TOOLS AND

TECHNIQUES

The Seven QC Tools

11
The Seven QC Tools are simple graphical methods of visualizing systems, data, or relation-
ships in order to facilitate problem solving and improvement efforts. They are easy to learn
and are especially useful in team problem-solving activities because they facilitate communi-
cation among the members.

FLOWCHARTS
To understand a process, one must first determine how it works and what it is supposed to
do. Flowcharting, or process mapping, identifies the sequence of activities or the flow of
materials and information in a process; it was introduced in Chapter 4 of the text. Flowcharts
help the people who are involved in the process understand it much better and more objec-
tively. Understanding how a process works enables a team to pinpoint obvious problems,
error-proof the process, streamline it by eliminating non-value-added steps, and reduce vari-
ation. Once a flowchart is constructed, it can be used to identify quality problems as well as
areas for productivity improvement. Questions such as “How does this operation affect the
customer?” or “Can we improve or even eliminate this operation?” or “Should we control a
critical quality characteristic at this point?” trigger the identification of opportunities. Figure
T11-1 shows an example of a flowchart.

RUN CHARTS AND CONTROL CHARTS

A run chart is a line graph in which data are plotted over time.The vertical axis represents
a measurement; the horizontal axis is the time scale.The daily newspaper usually has several
examples of run charts, such as the Dow Jones Industrial Average. Run charts show the per-
formance and the variation of a process or some quality or productivity indicator over time.
They can be used to track such things as production volume, costs, and customer satisfaction
indexes. Run charts summarize data in a graphical fashion that is easy to understand and
interpret, identify process changes and trends over time, and show the effects of corrective
actions.
The first step in constructing a run chart is to identify the measurement or indicator to
be monitored. In some situations, one might measure the quality characteristics for each indi-
vidual unit of process output. For low-volume processes, such as chemical production or sur-
geries, this would be appropriate, but for high-volume production processes or services with
large numbers of customers or transactions, it would be impractical. Instead, samples taken on
a periodic basis provide the data for computing basic statistical measures such as the mean,
range, or standard deviation, proportion of items that do not conform to specifications, or
number of nonconformances per unit.

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FIGURE T11-1 | Flowchart of a Quick Service Drive-Through Process

Customers pull up to sign

and decide what they
want to order
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Bell rings inside

Employee says,
”May I help you?“

Customer gives Employee repeats order Customer waits and

order and gives total drives through

Employees Customer and food Employee

process order reach window repeats total

Customer gives Employee gives Customer

money food and change pulls away

Constructing the chart requires the following steps:

Step 1. Collect the data. If samples are chosen, compute the relevant statistic for each
sample, such as the average or proportion.
Step 2. Examine the range of the data. Scale the chart so that all data can be plotted on
the vertical axis. Provide some additional room for new data as they are collected.
Step 3. Plot the points on the chart and connect them. Use graph paper if the chart is
constructed by hand; a spreadsheet program is preferable.
Step 4. Compute the average of all plotted points and draw it as a horizontal line
through the data.This line denoting the average is called the center line (CL) of
the chart.
If the plotted points fluctuate in a stable pattern around the center line, with no large
spikes, trends, or shifts, they indicate that the process is apparently under control. If unusual
patterns exist, then the cause of the lack of stability should be investigated, and corrective
action should be taken.Thus, run charts can identify messes caused by lack of control.
A control chart is simply a run chart to which two horizontal lines, called control limits,
are added: the upper control limit (UCL) and lower control limit (LCL), as illustrated in Figure
T11-2. Control limits are chosen statistically so that there is a high probability (generally
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greater than 0.99) that points will fall between these limits if the process is in control. Control
limits make it easier to interpret patterns in a run chart and draw conclusions about the state
of control.

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FIGURE T11-2 | The Structure of a Control Chart

Measurement

Data points
Upper control limit
UCL

Process Center line

mean

Lower control limit

LCL

Time

If sample values fall outside the control limits or if nonrandom patterns occur in the chart,
then special causes may be affecting the process; the process is not stable.The process should
be examined and corrective action taken as appropriate. If evaluation and correction are done
in real time, then the chance of producing nonconforming product is minimized.Thus, as a
problem-solving tool, control charts allow operators to identify quality problems as they
occur. Of course, control charts alone cannot determine the source of the problem.
Operators, supervisors, and engineers may have to resort to other problem-solving tools to
seek the root cause.Technical details of control charts are described in Tools and Techniques
section 14.

CHECK SHEETS
Check sheets are simple tools for data collection. Nearly any kind of form may be used to
collect data. Data sheets are simple columnar or tabular forms used to record data.To gen-
erate useful information from raw data, however, further processing generally is necessary.
Check sheets are special types of data collection forms in which the results may be interpreted
on the form directly without additional processing. For example, in the check sheet in Figure
T11-3, one can easily identify the most frequent causes of problems.

HISTOGRAMS
A histogram is a basic statistical tool that graphically shows the frequency or number of obser-
vations of a particular value or within a specified group. Histograms provide clues about the
characteristics of the parent population from which a sample is taken. Patterns that would be
difficult to see in an ordinary table of numbers become apparent. Check sheets are often
designed to provide a visual histogram as the data are tallied as shown in the example in
Figure T11-4.
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FIGURE T11-3 | Example of a Check Sheet: Airline Complaints

Problem Week 1 Week 2 Week 3 Week 4 Total

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Lost Baggage 4

Baggage Delay 23

Missed Connection 7

Poor Cabin Service 14

Ticketing Error 2

50

FIGURE T11-4 | Example of a Check Sheet as a Histogram

20
19
18
17
16
15
14
13 X
12 X
11 X X
Frequency 10 X X X
9 X X X
8 X X X X
7 X X X X
6 X X X X
5 X X X X X
4 X X X X X X
3 X X X X X X X
2 X X X X X X X
1 X X X X X X X X X X

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20

Time to Process Loan Request (days)

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PARETO ANALYSIS
The Pareto principle was observed by Joseph Juran in 1950. Juran found that most quality prob-
lems resulted from only a few causes. For instance, in an analysis of 200 types of field failures
of automotive engines, 5 accounted for one-third of all failures; the top 25 accounted for two-

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thirds of the failures. Juran named this technique after Vilfredo Pareto (1848–1923), an Italian
economist who determined that 85 percent of the wealth in Milan was owned by only 15
percent of the people. Pareto analysis separates the vital few from the trivial many and pro-
vides direction for selecting projects for improvement. For example, the check sheet in Figure
T11-3 provided the data for the Pareto diagram shown in Figure T11-5, which shows that
baggage delay and poor cabin service account for 74 percent of all problems.

FIGURE T11-5 | Example of a Pareto Diagram

100

Cumulative percent

Frequency Percent
23 50

14

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CAUSE-AND-EFFECT DIAGRAMS
The cause-and-effect diagram is a simple, graphical method for presenting a chain of causes
and effects and for sorting out causes and organizing relationships between variables. Because
of its structure, it is often called a fishbone diagram. An example of a cause-and-effect dia-
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gram is shown in Figure T11-6. At the end of the horizontal line, a problem is listed. Each
branch pointing into the main stem represents a possible cause. Branches pointing to the
causes are contributors to those causes. The diagram identifies the most likely causes of a
problem so that further data collection and analysis can be carried out.

FIGURE T11-6 | Example of a Cause-and-Effect Diagram

Client Time Rush request

Unclear Poor
directions handwriting
Overload

Word
processing
errors

Inattention
No spell check

Did not
understand
directions Training
Typist

SCATTER DIAGRAMS
Scatter diagrams are the graphical component of regression analysis. Although they do not
provide rigorous statistical analysis, they often point to important relationships between vari-
ables, such as the percentage of an ingredient in an alloy and the hardness of the alloy or the
number of employee errors and overtime worked (Figure T11-7). Typically, the variables in
question represent possible causes and effects obtained from cause-and-effect diagrams. For
example, if a manufacturer suspects that the percentage of an ingredient in an alloy is causing
quality problems in meeting hardness specifications, an employee group might collect data
from samples on the amount of the ingredient and hardness and plot the data on a scatter dia-
gram, which might indicate that lower quantities of the ingredient in the alloy are associated
with increased quality problems.
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FIGURE T11-7 | Example of a Scatter Diagram

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Number
of Errors

Volume of Overtime Work

Problems and Exercises

1. Discuss what would be the most appropriate tool to use to attack each of these quality
issues.
a. A copy machine suffers frequent paper jams, and users are often confused as to how
to fix the problem.
b. The publication team for an engineering department wants to improve the accu-
racy of its user documentation but doesn’t know why documents aren’t error-free.
c. An office manager has experienced numerous problems with a laser printer:
double-spaced lines, garbled text, lost text, and blank pages. She is trying to figure
out which is the most significant problem.
d. A military agency wants to evaluate the weight of personnel at a certain facility.
e. A contracting agency wants to investigate why it has had so many changes in its
contracts. The agency believes that the number of changes may be related to the
dollar value of the original contract or the days between the request for proposal
and the contract award.
f. A travel agency is interested in how call volume varies by time of year so that it can
adjust staffing schedules.
2. A catalog order-filling process for personalized printed products can be described as fol-
lows:1 Telephone orders are taken over a 12-hour period each day. Orders are collected
from each person at the end of the day and checked for errors by the supervisor of the
phone department, usually the following morning. The supervisor does not send each
one-day batch of orders to the data processing department until after 1:00 p.m. In the
next step—data processing—orders are invoiced in the one-day batches. Then they are
printed and matched back to the original orders.At this point, if the order is from a new
customer, it is sent to the person who did the customer verification and setup of new
customer accounts.This process must to be completed before the order can be invoiced.
The next step—order verification and proofreading—occurs after invoicing is com-
pleted. The orders, with invoices attached, are given to a person who verifies that all
required information is present and correct before typesetting. If the verifier has any
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questions, they are checked by computer or by calling the customer. Finally, the com-
pleted orders are sent to the typesetting department of the printshop.
a. Develop a flowchart for this process.
b. Discuss opportunities for improving the quality of service in this situation.
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3. An independent outplacement service helps unemployed executives find jobs. One of the
major activities of the service is preparing résumés. Three word processors work at the
service typing résumés and cover letters.They are assigned to individual clients, currently
about 120.Turnaround time for typing is expected to be 24 hours.The word-processing
operation begins with clients placing work in the assigned word processor’s bin. When
the word processor picks up the work (in batches), it is logged in using a time clock
stamp, and the work is typed and printed.After the batch is completed, the word proces-
sor returns the documents to the clients’ bins, logs in the time delivered, and picks up
new work. A supervisor tries to balance the workload for the three word processors.
Lately, many clients have been complaining about errors in their documents—mis-
spellings, missing lines, wrong formatting, and so on. The supervisor has told the word
processors to be more careful, but the errors persist.
a. Develop a cause-and-effect diagram that might clarify the source of errors.
b. What tools might the supervisor use to study ways to reduce the amount of errors?
4. Develop cause-and-effect diagrams for the following problems:
a. poor exam grade
b. no job offers
c. late for work or school
5. Ace Printing Company realized that it was losing customers and orders due to various
delays and errors.To get to the root cause of the problem,Ace decided to track problems
that might be contributing to customer dissatisfaction. Below is a list of the problems that
it found and their frequencies of occurrence over a six-month period. What technique
might you use to graphically show the causes of customer dissatisfaction? What recom-
mendations could you make to reduce errors and increase customer satisfaction?

Error/Delay Cause Frequency

Delays from customer changes 15
Lack of press time 178
Design department delays 76
Paper not in stock 85
Lack of proper order information 32
Lost orders 9
Press setup delays 205

6. The number of defects found in 25 samples of 100 machine screws taken on a daily basis
from a production line over a five-week period is given below. Plot these data on a run
chart, computing the average value (center line), but ignoring the control limits. Do you
suspect that any special causes are present? Why?

0 5 4 4 3 1 0 0 3 6
0 1 1 7 6 6 15 12 6 3
3 2 2 4 6
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End Note
1. Adapted from Ronald G. Conant, “JIT in a Mail Order Operation Reduces Processing Time from Four Days to
Four Hours,” Industrial Engineering, 20, no. 9 (September 1988): 34–37.

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