Advanced Construction Management
Quality is the totality of features and characteristics of a product or
service that bear on its ability to satisfy stated or implied needs.
 Some goals of quality programs include:
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 Fitness for use. (Is the product or service capable of being used?)
 Fitness for purpose. (Does the product or service meet its intended purpose?)
 Customer satisfaction. (Does the product or service meet the customer's
expectations?)
 Conformance to the requirements. (Does the product or service conform to the
requirements?)
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Quality Planning
Quality Assurance
Quality Control
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The process of identifying which quality standards are relevant to the project and
determining and how to satisfy them.
Input includes: Quality policy, scope statement, product description, standards and
regulations, and other process Output.
Methods used: benefit / cost analysis, benchmarking, flowcharting, and design of
experiments
Output includes: Quality Management Plan, operational definitions, checklists, and
Input to other processes.
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The process of evaluating overall project performance on a regular basis
to provide confidence that the project will satisfy the relevant quality
standards.
Input includes: Quality Management Plan, results of quality control
measurements, and operational definitions.
 Methods used: quality planning tools and techniques and quality audits.
 Output includes: quality improvement.
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Process of identifying or deciding all the quality requirements and
guidelines or framework for a project
Documents: QA Documents
 Quality assurance includes all the activities related to satisfying
the relevant quality standards for a project
 Another goal of quality assurance is continuous quality
improvement
 Benchmarking can be used to generate ideas for quality
improvements
 Quality audits help identify lessons learned that can improve
performance on current or future projects
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Tasks or activities performed in ground according to the
quality guidelines or framework prescribed in the QA
documents
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monitoring specific project results to ensure that they comply
with the relevant quality standards while identifying ways to
improve overall quality
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The main outputs of quality control are
 acceptance decisions
 rework
 process adjustments
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Some tools and techniques include
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pareto analysis
statistical sampling
quality control charts
testing
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Was the project completed on time?
Was the project completed within budget?
Did the structure as well as the owner expectation?
Is it stable ?
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common model :a group responsible for quality assurance and
another group primarily responsible for safety
smaller projects, the project manager or an assistant might
assume these and other responsibilities
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Inspectors and quality assurance personal
While the multitude of participants involved in the
construction process require the services of inspectors, it
cannot be emphasized too strongly that inspectors are only a
formal check on quality control. Quality control should be a
primary objective for all the members of a project team
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American Society for Testing and Materials (ASTM)
American National Standards Institute (ANSI)
SNI (Standard National Indonesia)
American Welding Society
Standard Specifications for Highway Bridges
BINAMARGA (Indonesian Standard for Highway)
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Elevations and dimensions shown on plan within a tolerance
of plus or minus 0.10 foot, and extending a sufficient distance
from footings and foundations to permit placing and removal
of concrete formwork, installation of services, other
construction, and for inspection
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Traditional: specifications for asphalt pavement specified the
composition of the asphalt material, the asphalt temperature
during paving, and compacting procedures
a performance specification for asphalt would detail the
desired performance of the pavement with respect to
impermeability, strength, etc.
Concrete pavements of superior strength result in cost savings by delaying the time
at which repairs or re-construction is required. In contrast, concrete of lower
quality will necessitate more frequent overlays or other repair procedures
Based on these life cycle cost considerations, a typical pay schedule might be
Load Ratio
Pay Factor
<0.50
0.50-0.69
0.70-0.89
0.90-1.09
1.10-1.29
1.30-1.49
>1.50
Reject
0.90
0.95
1.00
1.05
1.10
1.12
AGE
RATIO OF STRENGTH
3
0.45
7
0.65
14
0.88
21
0.95
28
1.00
90
1.20
365
1.35
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Unforeseen circumstances
Incorrect design decisions or changed by owner
Some design rely upon informed
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insuring accurate and useful information is an important part
of maintaining quality performance
document control (including changes during the construction
process),
procurement,
field inspection and testing,
final checkout of the facility.
Conform to elevations and dimensions shown on plan within a
tolerance of plus or minus 0.10 foot, and extending a sufficient
distance from footings and foundations to permit placing and
removal of concrete formwork, installation of services, other
construction, and for inspection
This set of specifications requires judgment in application
since some items are not precisely specified
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Quality control in construction typically involves insuring
compliance with minimum standards of material and
workmanship in order to insure the performance of the facility
according to the design.
For the purpose of insuring compliance, random samples and
statistical methods are commonly used as the basis for
accepting or rejecting work completed and batches of
materials. Rejection of a batch is based on non-conformance
or violation of the relevant design specifications
An implicit assumption in these traditional quality control practices is the notion of an
acceptable quality level which is a allowable fraction of defective items. Materials
obtained from suppliers or work performed by an organization is inspected and
passed as acceptable if the estimated defective percentage is within the acceptable
quality level. Problems with materials or goods are corrected after delivery of the
product
In contrast to this traditional approach of quality control is the goal of total quality
control. In this system, no defective items are allowed anywhere in the construction
process. While the zero defects goal can never be permanently obtained, it provides
a goal so that an organization is never satisfied with its quality control program even
if defects are reduced by substantial amounts year after year.
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This concept and approach to quality control was first
developed in manufacturing firms in Japan and Europe, but
has since spread to many construction companies.
The best known formal certification for quality improvement
is the International Organization for Standardization's ISO
9000 standard. ISO 9000 emphasizes good documentation,
quality goals and a series of cycles of planning,
implementation and review.
Total quality control is a commitment to quality expressed in all parts of an organization
and typically involves many elements.
Design reviews to insure safe and effective construction procedures are a major element.
Other elements include extensive training for personnel, shifting the responsibility for
detecting defects from quality control inspectors to workers, and continually maintaining
equipment.
Worker involvement in improved quality control is often formalized in quality circles in
which groups of workers meet regularly to make suggestions for quality improvement.
Material suppliers are also required to insure zero defects in delivered goods. Initially, all
materials from a supplier are inspected and batches of goods with any defective items
are returned. Suppliers with good records can be certified and not subject to complete
inspection subsequently
#
Name
Where
Purpose
01
Cause & Effect
Diagram
(Ishikawa, Fishbone)
Diagram showing an outcome and a list of
potential causes (appears like a fish skeleton)
• To illustrate how various factors might be linked to potential problems or
effects
• Used In Quality Planning (look forwards) and Quality Control (look
backwards)
• Help stimulate thinking, organize thoughts, generate discussion
02
Control Charts
Graphical representation mapping process
variables within acceptable limits; upper and
lower control limits contain normal/expected
variations; uses Rule of Seven to identify non
random patterns
• To determine whether or not a process is stable or has predictable
performance
• Data gathering
• Special Cause identification / assignable causes
• Shows Process behaviour over time
• Shows if the process is under control v out of control
03
Flowcharting
Diagram showing activities, decision point and
sequence from beginning to end and interrelation
of various elements
• Can assist anticipation of problems and preventative action
• Used In Quality Planning (look forwards) and Quality Control (look
backwards)
04
Histogram
(Bar chart)
Bar Chart where Distribution of variables &
height of column represent relative frequency.
• Helps Identify Cause of the problem by the shape and width of the
distribution
05
Pareto Chart
(80-20 chart)
(Histogram)
Histogram order by frequency of occurrence,
which shows how many defects regenerated by
type or category of identified cause
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06
Run Chart
Line Graph showing data points plotted in the
order in which they occur
• Shows History and pattern of variation. Trend Analysis
• Technical Performance (number of error/defects identified; number still
uncorrected)
07
Scatter Diagram
Diagram showing the pattern of relationship
between two variables
• The closer the points are to a diagonal line the more closely related they are;
helps identify cause
Identification of non-conformance
Addressing root cause of the most critical problems
Useful if there is little time available / prioritize
Separates critical few from the uncritical many
Exhaustive or 100% testing of all materials and work by inspectors can be exceedingly
expensive, however. In many instances, testing requires the destruction of a material
sample, so exhaustive testing is not even possible.
As a result, small samples are used to establish the basis of accepting or rejecting a
particular work item or shipment of materials.
Statistical methods are used to interpret the results of test on a small sample to reach a
conclusion concerning the acceptability of an entire lot or batch of materials or work
products
There are two types of statistical sampling which are commonly used for
the purpose of quality control in batches of work or materials:
1. The acceptance or rejection of a lot is based on the number of defective
(bad) or no defective (good) items in the sample. This is referred to as
sampling by attributes.
2. Instead of using defective and no defective classifications for an item,
a quantitative quality measure or the value of a measured variable is
used as a quality indicator. This testing procedure is referred to as
sampling by variables.
Whatever sampling plan is used in testing, it is always assumed that the
samples are representative of the entire population under consideration
Consider a lot of finite number N, in which m items are defective (bad) and the
remaining (N-m) items are non-defective (good). If a random sample of n
items is taken from this lot, then we can determine the probability of having
different numbers of defective items in the sample
the probability of having exactly x defective items in the sample is given by the ratio as
the hyper geometric series
Suppose that the actual fraction of defectives in the lot is p and the actual fraction of no
defectives is q
Sampling by variables was developed for application to continuously measurable quantities of this type.
The procedure uses measured values of an attribute in a sample to determine the overall acceptability of
a batch or lot. Sampling by variables has the advantage of using more information from tests since it is
based on actual measured values rather than a simple classification. As a result, acceptance sampling by
variables can be more efficient than sampling by attributes in the sense that fewer samples are required
to obtain a desired level of quality control.
In applying sampling by variables, an acceptable lot quality can be defined with
respect to an upper limit U, a lower limit L
With both a lower and an upper limit on acceptable quality, the fraction defective
would be the fraction of items greater than the upper limit or less than the lower
limit
In the application of sampling by variables plans, the measured characteristic is
virtually always assumed to be normally distributed
The normal distribution is likely to be a reasonably good assumption for many
measured characteristics such as material density or degree of soil compaction.
which is t-distributed with n-1 degrees of freedom
With an upper limit, the calculations are similar, and the probability that the
average value of a population is less than a particular upper limit can be calculated
from the test statistic
The calculations to estimate the fraction of items above an upper limit or
below a lower limit are very similar to those for the population average. The
only difference is that the square root of the number of samples does not
appear in the test statistic formulas: