability
Operator variationreproducibility
Instrument variationrepeatability
True value of the part
Operator variationreproducibility
Processshift
% G
R&
R
Cpk/Ppk
Low
High
Low High
% G
R&
R
Cpk/Ppk
Low
High
Low High
(Back to Basics)
Scenario — Low GR&R + Low Cp/Pp & Cpk/Ppk
LSL USL
True value of the part
Accepting BAD product Rejecting GOOD product
Instrument variationrepeatability
Operator variationreproducibility
True value of the part
Instrument variationrepeatability
Operator variationreproducibility
ProcessShift
% G
R&
R
Cpk/Ppk
Low
High
Low High
% G
R&
R
Cpk/Ppk
Low
High
Low High
(Back to Basics)
Scenario — High GR&R + High Cp/High Cpk
LSL USL
True value of the part
Accepting BAD product Rejecting GOOD product
Instrument variationrepeatability
Operator variationreproducibility
Instrument variationrepeatability
True value of the part
Operator variationreproducibility
% G
R&
R
Cpk/Ppk
Low
High
Low High
% G
R&
R
Cpk/Ppk
Low
High
Low High
(Back to Basics)
Scenario — Low GR&R + High Cp/Pp & Cpk/Ppk
LSL USL
True value of the part
Accepting BAD product Rejecting GOOD product
Instrument variationrepeatability
Operator variationreproducibility
True value of the part
Instrument variationrepeatability
Operator variationreproducibility
% G
R&
R
Cpk/Ppk
Low
High
Low High
% G
R&
R
Cpk/Ppk
Low
High
Low High
(Back to Basics)
Capability & GR&R Grid
% G
R&
R
Cpk/Ppk
Low
High
Low High
CTQ1CTP3
CTQ2CTP2
CTQ3
CTP1
Now that we know the baseline data of performance indices/capability & GR&R of our pizza-making CTQ & CTP, let us place them in the appropriate quadrants.
Step 7: Using Process Capability and GR&R to Identify Improvements
Step 8 - Prioritizing Improvement Efforts (Process Health Card)
•If new test station/equipment added, operator changed, equipment
overhauled, new GR&R study is required. If no changes, 6 months
frequency ofGR&R monitoring is a good practice.** If there has been sudden change in process variation (for good or bad), extended period of lack of stability, a new study has
to be conducted and control limits recalculated. If no changes, 6 months frequency of review of control limits is a good practice.
CTQ: critical to quality characteristics. CTP: critical to process parameters.
Relationship between CTP and CTQ to be established up front.
Pro
duct
Pro
cess
CTQ1
CTQ2
CTQ3
CTP1
CTP2
CTP3
LCL UCL Stability** Cp/Pp Cpk/Ppk
DateCL
ESTB.GRR%DateGRR*
Alpha/Beta Risk%
GRR/ CL Next due
Date
Significant Moderate Weak
CTQ 1 2 3
1
2
3
CTP
Relationship
01/07
01/07
01/07
01/07
01/07
01/07
07/07
07/07
07/07
07/07
07/07
07/07
37%
8%
25%
7%
12%
25%
01/07
01/07
01/07
01/07
01/07
01/07
20
1.30
15
200
1.5
1.7
24
1.80
18
208
1.7
2.0
NO
YES
NO
YES
YES
NO
0.8
0.9
1.2
1.3
1.00
0.95
0.6
0.88
1.15
1.25
0.92
0.82
Alpha/Beta errors can be obtained from statistical software misclassification feature, or by using simulation software.
Data query/retrieve (real time –
where possible)
Validate data sequence
Control chart
Identify special causes (If not stable)
Summarize the Cp, Cpk, Pp, Ppk, GR&R%,
false acceptance, false reject
Establish severity,
occurrencedetection scales
Identify process steps
to perform FMEA
Identify failure modes, causes,
effects, current controls
& risks
Identify equipment
Plan GR&R experiment
Measure capability Cp/Cpk
(if stable)
Cp, Cpkacceptable?
By process date?By lot sequence?By measure date?
SPCFMEA GR&R
Yes
Analyze data
Measure GR&R
Identify critical process
variables tomonitor, assign
RPN
Developcontrol
plan (CTQ,CTP)
Estimate process performance indices
Healthcard
Prioritize improvement efforts
CTQ vs CTPmatrix
Continue monitoringstability & process capability
No
Triggering Actionable Discussions
•
Out of all CTQ and CTP from a given product line, prioritize a vital few for improvement actions. In this example, CTQ1 and CTP3 are prioritized.
•
By improving CTQ1 and CTP3, we can reduce the producer/consumer risks to a set goal acceptable by customers and manufacturing.
•
Improve gage R&R to <10%. Improve process capability indices >1.5.
•
Move items from red, yellow, and blue zones to green based on prioritization.
One might ask…•
Why go through these process steps? Why not focus on low process capability to start with?
•
Answer: This process helps …–
Understand whether the CTQs and CTPs that are measured are traceable to customer needs.
–
Prioritize improvements using the CTQ-CTP relationship matrix.
–
Review priority for improvement in relationship to measurement capability. (As a containment, organizations would rather risk losing yield than sending nonconforming products to customers. 1% of incorrectly accepted products is 10,000 PPM.)
About Engineering Meetings•
Meeting discipline issues narrated in this presentation are common to any organization in general and not targeted on any specific organization.
•
There is more to engineering meetings than Cpk and Gage R&R: e.g., engineering changes, machine maintenance issues, budget control, etc.
•
This presentation is targeted to help quality professionals and engineering professionals involved in quality improvement and does not suggest replacing the entire engineering meeting.
Acronyms & Definitions•
CTQ: critical to quality (characteristics)
•
CTC: critical to cost/customer (characteristics)•
CTP: critical to process (parameter)
•
GR&R: gage repeatability & reproducibility•
LSL: lower specification limit
•
USL: upper specification limit•
FMEA: failure mode effects analysis
•
RPN: risk priority number
•
Alpha risk: probability of rejecting good products•
Beta risk: probability of accepting bad products
Acknowledgements, References, & Bibliography•
Acknowledgements:–
Ms. Noel Wilson, ASQ -
Review, feedback, and support.–
Mr. Steven Hunt-
@ Risk Misclassification & Simulation.–
Ms. Cathy Akritas, Minitab Inc-
Help with Misclassification macro.–
Mr. Ed Russell, Mr. John Noguera, Mr. Andrew Sleeper -
Suggestions and guidance for Misclassification Simulation.
•
References:–
Concepts for R&R Studies, ASQ Press, by Larry B. Barrentine.–
FMEA Minus the Headache,”
QP, April 2009, by Govind Ramu.–
Measurement Systems Analysis Manual,AIAG.–
MINITAB 15 Help Menu. •
Bibliography:–
http://www.isixsigma.com/forum/ask_dr_harry.asp?ToDo=view&questId=82&catId=11–
AIAG Statistical Process Control –
SPC–
http://www.onesixsigma.com/crystalball/Misclassification-Rates-in-Measurement-Systems-
Analysis-Gauge-RR-01011970
–
http://www.qualitytrainingportal.com/resources/fmea/index.htm
55
Questions and AnswersThanks:Govind Ramu
Probability of rejecting good products and accepting bad products for Ppk=0.43 and GR&R 30%: E.g., CTQ1 -
Red Quadrant
Incorrectly accepted = 12.02% (Beta Risk) Incorrectly rejected = 1.80% (Alpha Risk)
Reference AIAG Manual Measurement System Analysis 3rd Edition- Pages 16-22
45
Note:
The exact percentage of errors was calculated simulating the distribution with 100,000 random data points using @ Risk software
and MINITAB Macro.
Probability of incorrectly rejecting good parts
Probability of incorrectlyAccepting bad parts
Probability of rejecting bad parts8.99% both tails
Probability of accepting Good Parts 88.08%
Product Distribution
GRR Error Distribution
Probability of rejecting good products and accepting bad products for Ppk=0.43 and GR&R 10%: E.g., CTQ2 -
Yellow Quadrant
Reference AIAG Manual Measurement System Analysis 3rd Edition- Pages 16-22
Incorrectly accepted = 5.22% (Beta Risk) Incorrectly rejected = 0.68% (Alpha Risk)
Probability of rejecting bad parts9.77% both tails
Probability of accepting Good Parts 89.28%
Probability of incorrectly rejecting good parts
Probability of incorrectlyAccepting bad parts
Product Distribution
GRR Error Distribution
Note:
The exact percentage of errors was calculated simulating the distribution with 100,000 random data points using @ Risk software
and MINITAB Macro.