The document discusses quality management system construction for the construction industry. It provides an overview of key aspects of quality management system construction including forms, tools, and strategies. It also lists additional useful resources for quality management system construction such as free ebooks, forms, templates, and interview questions. The document then discusses the contents of quality management system construction for the construction industry including the goals of ensuring projects are completed on time, on budget and to a high quality. It also discusses some of the challenges the construction industry faces in assuring construction quality.

1. quality management system construction
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I. Contents of quality management system construction
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The main goal of construction industry is to ensure that construction projects are successfully
completed within the constraints of best quality, stated period and at minimum cost possible. The
main aim of this research is to review the potential of integratingthe quality management system
within the context of construction management. The methodologies adapted for this study
areinterviews with construction key personnel. The importance of the interviews will help to
justify the potential of integratingwithin the context of construction management. The main
obstacles that have been identified is the level of understanding of personnel about the full
content of the quality management system itself. It is found that, in ensuring the successful
objectives of company, the implementation of quality management system in construction
industry will assist the industry to improve theefficiency and effectiveness of the organization
management system.
The construction industry is being viewed as one with poor quality emphasis compared to other
sectors likethe manufacturing and service sectors (Wan Yusoff, et al., 2006; Kubal, 1994; Kanji
and Wong, 1998;Wong and Fung, 1999). Because of the poor workmanship of the end product, a
lot of criticisms have beendirected to construction industry. Furthermore, the processes, people,
materials are also under pressure forbetter quality in construction.
Construction industry facing problems to assure the construction quality because of the nature of
operationis complicated (Wan Yusoff, et al., 2006; Kanji and Wong, 1998). It is because, the
construction industryconsists of a multitude of occupations professions and organizations (Wan
Yusoff, et al., 2006;Sommerville, 1994). They are involved in different phases of construction
and each one play a differentrole in delivering a quality project. Failure of any of the parties will
affect the quality of the final project(Wan Yusoff, et al., 2006; Kanji and Wong, 1998)
Quality management system (QMS) is defined as “all activities of the overall management
function that determine the quality policy, objectives and responsibilities, and implement them

2. by means such as quality planning, quality control, quality assurance and quality improvement
within the quality system” (Abdul Hakim and Mat Naim, 2006; MS ISO 8402, 1994). The
general names for quality systems such as TotalQuality Management (TQM) and the famous ISO
9000 quality standards.
According to AbdulAziz A.B and Tawfiq H.A (1999), quality systems involve internal and
externalaspects. An internal quality system covers activities aimed at providing confidence to the
management of an organization that the intended quality is being achieved. This is called a
“quality management system”. Successful implementation of quality management system can
contribute to an increase in product quality,improvement in workmanship and efficiency, a
decrease in wastage, and increase profit. Meanwhile, an external quality system covers activities
aimed at inspiring confidence in the client that the supplier’s quality system will provide a
product or service that will satisfy the client’s quality requirements. This iscalled a “quality
assurance system”.
ISO 9000 deals with the fundamentals of quality management systems (Quality Standard, 2008;
Tsim
et al ,2002), including the eight management principles (Quality Standard, 2008; Beattie and
Sohal,1999; Tsimet al , 2002) on which the family of standards is based. ISO 9001 deals with the
requirementsthat organization wishing to meet the standard they have to fulfill. In order to
integrate the qualitymanagement system within the context of construction management, the
need to study the elements instandard guidelines of quality management system is essential to
ensure the standardization of the qualitymanagement system is successful.
==================
III. Quality management tools
1. Check sheet
The check sheet is a form (document) used to collect data
in real time at the location where the data is generated.
The data it captures can be quantitative or qualitative.
When the information is quantitative, the check sheet is
sometimes called a tally sheet.
The defining characteristic of a check sheet is that data
are recorded by making marks ("checks") on it. A typical
check sheet is divided into regions, and marks made in
different regions have different significance. Data are
read by observing the location and number of marks on
the sheet.
Check sheets typically employ a heading that answers the
Five Ws:
 Who filled out the check sheet

3.  What was collected (what each check represents,
an identifying batch or lot number)
 Where the collection took place (facility, room,
apparatus)
 When the collection took place (hour, shift, day
of the week)
 Why the data were collected
2. Control chart
Control charts, also known as Shewhart charts
(after Walter A. Shewhart) or process-behavior
charts, in statistical process control are tools used
to determine if a manufacturing or business
process is in a state of statistical control.
If analysis of the control chart indicates that the
process is currently under control (i.e., is stable,
with variation only coming from sources common
to the process), then no corrections or changes to
process control parameters are needed or desired.
In addition, data from the process can be used to
predict the future performance of the process. If
the chart indicates that the monitored process is
not in control, analysis of the chart can help
determine the sources of variation, as this will
result in degraded process performance.[1] A
process that is stable but operating outside of
desired (specification) limits (e.g., scrap rates
may be in statistical control but above desired
limits) needs to be improved through a deliberate
effort to understand the causes of current
performance and fundamentally improve the
process.
The control chart is one of the seven basic tools of
quality control.[3] Typically control charts are
used for time-series data, though they can be used
for data that have logical comparability (i.e. you
want to compare samples that were taken all at
the same time, or the performance of different
individuals), however the type of chart used to do
this requires consideration.

4. 3. Pareto chart
A Pareto chart, named after Vilfredo Pareto, is a type
of chart that contains both bars and a line graph, where
individual values are represented in descending order
by bars, and the cumulative total is represented by the
line.
The left vertical axis is the frequency of occurrence,
but it can alternatively represent cost or another
important unit of measure. The right vertical axis is
the cumulative percentage of the total number of
occurrences, total cost, or total of the particular unit of
measure. Because the reasons are in decreasing order,
the cumulative function is a concave function. To take
the example above, in order to lower the amount of
late arrivals by 78%, it is sufficient to solve the first
three issues.
The purpose of the Pareto chart is to highlight the
most important among a (typically large) set of
factors. In quality control, it often represents the most
common sources of defects, the highest occurring type
of defect, or the most frequent reasons for customer
complaints, and so on. Wilkinson (2006) devised an
algorithm for producing statistically based acceptance
limits (similar to confidence intervals) for each bar in
the Pareto chart.
4. Scatter plot Method

5. A scatter plot, scatterplot, or scattergraph is a type of
mathematical diagram using Cartesian coordinates to
display values for two variables for a set of data.
The data is displayed as a collection of points, each
having the value of one variable determining the position
on the horizontal axis and the value of the other variable
determining the position on the vertical axis.[2] This kind
of plot is also called a scatter chart, scattergram, scatter
diagram,[3] or scatter graph.
A scatter plot is used when a variable exists that is under
the control of the experimenter. If a parameter exists that
is systematically incremented and/or decremented by the
other, it is called the control parameter or independent
variable and is customarily plotted along the horizontal
axis. The measured or dependent variable is customarily
plotted along the vertical axis. If no dependent variable
exists, either type of variable can be plotted on either axis
and a scatter plot will illustrate only the degree of
correlation (not causation) between two variables.
A scatter plot can suggest various kinds of correlations
between variables with a certain confidence interval. For
example, weight and height, weight would be on x axis
and height would be on the y axis. Correlations may be
positive (rising), negative (falling), or null (uncorrelated).
If the pattern of dots slopes from lower left to upper right,
it suggests a positive correlation between the variables
being studied. If the pattern of dots slopes from upper left
to lower right, it suggests a negative correlation. A line of
best fit (alternatively called 'trendline') can be drawn in
order to study the correlation between the variables. An
equation for the correlation between the variables can be
determined by established best-fit procedures. For a linear
correlation, the best-fit procedure is known as linear
regression and is guaranteed to generate a correct solution
in a finite time. No universal best-fit procedure is
guaranteed to generate a correct solution for arbitrary
relationships. A scatter plot is also very useful when we
wish to see how two comparable data sets agree with each
other. In this case, an identity line, i.e., a y=x line, or an
1:1 line, is often drawn as a reference. The more the two
data sets agree, the more the scatters tend to concentrate in
the vicinity of the identity line; if the two data sets are
numerically identical, the scatters fall on the identity line

6. exactly.
5.Ishikawa diagram
Ishikawa diagrams (also called fishbone diagrams,
herringbone diagrams, cause-and-effect diagrams, or
Fishikawa) are causal diagrams created by Kaoru
Ishikawa (1968) that show the causes of a specific
event.[1][2] Common uses of the Ishikawa diagram are
product design and quality defect prevention, to identify
potential factors causing an overall effect. Each cause or
reason for imperfection is a source of variation. Causes
are usually grouped into major categories to identify these
sources of variation. The categories typically include
 People: Anyone involved with the process
 Methods: How the process is performed and the
specific requirements for doing it, such as policies,
procedures, rules, regulations and laws
 Machines: Any equipment, computers, tools, etc.
required to accomplish the job
 Materials: Raw materials, parts, pens, paper, etc.
used to produce the final product
 Measurements: Data generated from the process
that are used to evaluate its quality
 Environment: The conditions, such as location,
time, temperature, and culture in which the process
operates
6. Histogram method

7. A histogram is a graphical representation of the
distribution of data. It is an estimate of the probability
distribution of a continuous variable (quantitative
variable) and was first introduced by Karl Pearson.[1] To
construct a histogram, the first step is to "bin" the range of
values -- that is, divide the entire range of values into a
series of small intervals -- and then count how many
values fall into each interval. A rectangle is drawn with
height proportional to the count and width equal to the bin
size, so that rectangles abut each other. A histogram may
also be normalized displaying relative frequencies. It then
shows the proportion of cases that fall into each of several
categories, with the sum of the heights equaling 1. The
bins are usually specified as consecutive, non-overlapping
intervals of a variable. The bins (intervals) must be
adjacent, and usually equal size.[2] The rectangles of a
histogram are drawn so that they touch each other to
indicate that the original variable is continuous.[3]
III. Other topics related to quality management system construction (pdf
download)
quality management systems
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