Handling & Process (pdf) DEPARTMENT PROFILES Reliability Test Services QUALITY WHITE PAPERS Defects in DMOS Antenna Ratio Violation ADDITIONAL INFORMATION FAQ EOS/ESD Information Obsolete Product Listings Environment al Safety Glossary: Quality Terms CONTACT US Comments & Questions National Locations FMEA is a systematic analysis of potential failure modes aimed at preventing failures. This is intended to be a preventative action process carried out before implementing new or changes in products or processes. An effective FMEA identifies corrective actions required to prevent failures from reaching the customer and to assure the highest possible yield, quality and reliability. In semiconductor device design and manufacturing, it is common to perform different types of FMEA. These can be divided into two primary categories: product related and process related. These are often called Design FMEA and Process FMEA and they are often further subdivided to focus on specific areas of product or process development. The main purpose of an FMEA is: To identify possible failure modes that could occur in the design or manufacturing of a product. To identify corrective actions that could reduce or eliminate the potential for failures to occur. To provide documentation of the process. To quantify the risk level associated with each potential failure mode. An FMEA is a two-phase process. First the potential failure modes and corrective actions are identified. Then after the corrective actions are implemented, the product or process is re-evaluated to determine if the result is acceptable. This is best accomplished with a cross-functional team with members from all affected work groups (e.g. Marketing, Engineering, Manufacturing, Test, QRA, etc.) Benefits of FMEA An FMEA provides benefits to both the manufacturer and the customer. Some of these benefits include: Assists in determining the best possible design and development options to provide high reliability and manufacturability potential. Assists in considering the possible failure modes and their effect on the reliability and manufacturability of the product. Provides a well-documented record of improvements from corrective actions implemented. Provides information useful in developing test programs and in-line monitoring criteria. Provides historical information useful in analyzing potential product failures during the manufacturing process. Provide new ideas for improvements in similar designs or processes. Documenting an FMEA This preventative action process provides a methodical approach to study the cause and effect of potential failures. The form below (Fig. 1) is used to document the process. Product or Process: FMEA Type: FMEA Date:
Transcript
Handling & Process (pdf)
DEPARTMENT PROFILES
Reliability Test Services
QUALITY WHITE PAPERS
Defects in DMOS
Antenna Ratio Violation
ADDITIONAL INFORMATION
FAQ EOS/ESD
InformationObsolete
Product ListingsEnvironmental
SafetyGlossary:
Quality Terms
CONTACT USComments &
QuestionsNational
Locations
FMEA is a systematic analysis of potential failure modes aimed at preventing failures. This is intended to be a preventative action process carried out before implementing new or changes in products or processes. An effective FMEA identifies corrective actions required to prevent failures from reaching the customer and to assure the highest possible yield, quality and reliability.
In semiconductor device design and manufacturing, it is common to perform different types of FMEA. These can be divided into two primary categories: product related and process related. These are often called Design FMEA and Process FMEA and they are often further subdivided to focus on specific areas of product or process development. The main purpose of an FMEA is: To identify possible failure modes that could occur in the design or manufacturing of a product.
To identify corrective actions that could reduce or eliminate the potential for failures to occur.
To provide documentation of the process.To quantify the risk level associated with each potential failure mode.
An FMEA is a two-phase process. First the potential failure modes and corrective actions are identified. Then after the corrective actions are implemented, the product or process is re-evaluated to determine if the result is acceptable. This is best accomplished with a cross-functional team with members from all affected work groups (e.g. Marketing, Engineering, Manufacturing, Test, QRA, etc.)
Benefits of FMEA
An FMEA provides benefits to both the manufacturer and the customer. Some of these benefits include:
Assists in determining the best possible design and development options to provide high reliability and manufacturability potential.
Assists in considering the possible failure modes and their effect on the reliability and manufacturability of the product.
Provides a well-documented record of improvements from corrective actions implemented.Provides information useful in developing test programs and in-line monitoring criteria.Provides historical information useful in analyzing potential product failures during the
manufacturing process.Provide new ideas for improvements in similar designs or processes.
Documenting an FMEA
This preventative action process provides a methodical approach to study the cause and effect of potential failures. The form below (Fig. 1) is used to document the process.
The Process/Product Description or Purpose should be clearly defined. This may be broken down into sub-processes with each being considered separately. Potential Failure Modes lists the different ways the process might fail to meet the process requirements or design intent. The Potential Effect(s) of Failure is how the customer perceives the failure. The "customer" includes subsequent design or manufacturing operations and/or the end customer. Each of the Failure Modes and Effects is assigned a Severity (SEV) value and Classification (CLASS). How a failure could occur should be described in terms of something that can be corrected or controlled and listed under Potential Causes/Mechanisms of Failures. The probability that a given cause or mechanism that might occur is assigned a numeric value in OCC. Current Design/Process Control Prevention/Detection describes any controls that can prevent or detect each of the failure mechanisms. The probability that each control will effectively detect the failure is assigned a numeric value in DET.
The Risk Priority Number (RPN) is the product of Severity, Occurrence and Detection. These are assessed and engineering judgment is used to determine if the risk is acceptable. Recommended Actions are developed to reduce the RPN with priority given to the highest RPN values and customer defined specific characteristics. Once the actions are implemented, the Severity, Occurrence and Detection values are reassessed, and a new RPN is calculated. This process continues until the risk level is acceptable.
An FMEA is a living document that should be reviewed and updated periodically. Any change in design, process or use of the product should be updated in the FMEA.
Quality System Certifications - ISO/TS 16949, ISO9001 & StackNational Semiconductor Product Groups and Manufacturing Sites have successfully completed & ISO/TS16949 based (including ISO9001;2000) assessments conducted by Det Norske Veritas (DNV) Certification Incorporated and are currently certified.
The following DNV certifications certify conformance of National Semiconductor's Quality Systems:
Corporate Sites CertificationISO / TS16949
Corporate Sites CertificationISO 9001:2000
STACK Certification
All Sites Click to View Certificate
Click to Expand
Santa Clara, CA
Arlington, TX
So. Portland, Maine
Greenock, UK
Malacca, Malaysia
Suzhou, China
DNV is one of the leading international certification bodies. For more information about the Det Norske Veritas, visit their web site at:
National Semiconductor Corporation strives to achieve best-in-class quality and reliability performance on all their products through a systematic approach that emphasizes quality at every phase of product development through manufacturing. From initial design conception to fabrication, test, and assembly; quality is built-in and assured through stringent SPC monitoring of fabrication and assembly processes, materials inspections, wafer level reliability (WLR), new product qualifications, reliability monitoring of finished product and strict change control management.
What is Reliability?
Reliability is the characteristic expressed by the probability that the part will perform its intended function for a specific period of time under defined usage conditions.
Reliability Failures
There are 2 basic types of failures, Early Failures and Wear Out Failures. These are reflected in the curve known as the Bathtub curve.
National Semiconductor uses Reliability Testing to ensure all its products are below targets set for Early Failure Rates in PPM and Wear Out Failures in FITs.
Qualification
New Processes and New Packages
New Processes and New Packages are qualified using a minimum 3 lot (77 units per lot) testing for:
Early Failure Testing (915 samples) Operating Life Test Temp and Humidity Biased Test Temperature Cycling Auto-Clave ESD/Latch-Up Board Level Temp Cycle (for packages)
Power Cycling and Data Retention Testing is also done when applicable.
Smart Quals
Products designed to Process and Package Design Rules and using Qualified Processes and Packages are released using 168hr Rel Data.This approach supports Time to Market needs without compromising Reliability.To ensure there is no customer risk, National has continuous reliability monitoring in place.
Reliability Monitor Program
An Ongoing Reliability Monitor is in place to ensure that products manufactured to Qualified Processes under Qualified Reliability Standards, has not drifted.
Results of the Rel Monitor Program are published on National’s Quality Web Page; Test Frequency is as posted below.
TEST FREQUENCY
EFR(All major processes)
Every week
OPL (1000 hr)
THBT (1000 hr)
ACLV (96 hr)
TMCL (1000 cycles)
Every 8 weeks
Every 8 weeks
Every 8 weeks
Every 8 weeks
Fix Reliability Testing Capabilities Reliability Test Services and ESD and Latch-Up Testing Labs are fully equipped to support the Reliability Qualification Testing. Details of the Lab Equipment are listed in the following two tables. Reliability Testing Services Equipment Inventory
Dynamic Operating Life (Op Life)13 ADEC burn-in ovens3 Wakefields1 AMT
65 to 160°C65 to 160°C65 to 160°C
Comments:Vector drivenDriver board dr.Driver board dr.
Static Operating Life4 Jarvis ovens9 Marin
65 to 160°C65 to 160°C
Temp & Humidity (T&H)12 BLUM M ovens 85 C at 85% humidity
(normal)
Can do:20 to 90 C at 30 to 90% humidity
Temp Cycles2 Blue M Systems4 Ransco systems (batch loaded)
-40 to 125°C-65 to 150°C-40 to 60°C 0 to 125°C
200lbs. Each1 - 200lbs, 2 – 40lbs1 - 151lbs
Auto-Clave (ACLV)5 Dispatch systems (batch loaded) 121 C at 15 PSI
High Accelerated Stress Test (HAST)2 Hirayama1 Express1 Dispatch
135C at 85% RH/PSI135C at 85% RH/PSI135C at 85% RH/PSI
Board loaded voltage applied
Power Temp Cycle1 Thermo Dynamic system3 ICA1 systems
40 to 125°C (Ambient)40 to 125°C (Ambient)
Board loaded voltage appliedBoard loaded voltage applied
Air Power Cycle2 Approval systems 25 to 150°C (Ambient) Board loaded voltage
applied
Water Power Cycle- 1 Approval systems 25 to 150°C (Ambient) Board loaded voltage
applied
Thermo Shock (Liquid to Liquid)- 1 Approval systems
Electromigration- 1 Micro-instrument 210C, 175C, 150C Forcing current
Highly Accelerated Life Test(HALT)- 1 Qualmark System
Vibration and thermal3 axis, plus 65C to 150°C
BSBO – Ethernet cardsPlexis/Tigris
Equipment in the ESD/Latch-Up Lab
Max Pins
HBM Voltage
MMVoltage
IEC 1000Capable
On Board Clock
Vectored Latch-up
KeytekZapMaster
256 25 - 12000 25 - 2000 Yes No No
RCDM N/A 50 - 4000 N/A No No No
MK-2 768 50 - 8000 50 - 2000 No Yes Yes
Failure Mechanisms/Failure Models
Various failure mechanisms are tested during Rel Testing. Major ones are listed below.
Failure Mechanism and Model
Failure Mechanism Failure Model
Electromigration Blacks Model
Excessive Intermetallics Kidsons Model
Reverse Bias Breakdown Tasca
Stress Dependent Diffusive Voiding
Okabayashi Model n NE 1, Okabayashi Model n EQ 1
Time Dependent Dielectric Breakdown
Fowler Nordhiem Tunnel Model
Slow Trapping Positive Gate Voltage Model, Negative Gate Voltage Model
Metallization Corrosion Plastic Metal Corrosion, Hermetic Metal Corrosion
Die fracture Westergaard Bolger Model Die, Suhirs Vert Crack Model Die, Suhirs Horz Crack Model Die, Westergaard Model Power, Suhirs Horz Crack Power
Modular Case Fatigue Shear Fatigue Model Case
Modular Case Fracture Shear Fatigue Model Case
Substrate Fracture Westergaard Bolger Model Sub, Suhirs Vert Crack Model Sub, Suhirs Horz Crack Crack Model Sub
Die Attach Fatigue Attach Fracture Model Brittle, Attach Fatigue Model Brittle, Tensile Fatigue Model Ductile, Shear Fatigue Model ductile, Raja Die Attach Fatigue
BGA Solder Fatigue Time to fail by Creep, Coffin Manson BGA Solder Fat
Discrete Solder Fatigue Dis Solder Jnt Cap 90pb10sn, Dis Soldr Jnt Fat Cap 63sn37pb
Wire Bond Fatigue Hu Pecht Dasgupta Model, Wirebond Pad Shear Failure, Bond Pad Fatigue Revised
Wire Fatigue Hu Pecht Dasgupta Model
Electro Static Discharge Wunsch and Bell Model, Wunsch and Bell Model, Wunsch and Bell Model
Determination of Failure Rate (Point Estimate)
Failure rate can be determined by using actual test results. Determine "demonstrated" failure rate from actual test data as follows:
Failure Rate=No. rejects/sample size x no. hours
Example 1. Assume a sample size of 13500, 2 failures and test duration of 500 hours. To calculate FR:
FR = 2 rejects/13500 devices x 500 hoursFR = 2/6750000 device-hours=0.000000296 rejects per device-hour 296 FITS or 3375,000hours MTBF (reciprocal of 0.000000296)
In expressing Failure Rate, the equivalent values below may be helpful.
No. Failure Per Device-Hours
Failure Rate% Per 1000 Hours
PPM (Hours) FITSMTBF (Hour)
1/1 x 109 0.000000001 0.0001 0.001 1 1 x 109
1/1 x 108 0.00000001 0.001 0.01 10 1 x 108
1/1 x 107 0.0000001 0.01 0.1 100 1 x 107
1/1 x 106 0.000001 0.1 1 1000 1 x 106
1/100,000 0.00001 1.0 10 10,000 1 x 105
1/10,000 0.0001 10.0 100 100,000 1 x 104
1/1,000 0.001 100 1000 1,000,000 1 x 103
Determination of Failure Rate (Statistical Estimates)
In addition to point estimates, FR and MTBF may be estimated by using the chi-square statistic at 2 (r + 1) degrees of freedom. The 50% probability statistic would give the "best estimate", the 60% or 90% probability statistic would give the upper confidence limit.
Acceleration Factors
In order to express accelerated test results in terms of expected failure rate at actual use conditions, semiconductor manufacturers commonly use the Arrhenius model.
The Arrhenius model assumes that degradation of a performance parameter is linear with time, with the rate of degradation depending on the temperature stress. To put it another way, the Arrhenius equation relates the time rate of change of a process to the temperature at which the process is taking place.
If appropriate, the calculated acceleration factors listed in the following table may be used.
Acceleration Factors for Common Junction Temperaturesand Common Activation Energies
Failure rates and MTBFs obtained from Operating Life Tests pertain when the junction temperature is the same as the ambient test temperature. Temperatures used during OPL tests are usually TA=125°C or TA=150°C. In most cases, these ambient temperatures are very close to the junction temperature TJ . However, when a significant difference between TA and TJ exists, respective TJ must be considered. This would be the case with parts that dissipate significant amounts of power, such as certain linear and MOS devices.
Confidence Factors
The failure rate resulting from a High Temperature Bias test is an average, or estimate, of the typical expected failure rate for a product or process; but has no statistical boundaries established.
National Semiconductor generally states the upper 60% confidence limit for failure rate estimate using the chi-squares statistic, per the following formula.
Values of chi square are found in a number of statistical tables. A few more typical values are shown as follows:
Percentiles of the Chi2 Distribution
(Values of Chi2 corresponding to certain selected probabilities)
Typical Use AQL Best Estimate 60% ConfidenceLTPD or 90% Confidence
Probability in % 5.0 50.0 60.0 90.0
0.05 0.50 0.60 0.90
dfTotal Failures
2
4
6
8
10
12
14
16
18
20
22
26
0
1
2
3
4
5
6
7
8
9
10
12
0.103
0.711
1.640
2.730
3.940
5.230
6.570
7.960
9.390
10.900
12.800
15.400
1.390
3.360
5.350
7.340
9.340
11.300
13.300
15.300
17.300
19.300
21.300
25.300
1.830
4.040
6.210
8.350
10.500
12.600
14.700
16.800
18.900
21.000
23.000
27.200
4.61
7.78
10.60
13.40
16.00
18.50
21.10
23.50
26.00
28.40
30.80
35.60
32
42
15
20
20.100
28.200
31.300
41.300
33.400
43.700
42.60
54.10
With regards to the role of a QAM, that is dependent on the nature of the company and the size of your facility and whether or not you are wearing multiple hats or just one...
Our facility has approximately 250 employees and some of the roles of our Quality System Manager (comparable to a QAM I believe) are as follows:* Management Representative for our ISO Audits* Manage and oversee our Internal Audit Process, including the responsibility for overseeing the training and development of our Internal Auditors* Manage and oversee our Corrective Action Process* Assist in the effective resolution of our Customer Complaints* Manage and oversee our Quality System Documentation* Organize and schedule our Management Reviews* Help support our Supplier Management Program (in conjunction with our Purchasing and Maintenance functions)* Assist in the Quality Planning portion of Product Realization* etc.
PS: Our Quality System Manager currently wears one hat.
Just our slant on things...__________________~ ERL ~ :)
There went the easy answer. Here is a list of the non-contract specific things I normally handle.
Ensures documentation of quality procedures and work instructionsDevelop and maintain a quality system in accordance with ANSI/ISO/ASQC Q 9001:2000 Quality Management Systems-Requirements (2000-12-15: Third Edition) and ANSI/ISO/ASQC Q 9001:2000.Enforces adherence to the Quality Manual, procedures, work instructions, and ANSI/ISO/ASQC Q 9001:2000 Quality Management Systems-Requirements (2000-12-15: Third Edition).Train auditorsSchedules and communicates information on external auditsPrepare and implement the audit scheduleInterface with project managers and site managerInterface with team leadsInterface with purchasing, system engineer, and quality controlRetain or monitor the retaining of quality records and their anaylsisParticipates Monthly Management Reviews and Corprorate Program ReviewsChair any ISO 9000-based/Process meetingsMay attend department product quality meetingsTake notes at the Management Review meetings with the site managerPerform, schedule, create process awareness training for staffActs as mediator or impartial chair in meetings as ask by managementInterfaces directly with management on process manament resourse needsInforms management of any negitive trendsManage and validate the corrective and preventive action systemManage on the job training databaseCordinate process activities between teamsProcess Cheerleader- rewards for good process and quality related activities & tours to the customer
Quality Manager Responsibilities
Posted on November 16, 2009 by At-PQC™
The Quality Manager is responsible for the administration of the Quality Plan and has
the authority to manage all work affecting quality. The Quality Manager will provide
leadership for the development, implementation, communication and maintenance of
quality systems policies and procedures for the Company according to the approved
quality system. A primary goal is to achieve a high degree of joint ownership of quality
and compliance strategies with all of the major operational stakeholders in the
Company while addressing regulatory requirements in an effective, timely and
responsible manner.
Responsibilities
Formulate and manage the development and implementation of goals,
objectives, policies, procedures and systems pertaining to the quality assurance
and regulatory functions.
Develop, implement, communicate and maintain a quality plan to bring the
Company’s Quality Systems and Policies into compliance with quality system
requirements.
Manage documentation related to Quality System guidelines.
Quality Assurance project lead for cross-functional projects including
determining QA timelines, plans and position strategies.
Manage and maintain the quality aspects of the Design Control Program
including but not limited to design input and output documentation, applicable risk
analyses, verification and validation activities and formal design reviews.
Provide leadership for developing and directing Quality Assurance and Quality
Manage training of all company personnel in the requirements, documentation
and maintenance of the corporate Quality System.
Manage and maintain the Company’s quality inspection and product release
programs for incoming and in-process materials and components, processes and
finished goods.
Establish an auditing program and lead compliance audits of third party
suppliers, manufacturers and distributors.
Report on timely basis to executive management on the performance of the
quality system, any non-compliance issues and recommended actions.
Qualifications
Minimum of 5 years of Quality Systems supervisory/management experience
within a related industry.
Experience interacting with regulatory authorities.
Experience in quality management systems.
Experience in quality system audits.
Working knowledge of design control processes.
Experience with statistical sampling plans and trending analyses.
Knowledgeable about electronic data management.
Professional certifications (e.g. American Society for Quality (ASQ), Certified
Quality Auditor (CQA) desirable).
Skills
Ability to lead projects and programs with a positive “Get It Done” attitude.
Organized, attentive to detail and able to prioritize and handle multiple projects
with competing deadlines.
Works efficiently both on independent basis and as part of a team.
Ability to deal effectively with all levels within the organization as well as with
external parties, including regulatory bodies.
Proven strong problem solving ability with attention to root cause.
Maintains a personal and professional “continuous improvement” philosophy.
Excellent written and verbal communication skills, strong interpersonal skills.
The quality manager should be familiar with management tools for problem solving,
process management and various metrics. Quality managers use problem solving tools
to determine root causes and suggest solutions from various perspectives using data
to make decisions.
Problem solving tools include:
1. The Seven Quality Tools using Pareto charts, cause and effect diagrams,
flowcharts, control charts, check sheets, scatter diagrams and histograms.
2. Basic management and planning tools using Affinity diagrams, tree diagrams,
process decision program charts, matrix diagrams, interrelationship digraphs,
prioritization matrices and activity network diagrams.
3. Process improvement tools using root cause analysis, PDCA, six sigma DMAIC
model, failure mode and effects analysis and statistical process control.
4. Innovation and creativity tools using creative decision making and problem
solving techniques that include brainstorming, mind mapping, lateral thinking,
critical thinking and design for six sigma.
5. Cost of Quality using prevention, appraisal, internal and external failure costs to
suggest ways and means to improve the bottom line.
Process Management Tools include:
1. Planning and setting goals
2. Establishing controls
3. Monitoring and measuring performance
4. Documentation
5. Cycle-time reduction
6. Waste elimination
7. Theory of constraints for local vs system optimization and physical vs policy
constraints that affect throughput
8. Elimination of special causes of variation
9. Maintaining improvements
10. Continuous improvement
11. Process mapping
12. Flowcharting
13. 5 S’s
14. Just in time
15. Kanban
16. Value streams
Measurement, Assessment and Metric Tools include:
1. Goal-question-metric modeling to identify when, what and how to measure
projects and processes
2. Sampling techniques when appropriate
3. Statistical analysis to measure central tendency, dispersion and types of
distributions to monitor processes and make data oriented decisions
4. Trend and pattern analysis to assess data-sets, graphs and charts for various
cyclic, seasonal and environment trends and pattern shifts
5. Theory of variation to identify common and special causes of variation
6. Process capability using Cp and Cpk indices
7. Reliability and validity measurement theories using content, construct and
criterion types of measures
8. Qualitative assessments using anecdotal feedback, observations and focus group
output instead of objective measurements
9. Survey analysis interpretation
Additional quality manager skills include:
1. Customer relationship management to ensure partnerships and alliances
2. Energizing internal Customers to improve products, processes and services
3. Identification and prioritization of Customer needs and expectations using tools
such as Voice of the Customer, House of Quality, Quality Function Deployment,
focus groups and Customer surveys
4. Measurement of Customer satisfaction and loyalty using complaints, surveys,
interviews, warranty data, value analysis and corrective actions
5. Conflicting requirement resolution and management of resources
How-To Achieve the Goal
Cheat – that’s right – cheat; well, another way to put it is to re-design the process to
control the sheet music. Remember the movie clip from “Dune” – “He who controls the
spice controls the universe”? Well, if you control the sheet music then you control the
orchestra. That’s the tail wagging the dog but the technique works. Everybody in the
orchestra needs sheet music so all you have to do is implement Efficient QMS™ in
your business process to truly orchestrate (manage) an efficient quality management
system.
This entry was posted in Efficient QMS™ and tagged . Bookmark the permalink.
What is PPM?
(Parts per million)Click here for print version
PPM (Parts per million) is a measurement used today by many customers to measure quality performance.
Definition: One PPM means one (defect or event) in a million or 1/1,000,000
There was a time when you were considered a pretty good supplier when your defect rate was less than 1%, (10,000 PPM), then the expectation was increased to 0.1% or 1,000 PPM. Now the rate for most automotive components is targeted at 25 PPM or 0.0025%
To calculate: For example, let's say you had 25 pieces defective in a shipment of 1,000 pieces. 25/1000= .025 or 2.5% defective. .025 X 1,000,000 = 25,000 PPM.
Use the PPM Calculator:
Let's put it in perspective. Let's say, you produce 10,000,000 parts per year for your customer. If you're like most companies, your plant operates around 5 days a week, 50 weeks per year or 250 days a year. Let's assume your customers requirements are 25 PPM. That means that you would be allowed 25 pieces for
every 1,000,000 pieces or 250 defective parts per year. Or to put it another way, one bad part per day! Notice I did not say one bad part per day per person or job, or shift or machine. One bad part for the entire plant for 24 hours!
Impossible? Yes if you are still using the same manufacturing methods which were responsible for the 5 or 10% scrap you used to accept.
A friend of mine had the following quotation on his wall:
Insanity is doing things the same way we've always done them and expecting different results.
The monitoring and measurement systems we have today have paved the way for improved quality. We can now control the process in order to control the quality. Quality can not be inspected in after the fact. It is the result of careful planning, design, and execution.
If you don't measure it you can not control it.
If you would like to learn how to reduce your PPM while increasing profits I can help.
First by demonstrating a systematic and scientific approach to design and manufacturing in your facility.
Second, by training your personnel in the use of the tools and methodology.
For a more detailed article on PPM visit the following page.http://www.drdiecast.com/PPM_is_it_possible.htm
Click the following for information on consulting and training services offered by McClintic & Associates.
Process capability indexFrom Wikipedia, the free encyclopedia
In process improvement efforts, the process capability index or process capability ratio is a statistical measure of process
capability: The ability of a process to produce output within specification limits.[1] The concept of process capability only holds
meaning for processes that are in a state of statistical control. Process capability indices measure how much "natural
variation" a process experiences relative to its specification limits and allows different processes to be compared with respect
If the upper and lower specification limits of the process are USL and LSL, the target process mean is T, the estimated mean
of the process is and the estimated variability of the process (expressed as a standard deviation) is , then commonly-
accepted process capability indices include:
Index Description
Estimates what the process would be capable of producing if the process could be centered. Assumes process output is approximately normally distributed.
Estimates process capability for specifications that consist of a lower limit only (for example, strength). Assumes process output is approximately normally distributed.
Estimates process capability for specifications that consist of an upper limit only (for example, concentration). Assumes process output is approximately normally distributed.
Estimates what the process is capable of producing if the process target is centered between the specification limits. If the process mean is not
centered, overestimates process capability. if the process mean falls outside of the specification limits. Assumes process output is approximately normally distributed.
Estimates process capability around a target, T. is always greater than
zero. Assumes process output is approximately normally distributed. is also known as the Taguchi capability index.[2]
Estimates process capability around a target, T, and accounts for an off-center process mean. Assumes process output is approximately normally distributed.
A useful way of planning is to break down tasks into a hierarchy, using a Tree Diagram. The PDPC extends the tree
diagram a couple of levels to identify risks and countermeasures for the bottom level tasks. Different shaped boxes are
used to highlight risks and identify possible countermeasures (often shown as 'clouds' to indicate their uncertain nature).
The PDPC is similar to the Failure Modes and Effects Analysis (FMEA) in that both identify risks, consequences of
failure, and contingency actions; the FMEA also rates relative risk levels for each potential failure point.
[edit]Activity Network Diagram
This tool is used to plan the appropriate sequence or schedule for a set of tasks and related subtasks. It is used when
subtasks must occur in parallel. The diagram enables one to determine the critical path (longest sequence of tasks).
(See also PERT diagram.)
[edit]References
This article does not cite any references or sources.Please help improve this article by adding citations to reliable sources. Unsourced material may be challenged andremoved. (October 2008)
[edit]Further reading
Brassard, M. (1996) The Memory Jogger Plus+. ISBN 1-879364-83-2.
Seven New Management and Planning Tools
Seven Basic Tools of Quality .
QS-9000
QS-9000 is the name for the Quality System Requirements used to increase customer confidence in the quality of its suppliers.
The idea of QS-9000 is quite similar to ISO-9000, International Quality System Standard, but QS-9000 applies particularly to the automotive industry for Chrysler Corporation, Ford Motor Company, General Motors Corporation, and truck manufacturers. QS-9000 is made up of three sections: an ISO-9000 based requirement, a sector-specific requirement, and a customer-specific requirement. These requirements guarantee a supplier procures a good quality product. Furthermore, by developing QS-9000, we will be able to improve our product, customer satisfaction, and supplier relations as well.
Standards for ISO-9001 and QS-9000 ____________________________________________________________________ ISO QS Quality System Requirements 9001 9000 -------------------------------------------------------------------- Management Responsibility X X Quality System X X Contract Review X X Design Control X X Document and Data Control X X Purchasing X X Control of Customer-Supplied Product X X Product Identification and Tractability X X Process Control X X Inspection and Testing X X Control of Inspection, Measuring, and Test Equipment X X Inspection and Test Status X X Control of Non-Conforming Product X X Corrective and Preventive Action X X Handling, Storage, Packaging, Preservation and Delivery X X Control of Quality Audits X X Training X X Servicing X X Statistical Techniques X X -------------------------------------------------------------------- Production Parts Approval Process X Continuous Improvement X Manufacturing Capability X -------------------------------------------------------------------- Customer-Specific Requirement X ____________________________________________________________________
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Quality
Quality means a totality of characteristics of an entity that bear on its ability to satisfy stated and implied needs. In some references, Quality is referred to as "fitness for use", "fitness for purpose", "customer satisfaction", or "conformance to the requirements."
To achieve satisfactory quality we must concern all stages of the product or service cycle. In the first stage quality is due to a definition of needs. In the second stage it is due to product design and conformance. In the last stage quality is due to product support throughout its lifetime.
There are two major aspects of quality: quality of design and quality of conformance. Quality of design involves the variations of a product or services in grades or levels of quality. This includes the types of materials used in construction, tolerance in manufacturing, reliability, etc. Quality of conformance concerns how well the product conforms to the specifications and tolerances required by the design. Quality of conformance is influenced by the choices of manufacturing processes, training and supervision of the workforce, the type of quality-assurance system used, and the motivation of the workforce to achieve quality.
Source inspection is a technique used to prevent product defects by controlling the conditions that influence quality at their source. It is the performance of the supplier's facilities to increase customer confidence with the supplier's product quality. The following elements are essential parts of source inspection.
The quality history of suppliers. Any possible effects that occur during purchasing, based on the performance, safety, and
reliability of the final product. Product complexity. The ability to measure the product quality from buyer data. The availability of special measuring equipment at the buyer's plant to perform the required
inspection. The product's nature and its quality.
It is important to have either external or internal company inspectors to assure adequate product control. A sources inspection is performed to insure that the decision making is correct and unbiased. Furthermore, source inspection can be devised into two categories as follows;
1. Vertical source inspection inspects the process flow to identify and control external conditions that affect quality.
2. Horizontal source inspection inspects an operation to identify and control interval conditions that affect quality.
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SOP - Standard Operating Procedures
Standard Operating Procedures (SOP) are the instructions that cover operational parts. Initially, an SOP is based on Armywide publications and then modified to use local operating conditions and command policies as a guideline. The scope of SOP is extensive and varies. It provides the major instructions for all division elements of operational features.
In general, there are two formats for an SOP to follow:
A format that publishes all comprising documents which details of the function and the responsibilities of subordinate units.
A format that is published as a basic document which includes general instructions to all units. This kind of format has specific instructions for each individual unit. It is more detailed and easier to use.
SMED, often called "Quick Changeover", is an process that can help us to reduce downtime due to set-ups and changeovers. Quick Changeover means we reduce time to set up a machine or process. We use SMED as a guideline to eliminate our waste changeover time in our production process, especially while changing a machine from one product to another.
There are six major steps that we should be concerned with :
1. Ensure that everything needed for setup is already organized and on hand to save time finding something in the process setup.
2. It is good to move your arms but not your legs to avoid spending too much time during adjustment or set-ups.
3. Do not remove bolts completely to save time during removing bolts and setting up the process.
4. Regard bolts as enemies; do what ever you can to get rid of them to save time by using some equipment that is better than bolts when changing the process.
5. Do not allow any deviation from die and jig standards to save time by using the same standards. For example, use the same size of nut and bolts for each die and jig.
6. Adjustment is waste to make the jig or figure simple to setup and avoid wasting time to adjust the positions.
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SPC - Statistical Process Control
Statistical Process Control (SPC) is an collection of statistical techniques that are used to monitor critical parameters and reduce variations. We used SPC to achieve process stability and improve the capability through reduction of variability. Often the term "Statistical Quality Control" is used interchangeably with "Statistical Process Control."
The objective of SPC is to get a process under control. This is done by identifying and eliminating any specific causes of variation not associated with the process itself. A process that is in control will constantly perform within its own natural limits.
SPC can be broken into two components: process control and acceptance sampling. In process control, SPC involves these seven tools: Histogram, Check Sheet, Parato Chart, Cause and Effect Diagram, Defect Concentration Diagram, Scatter Diagram, and Control Chart These tools often called "The Seven QC tools." Most of the tools help us to identify a problem in the process. Acceptance sampling is used to reduce variation in the process by using statistical sampling techniques to select the proper sampling size and to interpret whether our whole product should be accepted or rejected.
Sampling is the process of obtaining samples from a large group of data (or called population). There are numerous data, so it is difficult or impossible to examine the whole group. Examining all data will expend a lot of time, so doing only a small part of entire data, a sample, is more appropriate. Additionally, sampling theory is a study of the relationship between the whole data and the samples. It is useful to understand whether there are differences between two samples.
All possible samples of size n can be drawn from a given population. For each sample, we can calculate a statistic; for example, the mean and the standard deviation of the data will vary from sample to sample. So a sampling distribution is useful to explain the data characteristics.
There are three types of sampling processes:
1. Single sampling is composed of selecting a specifically random sample of n items from each group of items presented, and then condemning each group depends up on the results. For example, chose n items from each group for inspection. We will accept the group if the number of defects is less than or equal to d, a specific value. Otherwise, we will reject them.
2. Double sampling is composed of selecting two specifically random samples of n1 and n2 from data. By a technique of this type, the results of selecting a first sample (n1) are accepting the group, rejecting, or talking another sample of n2 items. The decision making depends on the associated results.
3. Multiple sampling is a technique of sampling that is similar to the double sampling, but there are more than two sampling items used in decision making.
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Scatter Diagram
A scatter diagram is a graphical diagram to show the relationship between two data variables. It is used to display the change of one variable when another changes. From a scatter diagram, we can find a mathematical equation that relates to the variables. To create a scatter diagram, these steps are followed:
Collect data. This is the most essential step. Build a data sheet to show the information from the data. Define the variable axis of the graph.
1. The horizontal axis (X axis) displays the variable's measurement values; most are cause variables.
2. The vertical axis (Y axis) shows the measurement values of another variable; most are effect variables.
Plot data on the graph. Construct a mathematical equation.
From a scatter diagram, curves are tentatively devised for linear and non-linear curves. With this, we can call two relationships between variables to linear and non-linear relationships.
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Self Inspection
Self inspection is a technique of inspection in which workers check their own work. Self inspection provides the most immediate feedback. With this technique, the worker may accept products that ought to be rejected. Furthermore, the worker may not notice all the errors.
On the other hand, if the errors in decision and careless mistakes are eliminated, self inspection would be the efficient technique. However, it could be improved by developing tools or using devices that could automatically detect defects or mistakes. Providing new knowledge of quality processes to workers is an efficient method to improve the self inspection technique.
Generally, the results from inspections are reported in terms of the total percentage of defects. With this method, inspectors will check the final products. They may find some mistakes or product errors, but they will not know the actual error source. As mentioned, self inspection is a method to solve this problem.
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Sensory Inspection
Inspections involve distinguishing acceptable from unacceptable goods and comparing them with a standard. Sensory inspection is a kind of inspection, conducted by the human senses, such as
inspections of paint saturation or judgments of plating adequacy. They are different from physical inspection, which involves the use of devices, like calipers, micrometers or gauges, to measure.
For inspection of this kind, it is difficult to set criteria because it depends on the physical condition of human workers, the period of work, and the skills acquired from experience. Naturally, different people have different senses and even the same person may make different judgments at different times. It is laborious to judge an object with a complex form or a not-well-defined shape.
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Seven Steps or Seven QC Steps
The 7 QC Steps process is a structured problem solving approach for improving weak processes. This approach is known as reactive improvement. The 7 QC Steps is easy to understand and learn, easy to use, and easy to monitor.
The 7 QC steps process is structured as follows:
Step 1: Select a Theme. In this step, the weakness in the process or the problem to be solved is clarified in a theme statement. A Flowchart, a Theme Selection Matrix, or a Cause & Effect Diagram is used as a tool in this step.
Step 2: Collect and Analyze Data. This step focuses facts about the problem and discovers what types of problems occur frequently. When collecting data, you must think of all possible causes. Checksheets and Pareto Diagrams are the tools most often used.
Step 3: Analyze Causes.With sufficient data from step 2, the root cause, or fundamental cause, is found by constructing a Cause & Effect Diagram.
Step 4: Plan and Implement Solution. In this step, you brainstorm for ideas that are causing the problem and develop a solution that prevents the root cause from recurring. Then, you implement an adjustment to the process. The 4W's and 1H Matrix (What, When, Where, Who, and How Matrix) is used to develop a plan.
Step 5: Evaluate Effects.You evaluate the effects of implemented solution to make sure the solution worked and does not have unacceptable results from the comparison of data, before and after the implementation of the solution. In this step, comparative Pareto Charts and Graphs are frequently used to identify the results.
Step 6: Standardize Solution. A standardized solution is confirms that the old process is replaced with an improved process and indicates that the solution is workable. A flowchart is most often used.
Step 7: Reflect on Process and the Next Problem. In this step, you consider what the team's accomplishment was in the first 6 steps and recommend a weakness to work on next.
Seven QC tools are fundamental instruments to improve the quality of the product. They are used to analyze the production process, identify the major problems, control fluctuations of product quality, and provide solutions to avoid future defects. Statistical literacy is necessary to effectively use the seven QC tools. These tools use statistical techniques and knowledge to accumulate data and analyze them.
Seven QC tools are utilized to organize the collected data in a way that is easy to understand and analyze. Moreover, from using the seven QC tools, any specific problems in a process are identified.
7QC tools always include :
Check Sheet is used to easily collect data. Decision-making and actions are taken from the data.
Pareto Chart is used to define problems, to set their priority, to illustrate the problems detected, and determine their frequency in the process.
Cause-and-Effect Diagram (Fishbone Diagram) is used to figure out any possible causes of a problem. After the major causes are known, we can solve the problem accurately.
Histogram shows a bar chart of accumulated data and provides the easiest way to evaluate the distribution of data.
Scatter Diagram is a graphical tool that plots many data points and shows a pattern of correlation between two variables.
Flow Chart shows the process step by step and can sometimes identify an unnecessary procedure.
Control Chart provides control limits which are generally three standard deviations above and below average, whether or not our process is in control.
