1987.07 Spring 1987

SOUTHERN METHODIST UNII Statistical Quality Control Software: QSCA]J Analysis

David S. Savage

AL QUALITY CONTROL SOFTWARE:

QSCAN ANALYSIS

by David S. Savage Prepared for:

Dr. Richard Barr OREM 4390

Senior Design

DEPARTMENT OF OPERATIONS RESEARCH AND ENGINEERING MANAGEMENT

SCHOOL OF ENGINEERING AND APPLIED SCIENCE

DALLAS, TEXAS 75275

I I

STATISTICAL QUALITY CONTROL SOFTWARE:

QSCAN ANALYSIS

by David S. Savage

Prepared for: Dr. Richard Barr

OREM 4390 Senior Design

This report examines the proliferation of statistical quality control software in the manufacturing industry. It focuses on one type of software, QScan Statistical Process Control.

May 8, 1987

TABLE OF CONTENTS

I. Summary ........................................1

II. Backgrounds and Descri ptions ....................2

A. Introduction ................................2

B. Definition of Quality .......................3

C. Design vs. Manufactured Quality .............4

D. Statistical Quality Control .................6

E. Process Control Charts ......................7

F. Industrial Process Control Software ..........9

III. Analysis of QScan ..............................11

A. Introduction ................................12

B. Analysis Mode ...............................12

C. Presentation Mode ...........................14

IV. Data Implementation Output ......................15

V.

Conclusions .....................................17

Diaqrams and Charts ..........................19-31

II I

I. SUMMARY

Process Control Software is revolutionizing the

Quality Control function of industry. Its effect on the

qualityand productivity of products and services in

today's modern industrial atmos phere cannot be underesti-

mated. Understanding how to apply the software to a

manufacturers needs is the point of this report. Sample

data was used to illustrate how QScan Statistical Process

Control Software can enhance the quality of any manufac-

turing process.

'The most important aspect of QScan is the ease and

applicability with which it can be applied and the flexi-

bility it offers large industries with many product lines.

Any manufacturing firm, large or small, can benefit from

the use of QScan or any other statistical process control

software, but QScan offers much more.

QScan opens the quqlity process to all levels in a

manufacturing organization, and promotes-the exchange of

information and ideas for quality and productivity improve-

ment. Managers qet direct access to meaningul information,

and their reports are enhanced by high-resolution graphics.

Line supervisors are able to perform immediate spot checks,

auickly entering new data and analyzing the results for

process status. Quality engineers can monitor and control

U manufacturing processes, design sampling plans, and determine

process capability.

I I

II. BACKGROUND AND DESCRIPTIONS

A. Introduction

Quality control is a term that has received consi-

derable attention in the past few decades. The rise of

Japan into the secont most powerful nation in the free

world may account for this interest because of Japan's

success at beating foreign competitors in all areas of

quality and thus increasing the performance of their pro-

ducts and services. After WWII Japan faced the ominous

I test of rebuilding all of its industry from ruin. With the U.S.'s help, new factories and methods of production

were established and the beginnings of a new approach at

producing quality goods came about. One of the world's

I leading international quality consultants, Dr. W. Edwards

I .Deming, went to Japan in the post-WWII period to help them establish industries that relied on statistical quality

control. With his help, the Japanese created a method of

assuring quality in their products that even the U.S. en-

vied until it realized that Japan had "stolen" hundreds of

millions of dollars in foreign trade. It took this reali-

zation to move American industry into action and begin to

strive for quality.

Other factors affecting modern manufacturing and ser-

vice industries are increased customer quality requirements

1 2

I

Ii I I

and the development of new product technology. Part of

the new demand for higher quality products stems from Japan

Iand other foreign countries who have offered better pro-

ducts for Americans to buy, some at lower prices. The

I Japanese invasion into the American automobile industry is

I

a qood example. During the early 1970's, Toyota, Honda,

and other Japanese automobile companies introduced smaller

Iand cheaper cars into the American market. The most stri-

king feature of these cars, however, was their higher qua-

-I lity compared to American cars. The American automobile

I industry was not only forced to introduce the new "compact"

cars but also re-evaluate the quality standards they en-

forced. Japan's quality control methods played a large

part in the success of their automobiles.

I New technology in most industries has made it possible

manufacture products that provide more functions and

I

to

higher performance levels. This is another reason quality

Icontrol has become a major new functional area of all com-

panies that produce qoods and services. Products that are

more sensitive and operate at higher levels of performance

than ever before require more vigorous quality standards I and assurance.

B. Definition of Quality

I Products must meet the requirements of those who use

1 3

I U

them. Therefore, a general definition of quality is

"fitness for use." This definition is attributed to ano-

ther noted international quality consultant who worked with

Deming in Japan, Dr. Joseph M. Juran. It is especially

useful because it places emphasis on the consumer aspect

of quality. A more widely used definition of quality is

"conformance to requirements or specifications." Phil

Crosby has suggested that this definition is necessary be-

cause in order to manage quality adequately we must be able

to measure it.

Both of these definitions provide useful insights into

the nature of quality and combining them emphasizes that re-

quirements and specifications translate fitness for use into

measurable quantities. It is important to realize that qua-

lity doesn't necessarily mean high quality, it means unifor-

mity, consistency, and conformity to a standard or specifi-

cation. It is a statement of what the user, or consumer,

wants and can afford and what the producer can-provide.

Consequently, the producer and user must cooperate in defi-

ning a practical, reasonable, economical specification of

quality.

C. Design vs. Manufactured Quality

Manufacturers have always complained, "Quality costs

4I

I I

too much!" They would like to be able to compete with

higher quality manufacturers and producers but cannot jus-

tify the high expenditures this would require. The main

problem, however, is that they are failing to make the dis-

tinction between the two different aspects of quality -

"design quality" and "manufactured quality". This distin-

ction is quite important because, with a correct understan-

ding of these terms, it can be realized that good quality

and low cost can be achieved simultaneously.

I Design quality is usually what the confused manufac-

turers are referring to when they complain of high costs.

This quality of design, or product qrade, is a real cost.

When deciding what will appeal to potential customers, sup-

pliers of a new product or service must decide what it will

I cost them to produce the product or offer the service and

I what the consumers will be willing to pay for the product or service. Consequently, design quality must be considered

Icarefully in planning design, manufacture, and marketing

of new products or services.

I But design quality is not the only aspect of quality.

I

After design and manufacture, producers find that the manu-facturing process does not always produce each unit of pro-

duct in conformity to the design. Defects in materials,

parts, assemblies, and in the final product tend to arise. I 5

I

I I

When these defects are not related to design, they are the

result of incomplete, inadequate, or poorly controlled manu-

facturing processes. These products result in customer dis-

satisfaction and any defective or nonconforming materials,

parts, and finished products that must be discarded or re-

worked during manufacture result in increased cost. Manu-

factured quality is indeed an important aspect of quality

and can be called the quality of conformance to the design.

Higher design quality usually means higher cost, but higher

manufactured quality usually means lower cost.

D. Statistical Quality Control

Quality control is concerned with minimizing deviations

from manufactured quality. Juran's definition of quality

control is as follows: "Quality control is the regulatory

process through which we measure actual quality performance,

compare it with standards, and act on the difference."

Measurement includes all processes a manufacturer uses to

compare his product to a particular requirement or speci-

fication. These standards are determined by management as

design quality. "Acting on the difference" refers to the

assignment of causes of deviation in the manufacturing

process and correcting them.

6

jThe emphasis on the staistical aspects of quality -:

control motivated Deming to put forth the following defi-

nition: "The Statistical Control of Quality is application

of statistical principles and techniques in all stages of

design, production, maintenance and service, directed toward

the economic 'satisfaction of demand'." Statistical quality

control is most important because it is the only way to

significantly improve industrial quality and productivity

while making substantial reductions in the costs of quality.

These quality costs have become much larqer for companies

usinq existing quality-assurance practices that don't in-

clude statistical analysis.

E. Process Control Charts

As mentioned previously, manufactured quality pertains

to how well a product conforms to its desitn. All produc-

tion processes contain a certain amount of inherent or

natural variability that cannot be avoided. This natural

variability or "background noise" is the cumulative effect

of many small, uncontrollable causes. When this variability

is relatively small, it is usually considered to be an

acceptable level of process performance. Statistical

quality control allows for this backqround noise and it

is often called a "stable system of chance causes." A

1:1

II

manufacturing process that is operating with only chance

causes of variation is said to be "in statisctical control."

Unfortunately, other kinds of variability occasion-

ally present themselves in the output of a process. This

variability in key quality characteristics usually arises

from three main sources: improperly adjusted machines,

operator errors, and defective raw materials. Such varia-

bility is generally larger than chance background noise,

and usually represents an unacceptable level of quality

performance. These sources of variability that are not

part of the chance deviations of design are called assign-

able causes. Any process that is operating in the presence

of assignable causes is said to be "out-of-control."

Usually, production processes o perate in the in-con-

trol state for relatively long periods of time producing

acceptable products that conform to specifications. Assign-

able causes,-..however, occur at random, resulting in a

change to the out-of-control state where a larger propor-

tion of the process output does not conform to design spe-

cifications. The major objective of statistical quality

control is to detect this occurrence of assignable causes

and the resulting out-of-control state so that corrective

action may be undertaken and a return to-proper control can

8

II

be established.

Control charts represent the major tool for manufac-

turers to use in detecting out-of-control processes on-

line. They may also provide information useful in impro-

ving the process and thus improving product quality. Con-

trol charts use a center line that represents the averaqe

value of a ouality characteristic in the in-control state.

Two other horizontal lines, called the upper control limit

(UCL) and the lower control limit (LCL), are also shown

on the chart. These control limits are determined using

basic statistical techniques and give a definite area of

process control. Points that fall outside - the limits sug-

gest that the process may be out-of-control and should be

investigated.

F. Industrial Process Control Software

Industrial environments present a unique set of per-

formance and reliability requirements for industrial pro-

cess control software. Manufacturing systems can vary

from small job shops with manual data collection to larqe

continuous processes with automatic data collection invol-

ving micro, mini, and mainframe computers. Process control

software must accomodate these larqe manufacturers with

easily accessible data and flexible applications for dif -

I

9

ferent types of analysis.

In qeneral, statistical process control systems have

these requirements:

- Orqanizational Support

- Data Collection

- Data Manaqement

- Data Reduction

- Data Presentation

- Applications Development

Industrial Process control involves a variety of orqa-

nizational units with different styles and requirements.

Many different product lines, each with its own needs, may

use the process control software and require their own

independent applications.

Data collection is perhaps the most important require-

ment for it is the basis of quality control. It must be

flexible so as to accomodate different types of data input.

The software must support manual and automatic data collec-

tion as well as entry from automatic data ac quisition hard-

ware such as testing and sensing equipment within the manu-

facturing process. An interface with data base manaqement

systems is also required for broad perspectives of parti-

cular quality characteristics.

Data management requires the handling of large volumes

10

of files of various types because of the many different

quality characteristics that can be measured. Updating

frequency requirements for the different characteristics

may vary and must be completely flexible. Users need access

to all of the data in order to update, review, and create

multiple concurrent files. The software must support these

files containing descriptive as well as quantitative infor-

mation.

• Data reduction that is fast, powerful, and flexible

is required for effective statistical analysis. Large

manufacturing processes may su pply the user with huge loads

of data that could not possibly be handled manually.

Data presentation requires a comprehensive set of con-

trol charts that can be customized and standardized to pro-

duce regular process control reports for manaqement. And

applications development must be reliable for critical and

important industrial applications. Also, software compati-

bility, portability, and expandability provide a manufacturer

with an added deqree of freedom.

III. ANALYSIS OF QSCAN

A. Introduction

QScan is state-of-the-art statistical process control

11

software. It combines several new and unique features

that facilitate easy and quick quality analysis:

- Statscope: for viewing, editing and analyzing a

process.

- fjhartboard: for comparing views of one or more

processes.

- Slideshow: for presentations and reports.

These features will be discusses in more detail later.

QScan is operated with the aid of integrated functions:

- Analysis Mode : to enter, edit and anlyze process

control data, charts, and statistics.

- Presentation Mode: to produce Slideshows for reports

and presentations.

B. Analysis Mode

Analysis Mode is the cornerstone of QScan. The pri-

mary tool in Analysis Mode is Process Control Analysis:

a complete set of control charts and statistics for moni-

toring industrial processea &nd analyzing process capabi-

lity. It offers both analytical and presentationcontrol

charts and diagrams for determining quality and productivity.

Statscope displays analytical control charts, and Chart-

board creates presentation control charts, that can be saved

as Slides for Slideshow presentations and reports.

12

I I

Process Control Analysis provides the user with an

easy way to monitor any industrial process. There are

three distinct phases to recording and analyzing process

control data:

1) Defining Control Charts (Setup) - After a quality characteristic has been selected and a method for measurement has been determined, the parameters of the control chart can be set. These parameters are a function of the variability of the process. The center line and control limits represent in-control processes. The objective is to find out and eliminate assignable causes that may produce out-of-control conditions.

2) Monitoring the Process - Once the process is stable and the control limits defined, new samples are taken to confirm that the process remains in control. Every sample represents a new point on the charts. Control limits remain the same and the new samples are compared with the extablished control limits. QScan automatically evaluates and plots new points, and Warning Rules indicate when a particular quality characteristic is out-of-control.

3) Updating Control Charts - When a problem is detected, the manufacturing process should be studied, the problem identified, and the process corrected. After corrective action, new control limits must be established, and the process is monitored as before.

Statscope provides complete command over process

control charts, and includes an intelligent control chart

Editor that makes data entry and updating quick and easy.

Many different statistics and samples can be viewed and

monitored.

Chartboard displays different viewsbf the same data

file, and the same view of different files. Control

13

III charts can rapidly be scanned and compared with other data

files representing lines of control such as products,

Iassembly lines, or plants. For example, Statscope may

determine that a problem exists with the variability of I a process. It can analyze the specific samples during

I

that time frame, and Chartboard can then accomodate scanning

through several different control charts and diagrams for

Ithese particular samples. This allows manufacturers to

quickly determine the actual cause of the problem and take

corrective action.

C. Presentation Mode

IThe Presentation Mode in QScan provides users with an

ideal way of creating process control presentations. Slides

Ithat have been from the Chartboard function in the saved

I

Analysis Mode can be individually displayed, edited and

pointed, or collected together and organized into Slideshows.

ISlideshows can be arranged in the user's preferred fashion.

Slides are collected and or qanizedin Slideshows as

I"trays." They can be moved around an organized so as to

present a certain point that a system analyst may want to

convey. In this way, the Presentation Mode turns a QScan

workstation into a sort of slide projector. This is quite

useful for process control analysts giving reports, demon-

strations, or presentations.

1 14

IV. DATA IMPLEMENTATION AND OUTPUT

The data used in the analysis was received in Lotus

form. Two different kinds of processes provided the data

to analyze with QScan. The first process involves refining

a type of resin in a chemical reaction. Four different

data groups, the percentage of volatile resin content,

the percentage of resin solids, the percentage of resin

flow at 100 psi, and the quantity of prepreqnated gel at

3200 F gave statistics that were grouped in samples of 20.

The second process involves manufacturing side wall

panels in the interior shop. Defects in these panels were

sight identified and the rework time is also given.

Because the data was in Lotus form, it was required to

format the data into an acceptable im porting form for QScan.

The following page shows the specified format for importing

data into QScan.

The analysis of the percentage of volatile resin will

be oresented in this paper as an example of QScan capabilities.

The first table presents the appropriate data file, %Vol.Pcd,

but only the first sample of 25. The only required aspects

of the file are the [Type] and [Sample] commands. The data

itself may be listed horizontally or vertically.

After the data file has been loaded onto QScan, the

Parameter Specification Pa ge lists pertinent specifications

15

II

and parameters such as the sigma multiple (defaulted to

3.0), the Geometric Moving Avera qe Weight (defaulted to

0.2), and Cumulative Sum parameters. This page also

displays the Status of the particular process (out-of-

control for % volatile content), or a histogram, and

basic control charts.

A sample of Statscope is also included. For %Vol.Pcd,

this example shows sample #7, its number of observations

(20) and a histogram of its values. X-bar, X-min, and

X-max are given, as is the range (R). Statscope is useful

because it can move quickly from sample to sample in order

to compare and analyze different samples over time.

Next, 7 different control charts from Chartboard are

presented. Process Status (a histogram of the entire file,

aiving the number of observations with control limits), a

Ranges control chart (showing the ranges of individual sam-

ples), a Variability control chart (showing the standard

deviations of samples), a Cumulative Sums of X-bar chart

(showing the control mean of samples based on the cumulative

sum of deviations of the sample means), a Geometric Moving

Average of X-bar chart (showing the mean of samples based

on the qeometric moving average of the sample means), and

an X-bar chart itself are included next. Also, the Process

Status charts for the other 4 processes analyzed are inclu-

16

ded. Another beneficial aspect of QScan is that X-bar and

R charts may be shown on the same screen for better percep-

tion of the process. This is shown for the percentaqe of

Resin Solids data.

V. CONCLUSIONS

QScan statistical quality control software offers manu-

facturers a complete monitoring process of all production

functions. Its most beneficial characteristic is that

while it can accomodate the most demanding quality control

requriements, anyone in the manufacturing or qanization can

use QScan's results and a pply its answers to increase pro-

ductivity.

In any manufacturing process, quality has become an

important business strateqy. Higher demands on quality and

increased technology have caused all producers to re-evaluate

their production techni ques. One technique that has estab-

lished itself as a required function for manufacturing is

statistical process control software. Today's modern in-

dustrial atmosphere makes this software essential for larqe

industries with huge product lines or production techniques.

QScan offers state-of-the-art process control and serves

manufacturers in promoting the exchange of information and

ideas for quality and productivity improvement.

17

If time had permitted, a more thorough study of

different aspects of QScan not covered here would have

been interesting. Economic Modeling and Analysis in

QScan can provide a general strateqy for formulating mo-

dels describing various problem operational activities

and their associated costs. Management can then see how

different solutions will affect profits. QScan can also

provide interesting analysis of multivariate process

control, nonconformities Process control (U-charts, C-

charts, and pareto dia grams), and nonconforming process

control (P-charts and na-charts.)

18

19

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Averages and Uariability V. RESIN SOLIDS

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31