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Corrective And Preventive ActionsC.A. are intended to determine the cause of nonconformance's that have been detected and to find a solution, while P.A. is a plan to stop the problem from happening again in the future. Several tools were develop to help structure and document the necessary steps to apply CAPA. The tools I am most familiar with are DMAIC (Define, Measure, Analyze, Improve, Control), Rubric, and 8D.
DMAIC is a tool I learned to used during Black Belt training. DMAIC is a process one goes through to state the problem (Define), applying Metrics & collecting data to find the various causes (Measure), taking the data and applying different techniques to investigate and examine the data to find the root cause (Analyze), finding and applying the solution (Improve), then apply the necessary steps to either monitor or prevent the problem from reoccurring (Control).
Rubric is a tool I learned while at Abbott Diagnostic. Basically they break down the CAPA steps into 6 levels called 1) Identification, 2) Evaluation, 3) Resolution, 4) Investigation, 5) Implementation, and 6) Effectiveness.
8D is a quality tool that provides scientific facts to details of problems and solutions and presents a guideline to get to the root of the problem & verification the solution actually works.
CAPA - DMAIC
Project / Belt ManagementGary Jing 10/26/05 Slide 2
11 Sep 0311 Sep 03
Enter %Enter %
Enter dateEnter dateEnter dateEnter date
DefineDefine
1
MeasureMeasure
2
AnalyzeAnalyze
3
ImproveImprove
4
ControlControl
5
Key DeliverablesRequired• List of Project CTQs• Team Charter• High Level Process Map
(COPIS)
Tools That May Help• Project Risk Assessment• Stakeholder Analysis• High Level Project Plan• In Frame/Out of Frame• Customer Survey Methods
(focus groups, interviews, etc.)
• Elevator Speech
Required• Data Collection Plan • CTQ Worksheet:
Operational definition, Specification limits, target, defect definition for Project Y(s)
• Measurement System Analysis
Tools That May Help• QFD• Gage R&R/Attribute R&R• Detailed Process Map• FMEA• Pareto Analysis
Required• Baseline of Current Process
Performance• Graphical analysis of output (Y) • Statistical Goal Statement for
Project• List of Statistically Significant
Xs
Tools That May Help• Six Sigma Process & Product
Reports• Benchmarking• Fishbone Diagram• Hypothesis Testing• Regression Analysis
Required• List of Vital Few Xs• Transfer Function(s)• Optimal Settings for Xs• Confirmation Runs/Results• Tolerances on Vital Few Xs
Tools That May Help• Design of Experiments• New Process Maps• FMEA on new process• Process Modeling• Brainstorming
Required• MSA Results on Xs• Post Improvement
Capability• Statistical Confirmation of
Improvements • Process Control Plan• Process Owner Signoff
Tools That May Help• Control Charts• Hypothesis Testing• CAP Plan• Documentation/SOP
Overall Project Completion Percentage
Key Steps: Enter dateEnter date Enter dateEnter date Enter dateEnter date
DMAICProject
Progress Sheet
DMAICProject
Progress Sheet
Step A: Identify Project CTQs
Step 1: Select CTQ Characteristics
Step 4: Establish Process Capability
Step 7: Screen Potential Causes
Step 10: Define & Validate the Measurement System on Xs
Step B: Develop Team Charter
Step C: Define Process Map
Step 2: Define Performance Standards
Step 3: Measurement System Analysis
Step 5: Define Performance Objectives
Step 6: Identify Variation Sources)
Step 8: Discover Variable Relationships
Step 9: Establish Operating Tolerances
Step 11: Determine Process Capability
Step 12: Implement Process Control
Project Name:
Kick Off Date:
X
X
Define – Helps priorities a problem by using the following matrix template. Put together a team of qualified individuals to develop a problem statement that have the following characteristics:
1. Problem exist – seen, magnitude, impact to customers
2. Important to customers (VOC)
3. Financially beneficial
4. Problem statement focuses on symptoms not solutions.
5. Identify key stakeholders.
6. Stipulate goal statement by identifying key output metrics to be improved.
1. Show targeted completion dates & milestones.
7. Verify Project Scope by achieving project objectives within planned timeframe.
1. List key process output variables such as time, quality, cost metrics.
CAPA - DMAIC
Measure – to understand the current state of the process you need to collect reliable data on process, speed, quality, failures, costs, capability, SPC, etc. to expose the underlying cause of problems.
Key Steps:
1. Create & validate a value stream map to confirm current process.
2. Identify key process outputs & inputs (KPOV & KPIV) variables relevant to project.
3. Create a data collection plan and a data analysis plan to verify what kind of tools can be used for the type of data collected.
4. Collect data to establish baseline.
5. Calculate lead times and process capability.
6. Use Measurement System Analysis to make sure your data is valid. use one of the following analysis: Bias, Stability, Kappa, Gage R&R, & Discrimination.
CAPA - DMAIC
CAPA - DMAICAnalysis – to pinpoint & verify causes affecting the KPIV & KPOV connected to project.
Key Steps:
1. Identify value-add and non-value-add using value stream mapping.
2. Calculate Process Cycle Efficiency (PCE) to find how much improvement is needed.
3. Analyze process flow by identifying bottlenecks, constraints, fallout & rework points.
4. Analyze data collected in Measure.
5. Generate hypothesis to explain potential causes using, C&E (fishbone), FMEA.
6. Zeroing in on the problem using 5 W’s, 5 M’s, Pareto, Hypothesis testing (Ha & Ho).
7. Collect additional data to verify root causes using Ha & Ho, ANOVA, Scatter plots.
CAPA - DMAICImprove – implement tested solutions to problems found in Analysis.
Key Steps:
1. Develop potential solutions by using the caused-and-effect relationship (from Analysis) to identify a wide range of potential solutions.
2. Evaluate, select, & prioritize best solutions.
3. Develop “To Be” value stream map by revising the existing VSM to reflect what the process will look like after the changes are executed.
4. Develop & implement pilot solutions.
5. Confirm achievement of project goals.
6. Confirm improvements by reviewing metrics of controls and capability.
CAPA - DMAICControl – in order to complete project work & hand off improvements to process owners one must
implement metrics or monitoring system to make sure process problems do not return.
Steps:
1. Develop supporting methods and documentation to sustain full-scale implementation.
2. Lock in performance gains my using mistake-proofing measures to prevent people from performing old process steps.
3. Monitor implementation using metrics.
4. Develop Process Control Plan and hand it to process owner.
5. Audit the results by confirming measures of improvements and assign dollar figures were appropriate.
6. Finalize project by document ideas about where company could apply the methods and lessons learned from this project. Hold Control Gate Review and go over achievements.
7. Document improve processes, process maps, mistake proofing process controls, increase performance and quality.
Design For Six Sigma (DFSS)
DMADV – Define Measure Analyze Design Verify - strives to generate a new process where none existed, or where an existing process is deemed to be inadequate and in need of replacement. DFSS aims to create a process performance of around 4.5 sigma or better with the end in mind of optimally building the efficiencies of Six Sigma methodology into the process before implementation; traditional Six Sigma seeks for continuous improvement after a process already exists.
DFSS seeks to avoid manufacturing/service process problems by using advanced Voice of the Customer techniques and proper systems engineering techniques to avoid process problems at the outset (i.e., fire prevention). When combined, these methods obtain the proper needs of the customer, and derive engineering system parameter requirements that increase product and service effectiveness in the eyes of the customer.
DFSS is an approach and attitude towards delivering new products and services with a high performance as measured by customer critical to quality metrics. Some of the main tools include QFD - Quality Function Deployment, FMEA, DOE, & simulation techniques. DFSS methodologies are about a wider, deeper and more integrated approach to commercial design, which involves everyone in the process as well as the customer to deliver a better product/service and final implementation
DEFINE - This step is virtually identical to the DMAIC process. It focuses on identifying the size and scope of the opportunity, while making sure that DMADV is the best fit for the situation. It's also about building the most effective, efficient team with clearly defined goals supported with a well-thought out project plan.
MEASURE - While this step in the DMAIC process measures the performance of the current process, DMADV focuses on measuring (and quantifying) the expectations and requirements of customers. The team is building a a product/service profile against which design alternatives will be compared. The Six Sigma targets set in this step will define the success or failure of the DFSS project.
ANALYZE - This step combines the practicality of turning customer requirements into product/service functions with the creativity of generating and testing new concepts to fulfill those functions. The team must also create a design of a new production process along with its capabilities. A number of iterations are usually needed to get these process concepts up to Six Sigma level performance, even on paper. This is the step of small-scale experiments with very rapid PDCA cycles.
DESIGN - The team (torture tests) the most promising product/service design(s) by developing detailed production plans and their likely failure modes. Based on more realistic picture of process capability, the team must make tradeoffs between product/service features and functions and the level of reliability that production processes can consistently deliver. This is also where process control plans are designed and built right into the proposed production process.
Design For Six Sigma (DFSS)
VALIDATE - Since DMADVI is a (from-the-ground-up) process, small-scale experiments make the most sense for two reasons: First, pilot implementations minimize both the cost and the risk of trying something entirely new. Secondly, the PDCA cycle can be turned very quickly, making it possible to dramatically accelerate the team's learning curve. Once performance gaps have been uncovered and root causes eliminated, the team must design the quality management and production control systems needed to move to full-scale implementation. Finally, the team must create a transition schedule to the full-product production/service delivery.
Design For Six Sigma (DFSS)
Pareto Charts
Count 215 9 6 5 3 2 2 2Percent 4.332.6 19.6 13.0 10.9 6.5 4.3 4.3 4.3Cum % 100.032.6 52.2 65.2 76.1 82.6 87.0 91.3 95.7
Causes
Othe
r
Supp
lier w
aiting
E. Par
ts
Confirm
ation
Fro
m Sup
plier
Bad Pa
rts
Supp
lier L
ate
Commit D
ate Wro
ng
Lead
Tim
es Not
Upda
ted
Not F
ollow
ing up on
SO
Assig
n &
Proc
ess
50
40
30
20
10
0
100
80
60
40
20
0
Count
Perc
ent
Pareto Chart of Causes
A Pareto charts are use to graphically ranks defects from largest to smallest, which can help you prioritize quality problems and focus improvement efforts on areas where the largest gains can be made. Stat>Quality Tools>Pareto chart.
This chart illustrates the number and type of causes for late Sales Orders (Black Belt).
Cause & Effect (Fish Bone)
ShipmentsLate
Purchase
Supplier
Inspect
SAP
Shipping
ServiceCustomerReceive Movement
Lead Time
Customer Service
Shipping
SAP
Internal Supplier
Placing on Shelves
Warehouse to stock
Data entrynot realCommit Date -
corporateFaxing to
Stock LevelWrong
PartCan't find
Transaction
Packing
Unpacking
Movement
Shipping
Inspection
Receiving
Ordering
backBad Part feed
PrintsIn adequate
Unnecessary
CommunicationNo
OrderUnconfirmed
Waiting for Parts
Delays
verifiedLead times not
updatedLead Times not
not setPriorities of orders
SONo following up on
SupplierConfirmation from
ReportAssign & Process
OrdersPlan
UpdatedNot
Customs
RealNot
Date
Possible Causes Of Late Shipments
5 M’s – Root Causes
Hypothesis Testing
PopulationParameters
Mean μStandard Deviation σProportion % π
P-value – If the P value is >.05, then Ho is true and any value between U1 - U2 is consider insignificant (process change was insignificant). However, if the P value is <.05 then reject Ho and Ha is true and the value between U1 - U2 is consider significant (Process change was significant.)
Steps for Hypothesis testing:1. State Practical problem with Ho & Ha2. Test for normality: Stat>Basic Statistics>Normality or Stat>Basic Statistics>Graphical Summary3. State Alpha 4. Determine appropriate test: 1-sample T, 2-sample T, Z, Paired T5. Find P value and make decision (if p-value <.05 then reject Ho)
Hypothesis testing – is just a claim about a parameter. Such as Average luminosity is 2650 lumens. It determines whether a particular value is contained within a calculated range (CI – confidence interval . A common testing application is to see if two means are (U1 &
U2) equal. Or to verify this process change will reduce particle count defect. Or this project will reduce product variation .
Assumptions are: Normally distributed data, random samples, independence between & within samples.
Ho – Null Hypothesis – U1 = U2 or U1 - U2= 0 We assume the null Hypothesis is true unless we have evidence to prove otherwise.Ha – Alternate Hypothesis - U1 U2 or U1 - U2 0Uses:1. Allows us to determine statistically whether or not a value is cause for alarm.2. Tells us whether or not two sets of data are truly different (with a certain level of confidence)3. Tells us whether or not a statistical parameter (mean, standard deviation, variance, proportion, etc.) is different from a value of interest.4. Allows us to assess the “strength” of our conclusion (our probability of being correct or wrong.)5. Use when you need to compare performance level of a mean, variance, or proportion.
Sample 1 & 2
==
ANOVAANOVA – Analysis Of Variance – is used to compare 3 or more samples to each other to see if any of the sample means is statistically different from the others. It is used to analyze the relationships between several categorical inputs (KPIVs or factors) & one continuous output (KPOV). The samples (Values describing the factors) are referred to as levels or treatments. One-Way is used with a 1 factor & several levels. Two-Way is used with 2 factors & several levels. ANOVA.doc:
Step 1: State Practical Problem: Is the mean response (KPOV) the same for the 4 different materials ANOVA Material.mpj (1 factor – material & 4 levels of material).
Step 2: Assumptions – a) The means are independent (randomize) & adequate sample sizes. b) Data collected must be normal(residuals plots). c) Population variances are equal across all factor levels. Using the data from equal variance.mpj test for equal variance by Stat>ANOVA>test .
4
3
2
1
200150100500
Mate
rial
95% Bonferroni Confidence Intervals for StDevs
Test Statistic 0.08P-Value 0.994
Test Statistic 0.01P-Value 0.999
Bartlett's Test
Levene's Test
Test for Equal Variances for Response Reponse = Response, Factor = Material, Confidence = 95.
The graph illustrates the variances are relatively equal & balanced. Dots represents overall mean. P value above .05 & therefore can use a One-Way ANOVA. If not equal, use Stat>ANOVA>General linear
Step 3: State Hypotheses
Ho: μ1 = μ2 = μ3 =μ4
Ha: μ1 ≠ μ2 ≠ μ3 ≠ μ4
ANOVA (continue)
Step 4: Construct ANOVA table
Stat>ANOVA>One way
Input: Response=Response, Factor=material,
√ = store residuals & store fits
One-way ANOVA: Response versus Material
Source DF SS MS F PMaterial 3 2378 793 0.41 0.747Error 16 30840 1928Total 19 33218
S = 43.90 R-Sq = 7.16% R-Sq(adj) = 0.00%
Individual 95% CIs For Mean Based on Pooled StDevLevel N Mean StDev ---+---------+---------+---------+------1 5 9860.6 40.0 (-------------*-------------)2 5 9842.4 44.6 (-------------*-------------)3 5 9868.8 46.2 (-------------*------------)4 5 9869.4 44.6 (-------------*-------------)
---+---------+---------+---------+------ 9810 9840 9870 9900
Pooled StDev = 43.9
P value >.05 Or
F<S = .41 < 43 then Ho: µ1 = µ2 =
µ3 =µ4
ANOVA (continue)
100500-50-100
99
90
50
10
1
Residual
Perc
ent
9870986098509840
80
40
0
Fitted Value
Resi
dual
806040200-20
16
12
8
4
0
Residual
Fre
quency
2018161412108642
80
40
0
Observation Order
Resi
dual
Normal Probability Plot Versus Fits
Histogram Versus Order
Residual Plots for Response Step 5. Recheck the assumption made in Step 2 using Residuals Plot.
a) Are the means independent? Should display no trend or repeated pattern. This shows pattern & violates assumption
b) Is the data normal? Points should hug the diagonal line and they don’t. Histograms (bell shape) provide a visual check for normality. In this case it does not.
c) Are the variance equal cross all factor levels? Equal # of points should be on each side of the 0 line & they aren’t.
b c
b a
Step 6: The P-value of 0.747 (on previous page) > .05 & F<S indicates the Ho is true where μ 1 = μ2 = μ3 are equal.
Step 7: But the Assumption for the residuals do not hold and therefore cannot draw a reliable conclusion from the analysis.
ANOVA (continue)
8D – Problem Solving D0: The Planning Phase: Plan for solving the problem and determine the prerequisites.
D1: Use a Team: Establish a team of people with product/process knowledge.
D2: Define and describe the Problem: Specify the problem by identifying in quantifiable terms the who, what, where, when, why, how and how many (5W’s, 2H) for the problem.
D3: Developing Interim Containment Plan Implement and verify Interim Actions: Define and implement containment actions to isolate the problem from any customer.
D4: Determine and Identify and Verify Root Causes and escape points: Identify all potential causes that could explain why the problem occurred. Also identify why the problem has not been noticed at the time it occurred. All causes shall be verified or proved, not determined by fuzzy brainstorming.
D5: Choose and verify Permanent Corrective Actions (PCAs) for root cause and Escape point : Through pre-production programs quantitatively confirm that the selected corrective actions will resolve the problem for the customer.
D6: Implement and validate PCAs: Define and Implement the best corrective actions.
D7: Prevent recurrence: Modify the management systems, operation systems, practices and procedures to prevent recurrence of this and all similar problems.
D8: Congratulate your Team: Recognize the collective efforts of the team. The team needs to be formally thanked by the organization.[1][2]
Identification – is where the Event is broken down into detail by collecting data describing the Event.
The following questions are asked and answered:
1. What object or item is involved (e.g. name, batch #, Line, Lot #, description of item)
2. What is the event/problem or malfunction?
3. Where is the event/problem observed (geographically describe).
4. When did the event/problem occur (date, time)
5. What documents #’s, name, revision, & revision date are associate with problem.
Note *:
This does not include assignment of blame, cause, or offer a solution. It also verifies initial timing was or was not met (discovering the problem or event and notifying supervisor).
CAPA – Rubric - Identification
CAPA – Rubric - EvaluationEvaluation – breaks down identification further by collecting more data
The following questions are asked:
1. Identifies additional items impacted by the event (i.e., by date range, lot #, asset #, location, p/n, line) and how each item was impacted. Or why no additional items were impacted.
2. Documents whether or not all items impacted by the event were contained, not contained, or justified why containment was not necessary.
3. Document impact level and justification for the level. Include Frequency and Severity.
4. Documents an investigation or justifies why no investigation is needed.
CAPA – Rubric - InvestigationInvestigation – Create a Problem Statement by reviewing how the
requirement / expected result for the event/problem was not met by answering the following:
1. What object or item is involved (name, description, batch #, line #)?
2. What is the problem or malfunction?
3. Where is the problem observed?
4. When did the problem occur?
Collect / Analyze Data:1. Collect background information to understand problem more clearly
2. Doc. the 5M’s (man, machine, material, method, mother nature).
3. Collect evidence of data that supports impact level.
4. Doc. historical details by examining other data sources (CAPA, audits) related to event.
CAPA – Rubric - InvestigationRoot Cause Analysis:
1. Determine and document possible causes thoroughly using tools (fish bone, pareto, DOE, etc.).
2. Narrow causes to find root by testing and providing supporting evidence that documents justification to eliminate or retain cause.
3. Provide a clear, concise statement of the identified cause once root cause had been identified.
4. Once causes have been identified, evaluate and describe where else the event/problem may occur for the following:
1. Supply Chain, similar products/processes/equipment, quality systems related to the event/problem.
CAPA – Rubric - ResolutionResolution – is the plan used to resolve the impacted items.
The following steps are performed to address all impacted items.
1. Doc. all impacted item and disposition items for destruction, rework, continue use, return to supplier.
2. Doc. with justification if no corrective action is necessary for impacted items.
3. Identify all impacted items that will be corrected.
4. List actions taken to correct impacted items & how it will remedy the nonconformance.
5. List criteria that will be used to confirm correction was successful.
6. Who/what functional area will perform the correction.
7. When will correction be completed (due date).
CAPA – Rubric - ImplementationImplementation - is the process of carrying out corrective and preventive
actions. The list below shows what actions should be preformed to document and improve effectiveness.
1. Perform pilot of corrective action to make sure corrective action is successful and does not effect any other parts/products/process.
2. List process needed to prevent/mitigate recurrence/occurrence.
3. Identify how this action addresses the identified cause.
4. Identify functional area that will be performing the procedure to prevent recurrence?
5. When and where will the action be implemented?
6. Address any concerns that the preventive measure does not create any adverse consequences.
7. List any interim actions or modes of control that were applied pending implementation of corrective and preventive action if applicable.
CAPA – Rubric - EffectivenessEffectiveness - identifies specific criteria to verify the elimination or
reduction of causes with the steps listed below:
1. List methods of data collection (batch record review, complaints, ER, etc.).
2. Methods of analysis with evaluation criterion
3. Minimum sample size (i.e., lot, assets, etc.) & duration with justification.
4. Consider if the action created adverse consequences.
5. If no effectiveness plan was required provide justification.
Continuous Lean Improvement is a principle taught to employees on how to think lean while performing their assigned duties. It teaches what waste is and ways to reduce or eliminate it. Reducing Takt time or improving quality are means of how to make improvements.
Companies usually run using either a Push or Pull type of production or a combination of the two.
Pushed Production is based on forecast and extra quantities and inventory and can lead to waste and can cause many problems if customer decides they no longer need product.
Pull Production is based on customer orders and the amount they need - no extra quantities, no inventory (reduce waste).
One Piece Pull - balanced work & material flow - (no waiting, material is not backing up at anyone particular station).
One Piece Pull and Pull Production is what a company should strive for.
Continuous Lean Improvement
Continuous Lean ImprovementCurrent Status:
• Before any improvements are made one must define where they are currently by invoking and studying various metrics that can provide data to determine if the process is in Control, Capable, Normal, and within the assigned cycle time. This should be done at each station. If any of these parameters are not within spec., improvements should be made in these areas to eliminate problems.
Steps Toward Improvement:
1. Create a Value Stream Map (VSM). This map will identify value-added and non-value-added items. It’s basically a detail flow chart in conjunction with the amount of time taken for each steps needed to produce a part.
2. Calculate the total Lead Time.
3. Calculate Process Cycle Efficiency.
4. Locate and quantify the time traps and capacity constraints.
5. Compute the Workstation Turnover Times.
6. Identify the concepts and tools for improving flow in an area:
• Production Smoothing, Just-In-Time, Setup Reduction, Total Productive Maint.
Values of Process Mapping (video):
1. Graphical illustration of the process
2. Identify all Value and Non-Value-Added process steps
3. KPIV, KPOV, data collection points, PPM, Cycle time per setup
4. Identifies steps needing measurements system analysis.
5. Identify KPOV’s for capability studies
6. Identify holes in control plan
7. Opportunities for eliminating steps.
Benefits Value Gain Focuses on customer Reduces the hidden factory Raises Visibility Removes hidden waste Spotlights value & waste Eliminate tribal knowledge Promotes Awareness Shifts the culture from Who to what Capture knowledge allowed the error Communication Awareness
Process Map
1. Layout (Transportation)
2. Waiting
3. Incapable process
4. Poor maintenance
5. Poor work Methods
6. Inadequate training
7. Poor Product Design
8. Overproduction
9. Equipment Design & Selection
10. Poor work place organization
11. Supplier Quality/Reliability
12. Tool down time
13. Inappropriate Processing
14. Unnecessary / Excess Motion
15. Unnecessary Inventory
16. Defects
17. Underutilization of Employees
Identify Waste
Improvement – Process Map
Process Map of Sensor Isolator Burn In
Value Stream Mapping is a tool used to identify and prioritize based on problems & opportunities and their effects on the system. Provides linkage for improvement activities. Video
Provides process and time observations used to calculate total Lead time, Value-added time, Value-added ratio.
Display material and information flow from the customer through the supply base.
Establish project priority and identify opportunities.
Identify and set goals for improvement metrics.
Identifying and quantifying waste (in time and costs)
Steps to make VSM:
1. Determine what individual product, service, or family you will map.
2. Draw Process Flow 5. Collect process data & connect it to the boxes
3. Add Material Flow 6. Add Process & lead time data to the chart
4. Add Information Flow 7. Verify Map
Value Stream Maps
Improvement – Value Stream MapsCT = Cycle Time
PT = Process Time
CO =
Lead time - (also called cycle time, process cycle time, process lead time) The time from when a work item enters a process until it exits, i.e.: machine time to process part, time to order & receive material, operator time (set machine up, retrieve & load material, unload & move material, inspection, packing, shipping).
Cycle Time =Total Lead Time = Number of Things in Process
Average Completion Rate
This shows how lead time is related to the number of things in process (WIP) and the completion (exit) rate of the process.
To improve Total Lead Time, and in turn PCE, either increase capacity (average completion rate) and / or reduce WIP.
Workstation Turnover Time (WTT) for a given process step to workstation is the amount of time needed to set up and complete one cycle of work an all the different “things” (work items, SKUs) at that step. WTT is important step (time trap) to work on first.
Total Lead Time
PCE – indicates how efficiently the process is converting work-in-process into exist/completions. It measures the overall health of the process by taking the value-add time (work needed to be done as desired by customer) divided by the total lead time. Any process with low PCE will have large non-value-add costs and opportunities for cost reduction. The only way to improve PCE is to get rid of non-value-add work and costs. PCE's of less than .1 (or .1 x 100 = 10%) are common pre-improvement values. The goal is 1.
PCE = value add time (customer is willing to pay) / cycle time.
Cycle time - (also called lead time, process cycle time, process lead time) The time from when a work item enters a process until it exits, i.e.: machine time to process part, time to order & receive material, operator time (set machine up, retrieve & load material, unload & move material, inspection, packing, shipping).
Value stream process mapping is a graphical tool used to identify value added and non value add steps and time.
Takt time = customer demand rate - value add chart = available time (480 min) / # products to be shipped that day. Ex.: 480 min / 5 parts day = 88 minutes to ship a part to meet customer demand.
Minutes in a working shift
Process Cycle Efficiency (PCE)
Reasons for using SPC are to 1) Establish a measurement baseline, 2) Detect special cause variation, 3) Ensure process stability & enabling predictability, 4) Monitor process over time, 5) confirming the impact of process improvement activities. Before plotting SPC one must determine if the data is Attribute or Variable:
Variable Data - is a measurable defect (continuous data) . Length, width, height, (Cycle time, response time, continuous data). Always provides more info. & require lower sample size and is a requirement to be Normal distribution. Stat>Basic>Normality test P value must be > 0.05
When the data is not normal apply the Central Limit Theorem to normalize data. Which states the distribution of averages ( )approaches normal if u take large enough of samples.
Variable(continuous
data)
Subgroup SizeOf 1
Subgroup Size< 8 - 10
Subgroup Size> 8 - 10
Xbar & R Xbar & SImR
X
SPC For Continuous Data
2 grouped of charts (I, mR- few data points & , R - Subgroups) are generally shown: 1. I (individual) chart is used to monitor Mean when it’s impossible to group into
subgroups & therefore subgroup size is 1. Such as 1 data point per day, week, or month. Occurs when measurement are expensive. The R charts (below) must be in control before we can use the I chart.
2. Moving Range Chart (mR or R) is used when data is collected as individual observations & to monitor the moving Mean when it’s impossible to group into subgroups. Stat>Control Charts> * Individuals > ImR
Control limits are
UCL= + 3 Ϭ & LCL= - 3 Ϭ
= ave. or mean = ∑ data / # pointsIn this case the I chart is out of
Control at point 13,14,26,27.
In this case the R chart is out
Of Control at point 28.
3128252219161310741
140
135
130
125
120
Observation
Indiv
idual V
alu
e
_X=129.03
UCL=138.16
LCL=119.90
3128252219161310741
12
9
6
3
0
Observation
Movin
g R
ange
__MR=3.43
UCL=11.22
LCL=0
1
11
1
1
I-MR Chart of Pounds Scrapped
X
X
X
= ave. of moving ranges
X
MR
SPC Charts for Continuous Data
, R chart (Xbar & R, Average + Range) Stat>Control Charts> * Subgroup > RXPlots averages of subgroups (Xbar) on one chart & the ranges (R) within the subgroups on the other chart. This chart is used with a sampling plan to monitor repetitive process.•Subgroup sizes typically range from 3 to 9 items
•Xbar chart will highlight changes to the average (between subgroups or process accuracy)
•All of the Tests for Special Causes (next page) can be applied with these charts
•The R chart will detect changes to within subgroup dispersion (spread, process precision)
191715131197531
600.5
600.0
599.5
599.0
Sample
Sam
ple
Mean
__X=599.548
UCL=600.321
LCL=598.775
191715131197531
3
2
1
0
Sample
Sam
ple
Range
_R=1.341
UCL=2.835
LCL=0
Xbar-R Chart of Supp1
191715131197531
602
600
598
Sample
Sam
ple
Mean
__X=600.23
UCL=602.474
LCL=597.986
191715131197531
8
6
4
2
0
Sample
Sam
ple
Range
_R=3.890
UCL=8.225
LCL=0
11
Xbar-R Chart of Supp2
The 2 graphs below represent 2 Suppliers making the same product. Using Xbar, R chart with a sample of 5 you can see Supplier 1 is in while Supplier 2 is out of control. The R chart in #2 does not indicate that the process is out of control. However, you notice that the center line is at 3.890, which is almost 3x larger than Supplier 1's R of 1.341
X
SPC Charts for Continuous Data
Detects a shift in the mean, an increase in the standard deviation.
Detects a shift in the process mean.
Detects a trend or drift in the process mean. Small trends will be signaled by this test before the first test.
Detects systematic effects, such as two alternately used machines, vendors, or operators.
The tests below relate to “zones” which mark off the standard deviation from the mean. Zone “C” is + 1 std. dev.; Zone “B” is between 1 & 2 std. Dev.; and Zone “A” is between 2 & 3 std. dev. When creating SPC charts with subgroups apply the 8 tests displayed in options. 4 are shown below. stat>control charts>with subgroups>Xbar, R Xbar option - test
Interpreting Control Charts
Process Capability – Cpk, CpProcess Capability answers: ● How well are we doing? ● Are the process improvements making a difference? ● How well could we be doing? ● What can we expect tomorrow, next week? ● Which supplier, machine, process, factory, etc. is giving us the best quality?
Process is consider Capable when it’s output variability is able to stay within customer specifications. Process must be in control before performing Cpk. Supplier 1 is in control while Supplier 2 is out (see pg 3).
Cpk - Process capability index evaluates the productivity of an in-control process to the requirement limits. It can only be applied when the response displays a normal distribution (p >.05). Used when is not easily adjusted.
Cpk = ( - LSL)/3Ϭ or (USL- )/3Ϭ Which ever is the smaller of the two.
Cp - Process Capability indices (Cp) is used to measure how closely the process can reach the optimum level of satisfaction of customers. Used when the is constantly monitor and can be easily adjusted. It takes in all the possible elements needed for assuring improved quality products and services.
Cp = (USL – LSL) / 6Ϭ
μ = Population mean =sample Mean Ϭ - Standard DeviationUSL & LSL - Upper and Lower Specification Limits and is derived & set by the Customer
Capable OK Variation off target
Mathemetically Impossible
High variation Possibly off
target
>1.0
>1.0 <1.0
<1.0
Cpk
Cp
X
X X
X
X
Process Capability – Cpk, Cp
Below is an example of two suppliers supplying part that meet specifications 600mm +2mm. Using the stat>quality>tool>capability 6 pack>normal on camshaft.mtw. Subgroup=5, Lower spec.=598, Upper spec.=602, Options>target 600, Tests>all 8.
191715131197531
600.0
599.5
599.0Sam
ple
Mean
__X=599.548
UCL=600.321
LCL=598.775
191715131197531
3.0
1.5
0.0
Sam
ple
Range
_R=1.341
UCL=2.835
LCL=0
2015105
601.5
600.0
598.5
Sample
Valu
es
601.50600.75600.00599.25598.50597.75
LSL Target USL
LSL 598Target 600USL 602
Specifications
602600598
Within
Overall
Specs
StDev 0.576429Cp 1.16Cpk 0.9
WithinStDev 0.619299Pp 1.08Ppk 0.83Cpm 0.87
Overall
Process Capability Sixpack of Supp1Xbar Chart
R Chart
Last 20 Subgroups
Capability Histogram
Normal Prob PlotAD: 0.844, P: 0.029
Capability Plot
191715131197531
602
600
598
Sam
ple
Mean
__X=600.23
UCL=602.474
LCL=597.986
191715131197531
8
4
0
Sam
ple
Range
_R=3.890
UCL=8.225
LCL=0
2015105
604
600
596
Sample
Valu
es
604.5603.0601.5600.0598.5597.0
LSL Target USL
LSL 598Target 600USL 602
Specifications
605600595
Within
Overall
Specs
StDev 1.67231Cp 0.4Cpk 0.35
WithinStDev 1.87388Pp 0.36Ppk 0.31Cpm 0.35
Overall
1
6
1
Process Capability Sixpack of Supp2Xbar Chart
R Chart
Last 20 Subgroups
Capability Histogram
Normal Prob PlotAD: 0.287, P: 0.615
Capability Plot
For Supp. 1 the process mean falls short of the target and the process distribution mean lies to the left of the target. The left tail of the distribution falls outside the lower specification limit. We would like to see a Cpk much larger than 1, because the larger the index, the more capable the process. The Cpk index = 0.90, indicating they need to improve by reducing variability and by centering the process around the target.
Sup. 2 fails Test 1 at points 8,& Test 6 at points 12 & 13. Several points are outside the LSL & USL. Cpk & Cp are below 1. The Xbar chart & tests clearly indicate Suppler 2 is out of control even though P>.05.
Supplier 1 is definitely the better of the two but can still use some improvement.
Process Capability – Cpk, Cp
In my last job my manager asked me to determine the process capability for our department to see if we are reaching a goal of closing a Non-conformities within one calendar week (USL = 7 days). A primary performance index is the time taken to close a customer complaint.
I reviewed the last 400 complaints & collected data on how much time it took to close a complaint. File name Process Capability.mtw column C4.
Using the Stat>basic statistics>graphical summary you can see data is skewed toward the left & therefore not normal. This justifies the use of the Weibull Distribution for data that is skewed. Using the Stat>quality tools>capability analysis>non-normal & selecting column C4 and USL = 7.
21.618.014.410.87.23.6
Median
Mean
3.503.253.002.752.502.252.00
1st Quartile 1.0000Median 2.00003rd Quartile 5.0000Maximum 22.0000
3.0596 3.6204
2.0000 3.0000
2.6681 3.0657
A-Squared 23.92P-Value < 0.005
Mean 3.3400StDev 2.8530Variance 8.1397Skewness 2.43650Kurtosis 9.66809N 400
Minimum 1.0000
Anderson-Darling Normality Test
95% Confidence I nterval for Mean
95% Confidence I nterval for Median
95% Confidence I nterval for StDev95% Confidence I ntervals
Summary for Days to close
21.618.014.410.87.23.60.0
USL
LSL *Target *USL 7Sample Mean 3.34Sample N 400Shape 1.33187Scale 3.66845
Process DataPp *PPL *PPU 0.34Ppk 0.34
Overall Capability
PPM < LSL *PPM > USL 75000.00PPM Total 75000.00
Observed Performance
PPM < LSL *PPM > USL 93993.97PPM Total 93993.97
Exp. Overall Performance
Process Capability of Days to closeCalculations Based on Weibull Distribution Model
Process Capability – Cpk, Cp
To find the process capability and refer to a 6 sigma process. Do the following:
6 sigma process refers to a ZST score = 6 and is usually calculated from long term data.
ZLT = 3 Ppk (for normal distribution)
This is now consider normal due to obtaining DPPM using non-normal calculation in the previous page.
using Minitab calc>probability distribution> normal Click inverse, mean=0, standard deviation=1, input constant =.90601 (number good).
Then ZLT = 1.317 &
ZST = ZLT + 1.5 = 2.82
Therefore the current process is reported as a 2.82 sigma process which is consider not capable. See table.
On the previous page you have a DPPM (parts per million) of 93993.97 & a Ppk of .34
To find the % of good and bad do the following:
93993.97 / 1,000,000 = .09399 which is 9.39% bad or 100% - 9.399% = 90.6% good. Or
1000000 by (1M – 93993.97)/1M = .906007
6 sigma Process Capability (see previous page)
FMEA - Failure Mode Effects & AnalysisFEMA – is a Potential Problem Analysis (PPA) process for uncovering &
dealing with potential problems that are likely to occur with the process, product, or service. In other words estimate & prioritize the risks associated with probable failures (Risk Prioritization Num. -RPN).
3 Types:
1. Design – exposes problems before rollout to expose problems that may occur after release. Ex. Malfunctions, safety, hazards
2. Process – used to improve existing process & transactions that may result in defects, efficiency, safety hazards, etc.
3. System – Analyzes systems in early stages of concept & design
Preventative – remove the likely cause of a potential problem
Contingent – reduce the impact of a problem that cannot be prevented.
Good idea to have vendors implement FEMA’s.
Elements of FMEA
SEVERITY of the effect:As it applies to the effects on the local system, next level, and end user. Scale of 1 (least severe) to 10 (most severe).
OCCURRENCE frequency of the cause:Likelihood that a specific cause will occur and result in a specific failure mode. Scale of 1 (least often) to 10 (most often).
DETECTION system for spotting the failure:Ability of the current I proposed control mechanism to detect and identify the failure mode. Scale of 10 (no detection) to 10 (good detection).
RPN = O x S x D
Occurrence x Severity x Detection
Risk Priority Number
FMEA – 1st Why
FMEA – 2nd Why
α is the risk of finding a difference when there really isn’t one (usually set at 5%)β is the risk of not finding a difference when there really is one. (Power value = (1-β)= .9)σ If the standard deviation is known the critical difference δ can both be input accurately
Choosing an appropriate Sample size:1. Select the risk level of α error or level - Usually 5%2. Select the β level – between 5 - 20%3. Select the critical difference δ or Delta you would like to detect in your experiment.4. Establish or estimate current process sigma σ 5. Use software Minitab or the sample size selection table to determine n (number of
samples required per experimental factor level.6. Develop the sample plan7. Test and make proper conclusion.
Example: 1 MeanA industry standard average response time to get back to a customer is 18 minutes. Historically,
the standard deviation of the process is 5.2 minutes (+ 5.2 minutes). The team wanted to implement improvements to get an average of 13 minutes response time. Given σ = 5% and β = 10% (power = 90). What sample size is needed.
Solution:Currently Ho: Average 18 minutes [5% (α) chance of saying Ave. = 13 if Ave = 18 min.Trying to achieve Ha: Average 13 minutes [10% (β) chance of saying Ave. = 18 if Ave = 13 min.Stat>power & sample size>1-sample tInput: Difference (13 – 18)=-5, Power value (1-β)=.9, Sigma 5.2, in options = select less than, &
significant level α=.05Answer: Sample size = 11
Determining Sample Size
Design of Experiments (DOE)DOE is a systematic approach to investigation of a system or process. A series of structured tests are designed in which planned changes are made to the input variables of a process or system. The effects of these changes on a pre-defined output are then assessed.
Lean Manufacturing(Video)
The goal of Lean Manufacturing is to:
1. To optimize the manufacturing process as much as possible by reducing non-value added processes.
2. Eliminate anything that doesn't help achieve customer specifications.
3. Minimize or eliminate anything the customer would be unwilling to pay for.
Project – Apply Lean Concepts & 5S to Refurbishing Pumps.
1. Identify and eliminate Waste 5S (Sort, Set in order, Shine, Standardize, Sustain) Value Stream Maps One Piece Flow
2. Operational Improvement Process Flow & Lay out Process Cycle Efficiency (PCE) Process Balancing
3. System Synchronization (Kaizen) Production Planning – capacity planning Supply Chain – vendor participation Distribution – customer pull, VOC,
1. Why are we in business – to satisfy a demand & make a profit
2. Why would we make more profit using the 5s – time & space is consider value ($ # / # sq. ft)
3. Why is time so critical – wasted time and space reduces profits
4. Why & how is time & space related to 5s – using 5s helps identify & eliminate unnecessary time & space in producing product.
5. What is consider wasted time & space – Ex. misplaced tools, things in production that are not needed and take up space.
5S – Seeing the benefits using 5W
Process PeopleProfit
Make a Profit by providing a
product
Manage the Process by focusing on
Reducing the Cycle Time (increasing throughput)
People Run & Improve the
Process
5S 3 Key Elements
5S Sort (Def. & Implementation)
Definition:
Sort refers to the practice of going through all the tools, materials, etc., in the work area and keeping only essential items. The goal is to remove all nonessential items from the work place. Everything else is either stored offsite or discarded. This leads to fewer hazards and less clutter.
Steps Taken for Implementing Sort:
1. Select Team members:
a) Dario Guerrio, Juan Sandoal, Abel Cadena, Jane Nguyen, Kim Li, and Shannon McGowan.
2. Area selected is Pumps Refurbish & Tear Down
3. Questions to ask to prevent confusion & wasted effort:
a. What is this?
b. When did you last use it?
c. Is it critical or unique for the department / operation?
d. If its inventory, is this the minimal amount needed to keep up with the production schedule?
5S Sort (questions to ask)
3. Upon identifying items not belonging to the area fill out a Red Tag & place on item.
4. 5 day Local holding “Red Tag” area is located in the east corner of Mfg. Area of building D7.
5S Sort
5. Take before and after pictures of application areas. Ex. Disassembly, Cleaning, Discard Area, Bin Stacking, Assembly, Testing, Break-in, etc..
6. After 5 days record and move items to the Central Red Tag area where everyone can sift through the items to see if there is something needed – records are used so company can track assets.
7. After 1 month items in the central area were either dispose of, recycled, trashed, donated or resold.
5S Sort (Steps)
5S Sort (Imp. Template)
5S Set In Order (Def.)
“Set In Order” is a means to arrange needed items in the area and to identify or label them so that anyone can find them or put them away.
Slogan:
A place for everything and everything in it’s place so it should be easy to find.
Goal:
To arrange all needed work items in line with the physical workflow, and make them easy to locate.
Steps Taken for Implementing Sort:
1. Select team members:
a) John Salvetierra, Jeff Kerner, Chuong Nugyen, Jamie Sipes, Bill Orais and Shannon McGowan.
2. Selected areas are Refurbish Pumps & Tear Down at Entegris & Box Build at Jabil, PCB Test at KLA Tencor.
5S Set In Order (Implementation)
• Take before and after process time.
• Look for ways to make the work place more visually instructive.
• Label floor space, carts, tools, area, etc..
• Post acceptable & unacceptable work output.
• Display charts on quality performance trends.
5S Set In Order (Imp. Template)
Video sample of Set In Order
Before After
RG
EN
#1
INT
EL #1
PH
OT
O &
EC
ON
#1
PHOTO & ECON FINAL TEST #3
INTEL ELEC.
TEST #4Monitor & Key Bd.
RgenElect.
Test #4
Monitor & Key Bd.
USonic
Final P
ack
Trash Chemwaste
PHOTO & ECON #2ChargingPC
Intel & RgenRough & Fine Fill
Intel & RgenBreak In
Work inProg. PC
ToolBox
Photo & Econ #4
Valve Test
Intel & Rgen #2Integrity
T.
PumpPump
INTEL ELEC.
TEST #4Monitor & Key Bd.
RgenElect.
Test #4
Monitor & Key Bd.
Work inProg.
Intel &
Rgen
Rough
&
Fin
e Fill
Inte
l & R
gen
Brea
k In #3
PC
USonicFinal Pack
ToolBox
BinCart
BinCart
PH
OT
O &
EC
ON
F
INA
L T
ES
T #
3P
HO
TO
& E
CO
N #
2C
harg
ing
PH
OT
O &
EC
ON
#1
Photo & Econ #4 Valve Test
Trash
Chem
waste
Intel & R
gen #2Integrity T
.
RG
EN
#1
INT
EL #1
TrashTrash
Pass itthrough
Inte
l & R
genR
ough &
F
ine Fill
Intel & R
gen
Bre
ak In
#3
PC
VacPump
5S Set In Order (Sample)
Before
Op CV2
24SD6 SK
Person 1
Person 1Person 1
Person 1
Person 1
Top V2
Op HAttach Rail,R. Side, H+
47SK
4,13Op B
V1, H+,Side6SD,32SD
Op A Asm.20, 21,22,
23 13SD, 23SD
20,2122,238,31
Op IAttach Rail,L. Side, H+
47SK
3 Tables For EMI & Inspection
Op EBot
54SK 8SD
Person 1Person 1Person 1
Op FTop Asm, H+
42SK
Op GBot Asm, H+ 43SK
11,30
V19,12
16,18,191,3,4,5
4LevelShelf
Pallet Storagefor 19
Pallet Storagefor 20
Pallet Storagefor 77, 78
Work Space For Bare Rack Assembly
Plastics
Back wall
work station
Plastics
PC & Labels
Pla
stic
Pla
stic
CenterPlane
Op DV2, H+,& H18,12,9 SK
4LevelShelf
70 & 78Parts
70 & 78Parts
Table Table Table Table
16,21,18,19,
20Op AL & R Mid
23SD
9,12,20Op B
R+L=H &Sides
32SD 7SK
15,13Op D
Finish AsmTop & H+
34SK
Op HL Grill H+
41SK
Op F Bot, H+
44SK
11Op G
R Grill H+41SK
8
Person 1Person 1Person 1
Person 1
Person 1
Person 1 Person 1
4 LevelShelf
Op CStart Top &
H+34SK
4 LevelShelf
Phase ICurrent Sunfire Production Line
metal cage
Re-work Table
Rework Table
DeskPump
Elevator
PartsRack
PartsRack
PartsRack
Elevator
PartsRack
Parts
Rac k
PartsRack
WorkStation
WorkStationParts
RackPartsRack
PartsRack
PartsRack
PartsRack
Desk
Completed Racks
Rack Build
Hi Pot
Hi Pot
Sub
Asm
Sub
Asm
Sub
Asm
Sub
Asm
Sub
Asm Sub
Asm
Rack Build
Completed Racks
EMI & Inspection
Sh
ipping & Q
A
Shipping & QA
Missing Plastics Missing Rack Parts
Missin
g Rack P
arts
Missing Plastics Missing Plastics
3019 3019 3019 3020 3020 3020
4.00
3.50
5S Set In Order (Sample)
121 Fan Tray
Per
son
2
120 Fan Tray
Per
son
2Rac
kR
ack
TestA
119 KeySwitch
Person 1
Person 1
Shipping
Shipping &
QA
PartsRack
PartsRack
PartsRack
PartsRack
PartsRack
PartsRack
PartsRack
PartsRack
PartsRack
Note:V2 & V1 & H represent Sub-assemblies which make up the middle.
Work Space For Bare Rack Assembly
Back wall
metal cage Pump
Elevator
PartsRack
PartsRack
PartsRack
ElevatorRack Build
Hae
ger
Person 1
Hae
ger
Person 1
Carton
Wheel
Hae
ger
Person 1
Carton
Wheel
Carton
Wheel
Phase VII Sunfire
MFR & BFR Lines
E
Person 1
Person 1Person 1
Person 1
Plastics
F
VacuumLift
J
K
Brocade / BFR
Power & Air
Shipping Materials
Kanban Carts
Parts
Parts
Kanban CartsP
arts
Parts
Kanban Carts
Parts
Parts
Kanban Carts
Parts
Parts
Kanban Carts
Parts
Parts
Kanban Carts
Parts
Parts
Desk
A
G
CenterPlane
Storage
Hi Pot
Rework In Process
B
File
Person
X Option Complete
Hi PotTested
121
Tested137
Assembled122,139
X Option Build
MR
BP
revi
ew
MRBPreview
MRBPreview
PartsRack Cart
PartsRack Cart
Rework
CiscoTerminal
Rivet Stock
HardwareSupply
Pla
stic
Rac
k
Pla
stic
Rac
k
Pla
stic
Rac
k
Pla
stic
Rac
k
MR
B
Rac
k
Untested123,510
Person 1
137 Rack
Fan T
ray
Person 1
Person 1
Tes
ted
121
Te
stS
tati
on
Untested 137
Tested123,510
Person 1
14.90
Hi
Po
t T
est
Sta
tio
n
Tested120
IncomingKanban
IncomingKanban
IncomingKanban
IncomingKanban
IncomingKanban
IncomingKanban
Person
PC
&
Labels
IncomingKanban
139,
12
2S
CS
I T
ray
NT
Person 1
Desk
IncomingKanban
IncomingKanban
123
R
emo
te K
ey
Sw
510
Rac
k D
ev.
5
.25"
Fin
ishT
est A
sm.
Com
ple
te
Untested123,510IncomingKanban
Untested123
Untested 510
Desk
Person 1
Desk
Unt
est
ed
Rac
k
132, SCSI CD Dr.
NT
132, SCSI CD Dr.
NT
119 KeySwitch
Rack
Rack
Person 2
Person 2
Un
tested
Ra
ck
Walk Way
Test A Responsibilities:1. Test All Subs2. Record on Paper Log (back flushing)3. Stamp Unit4. Place on Rack or5. Place labels on traveller (2) & VOP6. Place tested unit inside Main chassis
Hi Pot Responsibilities:1. Hi Pot Test All 3700 chassis2. Record on Paper Log (back flushing)3. Stamp Traveller4. Wand all information on traveler
121
Fan
Tra
y
Person 2
Rack
Desk
EM
I Gas
ket
&Q
ualit
y
Person 1
Op FR Grill,
H+41SK53SK
Op GL Grill
H+41SK53SK
Person 1
Op C
Asm Top&
Join H+34SK
Person 1
Op AJoin L & R. Mid
23SD, 7SK
1,3,4,5
Op DBot & rail
60SK & 8SD
Op BJoin
Sides32SD
2 People
Op EBot & H+
44SKPerson 1
2 People
Person 1Person 1
Person 1
Person 1
Person 1
Person 1
Person 1
15, 13118 Pass Thru9, 12
16,21,18,19,20
Pass Thru
20 & 78
Op DFinish H
=9SK V2, H, =18SK
Top=12SK
Person 1
Op BAttach V1 & H =6SD,=32SD
Op IR. Side,
H+47SK 63SK
Op HL. Side,
H+47SK 63SK
Op GBot Asm,
H+43SK
Person 1Person 1 Person 1
Op AV1=13SD H=23SD
Op CV2=24SDV2=6SK
16,18,19
Person 1Op F
Top Asm H+,42SK
2 People
Person 1EM
I Gas
ket
&Q
ualit
y
Person 1Person 1
Person 1
Person 1Person 1
Person 1Person 1
Person 1
20,21,22,23
Pass T
hru9,12Pass Thru
V2,4,1311 & 30 8 & 31
Pass
Thru
1,3,4,5
C
D Op EBot 54SK
8SD
19 & 77
Elevator
PC
&
Labels
77 & 7819 & 20 2
Ball
5S Set In Order (Sample)
5S Shine (Def.)
To have a work place “Shine” one must remove dirt & debris, inspect & clean equipment, and eliminate sources of contamination.
Goal:1. Keep area and equipment clean so as to
recognize anything out of place:A. Oil Leak from equipment, excessive heat, damage or
worn tools or equipment.
2. Improve quality by getting rid of contamination.
Steps Taken for Implementing Shine:1. Select team members:
a) Mark Renolet, Jeff Kerner, Sam Vales, Jamie Sipes, Bill Orais and Shannon McGowan.
2. Selected work areas are Assembly areas at Abbott Diagnostic, Refurbish Pumps & Tear Down at Entegris & Box Build at Jabil, PCB Test at KLA Tencor.
Shine
5S
Create a Standard for common areas.
5S Audit Forms
SortSet in OrderShineStandardizedSustain
5S Seeing The Benefits
One of the surest ways to identify these benefits is to establish and track specific metrics. Some examples are listed below.
• Measure the time required to locate items in the workplace before 5S and then measure the time required after the workspace has been improved.
• It is easier and faster to train employees in a work area that is orderly and well marked.
• Take pictures in the work place before and after implementing 5S. Pictures are very effective at visually
Concrete measurements are a complement to the pictures, fueling the momentum needed to sustain 5S.
6 Sigma Is broken into 3 major topics:
1. A Statistical term & business metric (Process Capability)
2. A business strategy & initiative (Reduce Variation)
3. A problem solving / prevention system & methodology (DMAIC).
The objective of Six Sigma Quality is to reduce process output variation so that on a long term basis, which is the customer's aggregate experience with our process over time, this will result in no more than 3.4 defect Parts Per Million (PPM) opportunities (or 3.4 Defects Per Million Opportunities – DPMO
Design For Manufacturability (DFM)DFM – is the process and practice of designing products so it can be produced efficiently at the highest level of quality while considering manufacturing requirements.
Guidelines:
1. Minimize Total Number of Parts
2. Develop a Modular Design
3. Minimize Part Variation
4. Design Parts to be Multifunctional
5. Design Parts to be Multiuse
6. Avoid separate fastener
7. Design Parts for Ease of Fabrication
8. Minimize Asm. Dir.
9. Maximize Compliance
10. Minimize Handling
11. Simplify Adjustments
12. Avoid Flexible parts
13. Implement Pull vs Push
Design For Manufacturability (DFM)
Factory Design Considerations:
1. Cycle & Takt Time
2. Quality (SPC, 6 sigma, Lean Manufacturing, Tracking (barcode))
3. Process Capability (Cp, Cpk, Process Maps)
4. Ease of Manufacturing (VOC, Value Analysis)
5. Ease of Assembly (Environment, Facility)
6. Ease of Testing
7. Service & Repair
8. Inventory (suppliers, availability, lead times)
9. Shipping (packaging, equipment, material)
Design Controls For Med. DevicesWhat is Design Controls FDA 21 CFR PART 820.3:Design & Development – PlanningDesign Inputs – Origin of RequirementsDesign Outputs – Documents to be buildDesign Review – On TrackDesign Verification – Output same as InputDesign Validation – Design same as customer requirementsDesign Transfer – To manufacturingDesign Changes – Correct and upgrade the designDesign History File – Document Design, & Design process
21 CFR Part 820 cGMP cGMP are set forth in the QMS regulations. The requirements used to govern the methods used the facilities, design, manufacturing, packaging, labeling, storage, installation, and servicing of all devices intended for human use.
21 CFR Part 820820.5 Quality System – maintain a quality system appropriate for medical device mfg..
820.20 Mgmt. Resp. – shall establish its policy & objectives for commitment to quality.
820.22 Quality Audit – are conducted to assure that the quality system is in compliance with the establish quality system requirement and to determine the effectiveness of the quality system.
820.25 Personnel – shall have sufficient personnel with the necessary education, background, training, & experience to assure that all activities required are correctly done.
820.30 Design Controls – Class I, II, III shall establish and maintain procedures to control the device in order to ensure that specified design requirements are met.
820.40 Document Control – shall establish & maintain procedures to control all documents.
820.50 Purchasing Control - shall establish & maintain procedures to ensure that purchased or otherwise received product and services confirmed to specified requirements.
820.60 Identification - shall establish & maintain procedures for identifying product during all stages.
820.65 – Traceability – each mfg. of a device that is intended for surgical implant into the body can be identified with control number of each unit, lot, or batch #.
820.70 – Production & Process controls - shall develop & monitor production process to ensure device conforms to its specification.
21 CFR Part 820820.72 – Inspection, measuring, & test equip. – each mfg. Shall ensure all equip. is suitable for its intended purpose & is capable of producing valid results.
820.75 – Process Validation is where a process can be fully verified by inspection & test, validated & approved. Each mfg. shall ensure validated process are performed by qualified individual, continual monitoring of control methods of data is documented & dated. If process changes or deviates, mfg. Shall re-evaluate & perform revalidation where appropriate.
820.80 – Receiving, in-process, & finished device acceptance – each mfg. Shall establish & maintain procedures for accepting incoming product & outgoing product. Finish devices shall not be released for distribution till required activities have been completed.
820.86 – Acceptance Status – Each mfg. Shall be able to identify status of acceptance of each product
820.90 – Nonconforming Product – Each mfg. Shall maintain procedures to control nonconforming product that include identification, doc., evaluation, segregation, & disposition. The evaluation will include a decision whether or not a need of an investigation is required and the people associated.
820.100 – CAPA – Each mfg. Shall maintain procedures for implementing CAPA that include analyzing, investigating, identifying, verifying, implementing, relaying info related to problem to those directly responsible for assuring quality of product.
820.120 – Device Labeling – Each mfg. shall establish & maintain procedure to control labeling activities.
820.130 – Device Packaging – Each mfg. shall ensure the packaging containers are design to protect the device from alteration or damage during handling, shipping, & storage.
21 CFR Part 820820.140 - Handling – Each mfg. shall establish & maintain procedures to ensure that mix-ups, damages, deteriorations, contamination, or other adverse effects to product do not occur during handling.
820.150 – Storage – Each mfg. shall establish & maintain procedures for control of storage areas and stock rooms for prevent mix-ups, damage, contamination, etc.
820.160 – Distribution – Each mfg. shall establish & maintain procedures for control & distribution of finished devices that include name & address of the initial consignee, ID & quantity, date, and control number.
820.170 – Installation - Each mfg. of a device requiring installation shall establish & maintain installation instructions.
820.180 – Records Requirements – shall be maintain at the mfg. establishment that is accessible to responsible officials of the mfg & employees of FDA.
820.181 – Device Master Records - Each mfg. shall maintain DMR.
820.184 – Device History Records - Each mfg. shall maintain DHR.
820.186 – Quality System Records - Each mfg. shall maintain QSR.
820.198 – Complaint Files - Each mfg. shall maintain complaint files.
21 CFR Part 820820.200 – Servicing – Where servicing is required Each mfg. shall establish & maintain instructions & procedures for performing and verifying servicing meets the specified requirements.
820.250 - Statistical Techniques – Where appropriate Each mfg. shall establish & maintain procedures for identifying valid statistical techniques required for establishing, controlling, and verifying the acceptability of process capability and product characteristics.
ISO 13485 - 5 Principal ElementsQuality Management System:
1. Documentation requirements
2. Quality Manual
3. Control of Documents
4. Control of Records
Management Responsibility
1. Management Commitment
2. Customer Focus
3. Quality Policy
4. Planning
5. Responsibility, authority & communication
Resource Management:
1. Human Resources
2. Competence, awareness, training.
3. Infrastructure
4. Work Environment
Production Realization:
1. Planning
2. Customer-related Process
3. Design & Development inputs, outputs, review, verification, validation, changes
4. Purchasing
5. Control of Monitoring & Measuring Dev.
ISO 13485 - 5 Principal ElementsMeasurement, Analysis, & Improvements :
1. Monitoring & Measuring
2. Internal Audit
3. Monitoring & Measuring Processes
4. Monitoring & Measuring of Product
5. Control of Nonconforming Product
6. Analysis of Data
7. Improvement with continual improvement, CAPA
Verification & Validation for Medical Devices
Regulations & Standards for V & V: FDA Design Controls – 21 CFR 820.30
Design Verification shall confirm that the design output meets the design input requirements. The results of the design verification, including ID of the design, methods, the date and the individuals performing the verification, shall be documented in the DHF.Design Validation shall be performed under defined operating conditions on initial production units, lots, or batches, or their equivalents. Design validation shall ensure that devices conform to defined user needs and intended uses and shall include testing of production units under actual or simulated use conditions.
ISO 13485: 2003 – Quality Management System for MD Manufacturing. 7.3.5 Design Verification & 7.3.6 Design Validation
ISO 14971: 2007 – Application of Risk Mgmt. To Medical Devices6.3 Implementation of risk control measures.
Verification & Validation for Medical Devices
Key Tasks in V & V
1. Establish product requirements and perform risk analysis (what exactly are we building and how can it hurt someone?)
2. Determine the applicable standards (what do regulators say we have to test?)
3. Develop a test plan
4. Develop test methods, as necessary
5. Write test protocols (draft) and perform informal testing
6. Validate test tools
7. Build devices to test
8. Release test protocols
9. Execute test protocols
10. Evaluate results and write test reports.
Verification & Validation for Medical Devices
Key Concepts for V & V:
• Well-written requirements & risk analysis are crucial to V& V(make sure requirements are verifiable!)
• Some tests are more important that others (risks)
• Much of the testing that needs to be done is already defined in applicable standards.
• Formal V & V testing should be performed
•Using calibrated and controlled test equipment
•According to written protocols that include pre-defined conditions for testing and acceptance criteria.
•Using test protocols which were approved prior to use
• Test protocols and test reports should become part of the Design History File
• If you do not control the configuration of the device under test then the test results are meaningless.
• Start testing early in development; develop test methods as product develops.
Process Validation
Risk Management
SolidWorks - Sample
Gage R & RDefine: Involves evaluating the Reliability & Repeatability of a measurement system.
Repeatability refers to the inherent variability of the measurement system. It is the variation that occurs when successive measurements are made under the same conditions.
• Same person Same part
• Same characteristic Same instrument
• Same set-up Same environment
Reproducibility has the same bullet points above except the variation in the average of the measurements made by different operators using the same measurement instrument and technique when measuring the identical characteristic on the same part or process.
Decision Rules
KaizenDefine: Is used for intensive project where emp. Are pulled off their regular job.• Team works 3 to 5 days full time (spreading project work over 3 to 6 months.• Team spends 100% of their time on the project during the event• Project is well define going in (boundaries must be well defined ahead of time)• Basic Data already gathered.• Basis for action (will act when 70 to 80% confident vs. 95% in typical DMAIC• Implementation is completed as much as possible during the event• Items that cannot be finished during the event are to be completed within 20 days
When to use Kaizen:• When obvious waste sources have been identified• When the scope & boundaries of a problem are clearly defined & understood.• When implementation risk is minimal.• When results are needed immediately.• In the early stages of deployment to gain momentum & build credibility of the DMAIC.• When opportunities to eliminate obvious sources of instability & waste have been identified through process mapping, work area tour, data collection, etc.
Kaizen ExampleLayouts, Screw to long, Screw loose, Process redundant, creating to many failures, paint, cosmetic
