NOTES: WEEK ONE
Syllabus and Course Overview
Course as a SEMINAR
Note on Notebooks
TOPIC ONE: DEFINING QUALITYWHAT IS QUALITY? (discussion)
Your Perception…
HOW AND WHY HAS QUALITY CHANGED SINCE 1800 TO DATE?
(discussion)
QUALITY Definitions:
Customer Satisfaction
Elimination of waste
Perfection
Compliance with customer requirements
Do it right the first time
Providing a better product than competition
ASQ definition: "Quality is the totality of features and characteristics of
a product or service that bears on its ability to satisfy given needs".
CRITERIA FOR QUALITY:
Judgemental: Transcendent….can’t really put a finger on it …just
perceive its there.
Examples: Mercedes-Benz
Rolex Watches
Lexus
Problem: No Basis for measuring improvement.
Product Based: Quality is reflected in QUANTITY of some attribute.
Example: 10 pages per minute, 1028 resolution, 16 valves
Problem: Higher quantity is assumed to mean higher quality,
leading to perhaps the misconception that higher price means
higher quality.
User-Based: Quality is presumed to be what customer wants. …..classic
definition"…..fitness for intended use"
Problem: Individuals have different needs, desires and
therefore different quality standards.
Example: Screwdriver…..Craftsman…. fasterners vs.
crowbar.
Value-Based: Quality is based on value…e.g. product is just as good
as competitors, but priced lower.
Example: Wal-mart value pricing.
Problem: Matching customer needs with value
pricing…..maintaining "image"
Manufacturing-Based: Conformance to specifications.
Example: OAL 75 mm +/- .05 mm
Problem: May be within specifications but not what the
customer needs or wants.
Advantage: Have something that can be measured, monitored,
and evaluated for improvement.
Garvin’s Eight Principle Quality Dimensions (refer to page 12, 13)
Performance
Features
Reliability
Conformance
Durability
Serviceability
Aesthetics
Perceived quality
THE VIEW OF QUALITY IS RELATIVE!
Designer
Supplier
Manufacturer
Distributor
Consumer
QUALITY IN PRODUCTION SYSTEMS:
DEMING EMPAHSIZED THE LATERAL STRUCTURE AND RELATIONSHIP OF "CUSTOMERS"
WHO IS THE CUSTOMER WITHIN AN ORGANIZATION?
……WITHIN A DIVISION?
……WITHIN A DEPARTMENT?
……WITHIN A UNIT?
CAN PRODUCTIONS SYSTEMS MODEL BE USED FOR SERVICE INSDUSTRY?
EDUCATIONAL INSTITUTION AS EXAMPLE AND PROBLEM FOR ASSESSING QUALITY.
…..INCLASS DISCUSSION.
Sumary and Points!
For Quality to be REAL, there must be tangible factors that can be monitored for improvement.
Must understand the "product"
Attributes
Variables
Must understand the relationship of customers
Must understand the relationship of stages of processing
Must bring about personal responsibility and accountability
Discussion of assignments:
READ CHAPTER 1….NOTE THE KEY POINTS
Quality Model of Prior workplace
Personal Quality Assurance Plan (refer to page 25 in text)
Baldridge Award and Criteria Framework
http://www.quality.nist.gov
Chrysler Case Study
Begin project identification
NOTES: WEEK TWO----AUGUST 26, 1999Discussion of Baldridge Criteria;
Discussion of Chrysler Case;
Briefing on Quality Self Improvement Plans
Presentations of Quality Assurance in a prior workplace
TONIGHT: BUILDING A QUALITY MODEL
Quality in the U.S. today is: (discussion)
Quality must be orchestrated, not dictated
Three levels of quality:
Organizational level
process level
performer levelInfrastructure and path analysis (who are the customers?)
Benchmarking and measuring success
Quality of "Service"
ISO certifies that a SYSTEM is in place for: (discussion)
Documentation
Communication
Job analysis
Vendor certification
Tracking
FeedbackDiscussion: How would you assure quality in a "startup" business?
QUALITY IN MANUFACTURING
Productivity, Quality, and Cost
Life Cycles
Improvement vs. profit
Streamlining
Benchmarking
Reverse Engineering
Team empowerment
House of Quality (QFD)
QUALITY IN SERVICE
Discussion ...customer feedback / tech support
DIFFERENCES IN MANUFACTURING AND SERVICE
Output of services more intangible, manufacturing produces tangible products. Service organizations involve more
human factors which increases the variability and potential for error going unchecked. Inspection and quality control
methods are more difficult to employ in service organizations. Services are consumed....cannot be inventoried like
manufactured goods. Manufacturing is more capital intensive.....services more labor intensive. Automation of
quality is more capable in manufacturing...can be "built into the processing". Service delivery system is most critical...
and time sensitive....more critical link in quality of service through interaction of providers and customers.
Manufacturing typically there is delayed assessment ...products are used, consumed...evaluated...a more systemaic
evaluation of performance and feedback can be put into place for the quality assurance model.Summary and key points:
Total quality for effective operation in manufacturing and service systems requires a model must be in place...
Deming's Model applicable to manufacturing and service organizations
Measurement of success ...must have some comparison....benchmarking
Three levels of quality: Organizational, process, performer
Differences in manufacturing vs. service:
NOTES WEEK 3 : 02 - SEPT - 99UPDATE SUMMARY AND TARGETED DIRECTIONS
Defining Quality
Identifying Models
Recognizing Standards
Quality through Design
Quality Control and Process Improvement
Thus far we have looked at the following:
I.Defining Quality
Dimensions of Quality
Criteria for Quality
Recognizing Quality
Awards
Standards
Quality and competition
Quality Models (e.g. manufacturing model: Inputà Processà Output
Levels of Quality
Measurements of Quality
(Productivity vs. Quality and Costs)
II.Historical Influences on Changes in Quality
A.Some Leaders in Quality:
Deming (1900-1993)
14 Points for obtaining quality;
Plan -Do-Check-Act cycle for continuous improvement;
Ardent support for training and data-based problem solving.Juran (1904 - )
Editor of The Quality Handbook;
Many management strategies and process re-engineering foundations;
Qualty trilogy : Planning , control, and improvement;Feigenbaum (1929 - )
Concept of total quality control;
Clarification of quality costs (particularly due to poor quality);
Concept of "hidden plant" (plant capacity required for rework);
Ishikawa (1915 -1989)Registered the first quality control circle in 1962
Cause - effect diagreams
Elemental statistical methods….simplified statistics for effective useCrosby (1926 - )
Concept of zero defects as the only acceptable quality goal;
Published "Quality Is Free"
Defined quality as meeting customer requirements;
Taguchi (1924 - )Simplified experimental design and emphasized efficiency
Robust designs for effective, efficient production and customer use
Quality loss functionSome highlights include the following:
0. Emphasis on craftsman prior to industrial revolution;
1.1760-1860 Industrial revolution: Invention, mechanization, factory system;
2.1900-1920 Scientific management: Standardized work tasks based on Taylor's work;
3.1927 Hawthorne studies: Emotional and social factors shown to be relevant to motivation;
(foundation of organizational behavior);
4.1938 Operations research evolved and ---quantitative basis largely due to WWII
5.1960's Just in time: Short cycle production methods…Leader: Toyota;
Total Quality Management
6.1970's Computer-driven production planning: MRP systems…Leader in implementing: US
Implementation of quality circles
7. 1980's Team strategies and empowerment;
8.1980's to date Quality methods applied to service-sector
9.1980's to date fierce competition, global marketsChanges in operations strategies:
Quality: Quality-driven success proves itself in competitive industries;
Time (speed) Delay-free response draws customers, exposes causes of bad quality
Avoids complex costly control monitoring systems;
Globalization Political trade barriers fall, massive new markets open up (European
Community, former Soviet Bloc, China, India…..)
Teaming and Partnering: Mergers, takeovers global expansions…(external teaming)
Internal teaming also brought about quality improvement, customer response
Flexibility and agility: Quick, flexibility response from agile organization….rapidly
Changing markets….trying to gain competitive edge.
10. 1980's - date stronger emphasis of total quality …formulation of strategies
Proven models
Benchmarking
Standards
Designing in quality
QFD
CE
DFM
NOTE: Item 10 will be the focus tonight.
AN OPERATIONS STRATEGY MODEL:
Formulation
Customers:
1.Know and team up with next and final customer
2.Dedication to rapid response, flexibility, variability, and service
3.Continuous improvement in qualityCompany:
4.Achieve unified purpose and mission through shared information
And team involvement in planning and implementation of change
Competition:
5.Know the competition and world class leaders.
Implementation
Design and Organization:
1.Cut the number of product or service components or operations
And the number of suppliers to a few good ones.
2.Organize resources into multiple "chains of customers," each
Focused on a product, service, or customer family; create
Work-flow teams, cells.
Capacity:
3.Continually invest in human resources through cross-training
Education, job and career development; improved health,
Safety, and security.
4.Maintain and imporve present equipment and human work
Before thinking about NEW equipment; automate incrementally
WHEN process variability cannot otherwise be reduced.
5.Look for simple, flexible, movable, low-cost equipment that can
Be acquired in multiple copies---each assignable to work-flow
Teams, focused cells (Standardization)
Processing:
6.Make it easier to make/provide goods or services and reduce
Variation.
7.Cut flow time (wait time) distance, and inventory along chains
Of customers.
8.Cut setup, changeover, startup times.
9.Operate at customers rate of use (decrease cycle interval and lot
size).Problem Solving and Control:
10.Record and OWN quality, process, and problem data at the
workplace.
11.Ensure front-line teams get first chance at problem solving (Who
are the real experts?)
12.Cut transactions and reporting;
13.Control CAUSES not symptoms.Benchmarking:
We touched on bench marking last week; however we need to revisit:
First developed at Xerox Corporation in '70's….idea was to search for the best
practices for improving a company's own processes regardless of the source.
Became known as competitive benchmarking….however later expanded shared
resources and trading of knowledge. Today it is in wide use by manufacturing
and service sectors….hotels, law firms, transportation, manufacturing, banks,
fast-food companies and many others.THE BENCHMARKING PROCESS:
Getting Started
Planning
Organizing
Managing for benchmarkingPreparing
Identify key process
Form team
Understand own processResearch
Collect information
Who is better?
What to ask?Selecting whom to benchmark
Establish Relationship
Plan to collect and SHARE informationCollecting and sharing Information
Surveys
Site visits
Common 3rd partiesAnalyzing and Improving
Compare data
Plan to surpass
Implement and monitor
ImproveISO STANDARDS:
To assure quality, vendor certification became more common in the 1970's. Manufacturers began to streamline
and concentrate on fewer, reliable, efficient and proven or "certified" suppliers. While many companies have
established their own criteria, a need for global standards evolved as markets and suppliers expanded. The
European Community was a major force in endorsing the adoption of unified and recognized standards. ISO
9000 Series Standards evolved. Original standards were published in 1987 by the International Organization for
Standardization, based in Geneva, Switzerland. The term "iso" is Greek for "uniform" and was adopted as the
umbrella for describing the standard. Actually, the series includes the following standards:ISO 9000 Quality Management and Quality Assurance Standards -Guidelines for
Selection and Use.
ISO 9001 Quality Systems - Model for Quality Assurance in Design, Development
Production, Installation, and Servicing.
ISO 9002 Quality Systems - Model for Quality Assurance in Production, Installation,
And Servicing
ISO 9003 Quality Systems - Model for Quality Assurance in Final Inspection and Testing.
ISO 9004 Quality Management and Quality System Elements - Guidelines
Note: ISO 9000 registration does not certify quality of goods and services…it registers the
Existence of proper quality plans, programs, documentation, data, and procedures.
DESIGNED QUALITY
Design is the first step to quality:
Should target two critical areas:
1.What the customer wants
2.Processes that provide themNOTE: DON'T THINK OF THIS AS A CORPORATE MODEL BUT RATHER HOW IT CAN BE APPLIED TO
ORGANIZATIONS, DEPARTMENTS, TEAMS, AND INDIVIDUALS.STAGES: THE QUALITY ACTION CYCLE
1.DESIGN QUALITY IN
2.PERFORM SELF INSPECTION AND CORRECTION
3.FIND DEFECTS (BEFORE PASSING ON)
4.COLLECT AND ANALYZE DATA1.CARRY OUT PROCESS IMPROVEMENT PROJECTS
TOOLS AND METHODS: TEAMING UP
QFD
CE
DFM
QUALITY FUNCTION DEPLOYMENT (QFD)
QFD is a structured approach for integrating the desires and needs of the customer into the
design.Provides a way of looking at the "BIG PICUTRE"
Focus is on :
Voice of the customer
What are the requirements
How are they addressed in the design
Ranking compared to cometition
Specifications and target valuesThe QFD Matrix combines benchmarking, customer demands, product characteristics to
improve product quality.DIAGRAM
ASSIGNMENT: TEAM (CLASS) FOR NEXT WEEK: QFD FOR ……FAST FOOD…
EXPLANATION
CONCURRENT ENGINEERING
CE must involve team efforts for addressing asthetics, function, processing. Selection of teams
Including customers, designers, vendors, fabricators, assemblers, packing, distribution….
OVER THE WALL CONCURRENT
Grows out of control if organization is not controlled Easier to adopt to smaller organization
SLOW to make change Essential for rapid change
COSTLY Cuts costs up front
DESIGN FOR MANUFACTURABILITY (DFM)
Design to target markets and target costs
Minimize number of parts and number of operations
Ensure customer requirements are know and design to them
Ensure process capabilities are know (yours and suppliers) and design to them
Use Standards: procedures, materials, processes (known and proven)
Design multifunctional/multiuse components and service elements and modules
Design for ease of joining, separating, servicing
Design for "one-way" assembly, one-way travel (no back tracking)
Avoid special fastners, connectors and off-line or misfit service elements
Avoid fragile designs requiring special attention or changes standardsDIAGRAM: CLASS TEAM ASSIGNMENT FOR NEXT WEEK: REDESIGN FOR DFM
NOTES: SEPT 9,COURSE SECTIONS:
1. MODEL DEVELOPMENT
2. TECHNICAL PROCEDURES
3. RELIABILITY AND IMPROVEMENTI. HAVE WE SUCCEDED IN ESTABLISHING THE "BIG PICTURE" WITH RESPECT TO
QUALITY ASSURANCE AND THE FRAMEWORK REQUIREMENTS FOR ESTABLISHING
A QUALITY ASSURANCE PLAN?A. WHAT HAVE YOU LEARNED SO FAR ABOUT QUALITY ASSURANCE (DISCUSSION)
FOCUS: TRANSFER OF KNOWLEDGE.
II. PRESENTATION OF INTERVIEWS:
A. Focus on questions presented.
B. Evaluate from the view point of the group as a Quality Assurance team.1. Is a Quality MODEL in place?
2. Are Internal and external customers identified?
3. Are relationships established?
4. Are methods delineated for WHAT to measure?
5. Have measurement methods been established?
6. Have quality standards and criteria for compliance been established?III. DISCUSSION OF QFD ASSIGNMENT:
POINT OF QFD ASSIGNMENT: A relationship MUST be established for "cause and effect", what
vairiables to "control", how improvements can be recognized, where the firm stands with respect to
competition. QFD is A (one) SYSTEMATIC approach to BEGIN the QUANTIFYING process.
III. DISCUSSION OF DFM ASSIGNMENT:
POINT OF DFM ASSIGNMENT: Resources may be "thrown" at creating a STRONG Q.A and Q.C.
program that may be UNNECESSARY IF the product can be simplified through:- Emimination of Fastners
- Standardization of fastners or components
- Unitized design and fabrication
- Snap together assembly
- Compliance "built in"
Discussion of Burger King, Fuddruckers, and Subway:
What are they in the business of?
What Model is used?
What is the difference between how quality assured?
ASSIGNMENT: From what we have covered to date (including case studies, outside readings, interviews,
and other resources, develope a "USER'S GUIDE" for developing a Q.A. Plan.
NOTE: This will be the guide for your project.NEXT: TECHNICAL ISSUES IN QUALITY. Read Chapter 12: (Most should be review). We will
do the following in class next week:Example 4 - page 588
Example 5 - page 594
Example 7 - page 603Homework assignment will be problems 1-5, page 625 DUE 9/23
Note: A Quality Module is Posted Under MET366, Modules.....please review prior to 9/23.
16 SEPTTONIGHT:
+ DISCUSSION OF QFD ASSIGNMENT FROM LAST WEEK
+ BUILDING A MODEL: GUIDELINES FOR QUALITY ASSURANCE
* What is the firm in business for?
* What is the product?
* Who are the customers (external) ?
* Who is the competition?
* What is the current "model of flow"...e.g. flow diagram
* What are the inputs / processes / outputs ?
* Who are the customers (internal)?
* What are the variables and relationships (sources, causes and effects)?
* What criteria and standards are required?
* What variables are to be measured?
* What data will be analyzed?
* How will data be analyzed?
* What does it mean? (who will interpret?)
* How will "feedback" occur
* How will the improvement plan be implemented?
+ INSTRUCTIONAL MODULE: QUALITY AND METHODS OF ASSURANCE (Click Here for Graphics Version)
PURPOSE
The term quality is often used to promote a manufacturer's product as being superior to a competitor. But, how is quality integrated in the
manufacturing plan, and how is quality, defined, measured, and assured? These questions will be addresses in this short module on quality
assurance. The purpose of the the module is to provide a brief look at the tools and procedures currently being carried out in industry. While quality
may involve simple gauging, Total Quality Management (TQM), ISO full compliance,and more, the purpose of this module is to look a a few select
aspects of quality assurance including, inspection, statistical process control, process capability, and introduction to DOE.OBJECTIVES: After completing this module, you should be able to do the following:
Distinguish between Quality Control and Quality Assurance;
Develop a Cause-And-Effect Diagram for a simple process;
Explain the difference between attributes and variables;
Calculate and interpret a "Z" score;
Explain six sigma relative to quality;
Outline the "components of Statistical Process Control;
Define Process Capability;
Outline a simple Design for Experimentation;
Interpret the results of a two-level, two factor experiment.TERMS:
ATTRIBUTE
VARIABLE
VARIATION
COMMON CAUSE VARIATION
SPECIAL CAUSE VARIATION
MEAN
STANDARD DEVIATION
SAMPLING
STATISTICAL PROCESS CONTROL
CONTROL LIMITS
CONTROL CHARTS
PROCESS CAPABILITY
DOE
INTRODUCTION
Quality may be defined by different people using various descriptors; however, it ultimately means how satisfied the customer is or to what degree
is a product or service "fit for use". Quality is achieved through either quality of design or quality of conformance. Quality design means the
different levels of performance, reliability, function or serviceability that result from decisions made by engineering and management. On the other
hand, conformance means the systematic reduction of variability and elimination of defects. Further, standards have been adopted to assure not only
how, but the manner in which quality is carried out. Suppliers may be required to become certified in order to maintain the business of being a vendor
to a manufacturer in other words "Vendor Certification" and ISO Certification may be required. While, these topics are beyond the intention of this
module, the are mentioned to emphasize a point: THERE ARE NO ABSOLUTES, EVERYTHING VARIES IN INDUSTRY OR EVERYDAY
LIFE. There are differences in twins, or ball bearings or basketballs, cookies, or sparkplugs....everything varies. The goal, is to identify and
measure, and control the sources of variation. Sounds too simple....it is. We will look at a few common tools used in trying to seek improvement in
quality. Quality is NOT something that can be added on in the end it must be integrated throughout and become a holistic approach for continuous
improvement throughout the organization.INSPECTION
By the strick definition, quality control implies meausrement and inspection (usually after the fact) and thus is a method of detection. On the other
hand, quality assurance is a prevention system that seeks to correct problems BEFORE bad parts are produced. In either case, inspection is
necessary to determine if a product is within the required specifications. Inspections are conducted is to check how well a product conforms to
specifications. Quality is not cheep! Usually it isn't possible to check 100% of all product; thus, sampling methods are used in making decisions
about whether to reject or accept a lot or production run. This inspection must be on-going and continuous because of variation. There are two basic
ways in which inspections can be carried out. These involve checking attributes or variables. Attributes are measured using pass/fail, or GO/NOGO
gauging. While checks can be carried out simply, analysis of "why" or trending, cannot be conducted without variable measurement. Variable
measurement is a quantitative measurement of specific characteristics of interest such as dimensions, mechanical properties, and surface finish
roughness. An example of attribute versus variable inspection is shown below.
STATISTICAL METHODS FOR QUALITY CONTROL
Statistical methods are used to evaluate not only if a product is conforming to specifications, but also how well it conforms. In other words, the
goal is to seek and detect variation in the process. There are too major types of variation that occur. Common cause variation and special cause
variation. Other terms commonly used are natural chance causes or assignable causes. An assignable causes can be traced to a specific and
controllable cause. While the source of variation is is virtually infinite, there are typically five categories of variation of concern.
These include variation in or by humans, materials, machines, measurement, and the environment. Similarly, there are quality tools that are available
to assist in the detection of variation including both graphical and statistical.The major graphical tools of statistical methods include:
1. Histograms
2. Pareto Charts
3. Cause-and-effect diagrams
4. Control charts
5. Scatter Diagrams
Descriptive Statistical Measures
Consider a process that involves an assembly of a gear on a shaft. One of the variables of interest would be the outside diameter of the shaft and
the the other the inside diameter of the gear. The attribute approach would simply check to see if the tolerance range is met by each.
However if quantitative measurements are taken, the degree of variation can be determined through statistical tools, and a systematic analysis of
determining causal relationships can begin.If quantitative data is obtained, variable measurements are descriptive statistics such as the mean and range of variance about the average or
mean. The mean is the arithmetic average of the data found by summing the each observation and dividing by the total number of observations.
The range is the difference between the maximum and minimum values recorded.
Range only describes the overall "spread" but does not tell how much the data values vary from the mean. A more useful measure of variability is
the standard deviation. Remember that sampling is usually conducted and the "statistics" of the sample are used to estimate the "parameters" of
the population.The standard deviation is very useful when the distribution of the process variable under consideration is NORMAL. The sample standard deviation
is the square root of the variance and is found using the following formula:There are specific characteristics of the normal distribution that make it useful in analyzing data.
Lets look at an example of how the normal distribution might be used to estimate how many parts might be out of tolerance on the "high' side based
on the mean and standard deviation of the sample.Example Problem:
Plain carbon steel bushings are heat treated and temperated with a specification set to a Rockwell C of 36 +/- 4. The process is well established and normally distributed. From historical data the cummulative "Gand Mean" is 36.16 (Rockwell C). A sampe of 10 units is randomly selected from a production run consisting of 200 parts and hardness readings taken yielding the following results:
33 34 31 35 32
Determine the Range and estimate how many parts will have a Rc of greater than 40.
Solution:
R = 39 - 31 = 8
_
X = (33 + 34 + 31 + 35 + 32) / 5 = 33Since 2 standard deviations to the left AND right of the mean = 95.46 % of the area under the normal curve,
two standard deviations to the right only = 95.465 / 2 = 47.73 % + 50 % = 97.73 % of the total area. Therefore, the percent of parts lying to the right
of + 2 standard deviations = 100 - 97.73 = 2.27 %
Thus 200 x .0227 = 4.54 -> 5 parts will likely have hardness numbers greater than 36.16 Rc.
STATISTICAL PROCESS CONTROL
One of the major tools of SPC is the control chart. We have just looked a the normal distribution, and this has the basis for the standard control chart
used in SPC. Imagine rotating the normal distribution 90 degrees and plotting data about a line representing the mean. By identifying a limit above
and below the mean, referred to as the upper and lower control limits, a graphical trend can be generated.
Trending is very helpful in determining if something has changed to cause excessive variation that needs to be brought "back in control". There is a
catch 22 here though. How does one know if the trend was common cause variation or special cause variation? Well the answer is you don't.
Sometimes adjusts are made on machine settings responding to common cause variation when, in fact, the system should be left alone. This is called
tampering with the system, and only ultimately leads to the process only getting more out of control. It is "kinda" like trying to give directions to a
moving reference....like turn right at the dog standing beside the stop sign...sometimes its there, sometimes it isn't..The basic purpose of the control chart is to determine whether the quality characteristic being monitored is within the acceptable limits of "natural
variation" and whether it is "in control". Control charts are time series charts that plot historical data. Often the data is misused to forecast without
considering other factors influencing the process. Two of the most common charts are the X-Bar and R charts.
In general, the X-Bar indicates the typical measurements (the average), and the R chart indicates the variability by plotting the range. When a
process in "in- control", variation will still occur and, the degree of variability will be random and limited in magnitude. HOWEVER, if the changes in
X-BAR and R have excessive changes, then it is implied that there is an assignable cause or a special reason why this change occurred. The control
charts help identify when this occurs.
By plotting and monitoring variable believed to be cause-and-effect variables, indications of when "true" adjustments are needed can be established.
It should be noted that SPC is a valuable too, however, an established history must be in place before cause and effect is determined. A control chart
has to have limits that define the acceptable maximum deviations. These are the CONTROL limits. These limits are established using historical
data averaged over time. The average of the average is referred to the GRAND MEAN. The following example problem will show how control
limits are determined.Example Problem: The hardness specification for a drive shaft is Rc = 34 +/- 4. Determine the control limits based on the Rc data taken from the
following process runs:SAMPLE
_ _ =
RUN X1 X2 X3 X4 X (X - X)21 36 35 33 34 35.5 .64
2 37 31 31 35 33.5 .04
3 34 37 36 31 34.5 .64
4 32 34 35 33 33.5 .04
5 33 32 33 32 32.5 1.44
SUM: 168.5 2.80
GRAND MEAN: 33.7
SIGMA .8366Process Capability Analysis
Process capability means whether or not a process can meet specifications. In other words, a process is capable if it can consistently produce parts
within the specified limits. To overall goal is to make sure the system is "inside" the specification limits required.
The degree to which the control limits are located within the specification limits is referred to as the Process Capability (Cp) and is indicated by Cp
index. This value is found by using the following formula:Cp = USL - LSL
------------
6 sigmaThe Cp value should be greater than one, otherwise too large of a percentage of bad parts will be produced. Ratios greater than 1.33 are generally
considered acceptable. Manufacturers use the Cp ratio of their suppliers to evaluate the capability of the vendors to conform to the manufacturer's
specifications.Example problem:
Determine the process capability index for the previous problem with an Rc specification of 34 +/- 4.
Cp = USL - LSL 38 - 30
--------------- = ------------ = 1.59
6 Sigma 6 (.8366)DOE
A step beyond SPC is Design of Experiments (DOE). The real purpose of DOE is to establish the interrelated cause and effect relationship of critical
variables. DOE is a series of statistically based techniques to organize experimentation methods and gather the maximum amount of information with
the minimum amount of resources. Some of DOE methods employ screening experiments referred to as 2k Factorial Experiments. The "2"
represents the levels or settings for the variables under study and the "k" represents the number of factors being considered. These methods are
attractive because small samples are needed to evaluate the cause and effect relationship AT SPECIFIC levels. The draw back to 2k experiments is
that conclusions can ONLY be drawn at the settings or levels of the experiment, no inference can be made with regard to the change or rate of change
between settings. While this topic goes well beyond the goals of our class, an example will be used below to introduce DOE using a 22 Factorial.Example:
The effects of processing temperature, and percent of reinforcing fiber content on tensile strength for composite material are studied. There are
two levels of temperature (200 and 300 degrees C...lableled - and +). Similarly there are two levels of fiber content as a reinforcing material (10%
and 20% also labeled as - and +). Tensile strength is the response variable measured in pounds . Note since this is a 22 experiment, 4 runs are
needed (one for each level/setting).RUN TEMPERATURE [X1] % Fiber[X2] X1Y1 RESPONSE (lbs)[Y]
(x 100)1 - - + 55.0
2 + - - 60.6
3 - + - 64.2
4 + + + 68.22.4 4.2 -0.4
Interpretation: The plot shows the estimated main effects (fiber content and temperature). The temperature main effect is 2.4 which means that on
the average, an increase in temperature of 50 degrees yields an average increase of 2.4 percent increase in tensile strength (note only temperature is
being considered here fiber content is not). Stating this another way, a temperature increase from the low level setting of 200 degrees C to the high
setting of 300 degrees C leads to a (2 x 2.4) 4.8 percent increase in tensile strength. Similarly, increasing the fiber content from 10 % to 20 % on the
average will yield an 8.4 percent increase in yield strength (ignoring the effect of processing temperature). The interaction is quite low and can be
indicated by the degree to which the lines are parallel on the graphical plot.Overall interpretation: Tensile strength can be increased by increasing temperature and fiber content. Since the fiber content effect is (4.2/2.4 = 1.75
times) greater than the temperature effect, the experiment suggests that the effect of fiber content = 1.75 times the effect of processing temperature
at the settings observed.This example is intended to only show how a DOE can be set up and should not be used as a guide for actual experimentation. It should be noted that
in an actual 2k factorial designs in DOE, individual observations are used to calculate standard errors of the estimated effects to test for statistical
significance. This is beyond the intended scope of this module.
SUMMARY
The term quality ultimately means customer satisfaction or fit for use. Quality control involves detection of defects after the fact, where as Quality
assurance seeks to prevent the occurrence of defective products. Graphical and statistical methods are used to maintain quality and pursue
continuous improvement. Two types of inspection can be carried out. Attribute inspection in which pass or fail, go or no-go, good or bad type
decisions are made. Variable inspection allows for specific levels of measurement to be taken. Descriptive statistics can be used to determine how
much variations exist for a given variable or variables. The location of data about the mean can be compared to probability distributions such as the
NORMAL distribution. SPC is usually based on the properties of the normal distribution. Time series trends can be developed for an process to
determine changes over time. Control limits on the SPC chart provide bounds for keeping the process stable. These control limits should be
centered inside the specification limits. If this is the case, the process is capable of meeting the required specifications. A Cp ration can be
calculated to determine if the process is capable. A step beyond SPC is DOE. Design of experiments seeks to improve a process by studying critical
variables with minimum resources. Two level factorial designs are often used as screening techniques to determine if changes in a variable or
variables will produce a desired response.Problems
1. Calculate the mean and standard deviation for the following recorded micrometer reading :
.252 , .255 , .251 , .248 , .253 , .249 , .252 , .247 , .249 .251
Assuming variation in instrumentation can be eliminated, what can be intrepreted from this data?2. The inside diameter of a cylinder is 1.875 inches. If the standard deviation of the diameter is 0.0005, and a
total of 100 cylinders are to be produced, estimate how many cylinders will have an inside diameter of less
than 1.8745 inches. What recommendations would you offer to improve the quality process based on your findings?3. Using EXCEL, Develop a spreadsheet to calculate AND graph X-Bar and R charts for the data shown below:
Create 2 different charts based on two different assumptions:
Assumption 1: 10 samples taken from 4 different runs;
Assumption 2: 4 samples taken from 10 different runs.Sample Run 1 Run 2 Run 3 Run 4
1 22 22.5 22.5 24
2 20.5 22.5 22.5 23
3 20 20.5 23 22
4 21 22 22 23
5 22.5 19.5 22.5 22
6 23 23.5 21 22
7 19 22 22 20.5
8 21.5 20.5 19 19.5
9 21.5 22.5 20 22
10 21 23 22 23Analyze the data and compare the "quality" of the products. Have they changed? What has?
4. If the tolerance on the part in problem 3 is 21.00 +/_ 2.00 , find the process capability ratio and explain whether or not
the process is capable of producing good parts. Compare across the two different assumptions.5. An experiment is has been conducted to determine the effect of type of tires and type of transmission on
fuel economy for a light weight sport utility vehicle. The variables are coded as follows:Tire type: - standard
+ steel belted radialTransmission type: - manual
+ automaticPlot the data for the 2 factor DOE shown below and interpret the results.
RUN Tire Type Transmission Type MPG
X1 X2 X1X2 RESPONSE
1 - - + 24
2 + - - 25
3 - + - 18
4 + + + 20
SEPT 23
VARIATION ANAYLYSIS
SPC:
Review of in class problem from 9-16Control charts and variation analysis
X Bar and R charts: effects on sample size
S Charts
Dealing with "Out of Conrol" Data"
"Recalibarting" the Control Chart.
An Applied SPC problem for processing polyethylene film.
(see message board for assignment)