10120130405014

International Journal of Management (IJM), ISSN 0976 – 6502(Print), ISSN 0976 - 6510(Online),

Volume 4, Issue 5, September - October (2013)

109

READY MIXED CONCRETE SELECTION FOR INFRASTRUCTURE

DEVELOPMENT THROUGH ANALYTIC HIERARCHY PROCESS (AHP) IN

THE NEW MILLENNIUM

Ashish H. Makwana1, Prof. Jayeshkumar Pitroda

2

1Student of final year M.E. C. E. & M., B.V.M. Engineering College, Vallabh Vidyanagar

2 Assistant Professor and Research Scholar, Civil Engineering Department,

B.V.M. Engineering College, Vallabh Vidyanagar– Gujarat – India.

ABSTRACT

The Analytic Hierarchy Process (AHP) is a well-known multi-criteria decision making

method that has been applied to solve problems in diverse areas. This method was developed by Dr.

Thomas L. Saaty in 1970s as a tool to help with solving technical and managerial problems. During

the past decade, the construction industry in India witnessed remarkable growth, in which the ready-

mixed concrete (RMC) industry can claim to be a proud partner. Historically speaking, India missed

the benefits of RMC technology for decades. It was only in the early nineties that the industry was

born, but really commenced from the second half of the nineties. During the past few years, housing

and infrastructure have remained the major expansion area. Faster speed and improved quality of

concrete have been the two major demands of these sectors. Ready-mixed concrete was the right

solution for this and it was heartening to see that the RMC industry responded positively to these

demands. The result was the rapid growth of the RMC industry. The industry, which was initially

confined to metropolitan cities, later spread to the two-tier and three-tier cities, vindicating the fact

that RMC was a right solution for different markets. The growth of the RMC industry brought in its

wake certain challenges, chief amongst which was about the quality of concrete supplied by RMC

plants.

KEYWORDS: Analytic Hierarchy Process (AHP), Construction Industry, Ready Mixed Concrete

(RMC), quality, growth, plants.

INTERNATIONAL JOURNAL OF MANAGEMENT (IJM)

ISSN 0976-6502 (Print)

ISSN 0976-6510 (Online)

Volume 4, Issue 5, September - October (2013), pp. 109-126

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INTRODUCTION

Ready-Mixed Concrete (IS: 4926-2003) as “Concrete mixed in a stationary mixer in a central

batching and mixing plant or in a truck mixer and supplied in the fresh condition to the purchaser

either at the site or into the purchaser’s vehicles.” [10]

Ready mixed concrete (RMC) is a specialized material in which cement, aggregate, and other

ingredients are weigh batched at a plant in a central or truck mixer before delivery to the construction

site in a condition ready for placing by the customer. RMC is manufactured at a place away from the

construction site, the two locations being linked by a transport operation. IS: 4926-2003 defines

ready mixed concrete as 'Concrete mixed in a stationary mixer in a central batching and mixing plant

or in a truck mixer and supplied in a fresh condition to the purchaser either at site or into purchaser's

vehicle. [4]

The short 'life' of fresh concrete, with only 2-3 hours before it must be placed, results in ready

mixed concrete being a very much local delivery service, with rarely more than 30-60 minutes

journey to the construction site. The need for supply of ready mixed concrete to fit in with the

customer's construction program means that RMC has to be both a product and a delivery service.

This means that the ready mixed supplier is in two separate businesses — firstly, processing

materials and secondly, transporting product with a very short life. [4]

When researchers refer to the customer, researchers are speaking in effect of two customers.

As far as the product is concerned, concrete must satisfy not only the person who is using it, i.e., the

builder or contractor, but also the authority responsible for defining the properties. However, the

ready mix supplier has only one contract and that is with the builder or contractor and relies on the

latter to define exactly the requirements of die specifying authority (engineer). [4]

The basic product in ready mix concrete is fresh concrete, which is placed on site by the

customer. It is distinct from hardened, precast concrete units. The introduction of ready mixed

concrete has gradually replaced the operation in which the contractor made his own concrete on site.

When ready mix concrete was first introduced, engineers and contractors with considerable expertise

in concrete production and quality control were suspicious of the quality of this new product, whose

manufacture was no longer under their control. Ready mix concrete suppliers need to have stringent

quality control for their product and its delivery, so that customer's apprehensions regarding the

quality of concrete supplied by them are taken care. It will take a while before the customer places

his confidence and trust in the product and services offered by the supplier. [4]

Experience shows that the specifying authority or engineer will be satisfied with ready mixed

concrete if,

(1) The supply complies with the specification for fresh and hardened concrete; (2) He is

assured of continuity of suppliers from experienced and reliable ready mix concrete companies. [4]

In turn, the contractor or builder will be satisfied if,

(1) The deliveries are always on time and concrete is supplied at the required rate, (2) The

workability is correct and appropriate for the placing method used, (3) The quantities are correct, (4)

On those occasions when concrete proves to be defective, the supplier bears his fair share of the cost

of removal and replacement of the defective material, (5) The total cost of concrete, including

supply, handling, and placing, is economic. From this, it is seen that the specifying authority

(engineer) is concerned primarily with the quality of the product, whereas the user, i.e., builder or

contractor, is mainly concerned with the service and its cost, i.e., value for his money. [4]



111

Figure 1: Modern Ready Mixed Concrete Plant

(Source: JAGAJI Construction Janta Circle, Opp. Elecon Company, Vallabh Vidyanagar – Anand –

Gujarat)

Figure 2: Modern Ready Mixed Concrete Plant (Source: RMC India pvt. Ltd. Vadodara, Gujarat)

LITERATURE REVIEW

Ready mixed concrete was first patented in Germany in 1903, but means of transporting was

not sufficiently developed by then to enable the concept to be utilized commercially. The first



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commercial delivery of ready mixed concrete was made in Baltimore, USA in 1913 and the first

revolving-drum-type transit mixer, of a much smaller capacity than those available today, was born

in 1926. In 1920s and 1930s, ready mixed concrete was introduced in some European countries. [4]

Some early plants were of very small capacities. In 1931, a ready mixed concrete plant set up at what

is now Heathrow airport, London, had 1.52m capacity central mixer, supplying six 1.33 m3 capacity

agitators with an output of 30.58 m3/h. Aggregates were stored in four compartments, each of 76.45

m3 capacity. Cement was handled manually in bags. Till the beginning of World War II, there were

only six firms producing ready mixed concrete in UK. After the War, there was a boost to the ready

mixed concrete industry in whole of Europe. In mid 1990s, there were as many as 1100 RMC plants

in the UK, consuming about 45% of cement produced in the country. [4]

European Ready Mixed Concrete Organization (EMRO) was formed in Europe in 1967. In

1997, some 5850 companies having a large turnover were represented by it. Cement consumption in

RMC plants ranged from 33% to 62% of total cement sales. [4]

In USA, till 1933, only 5% of cement produced was utilized through RMC. ASTM published

first specification for ready mixed concrete in 1934. The RMC industry in USA progressed steadily.

During 1950-4975, RMC industry consumption of total OPC in the USA increased form (l/3) rd to

(2/3) rd and by 1990 to 72.4%. There were 5000 RMC companies in that country by 1978. [4]

In Japan, the first RMC plant was set up in 1949. Initially, dump trucks were used to haul concrete of

low consistency for road construction. In early 1950s mixing type trucks were introduced. Since then

there has been a phenomenal growth of the industry in that country. By the end of 1970s there were

4462 RMC plants in Japan. By 1992 Japan was the largest producer of RMC, producing 181.96

million tons of concrete. In many countries, including some developing countries such as Taiwan,

Malaysia, Indonesia, as well as certain countries in the Gulf region, RMC industry is well developed

today. [4]

Ready mixed concrete plants arrived in India in early 1950s, but their use was restricted to

only major construction projects such as dams. Later RMC was also used for other projects such as

construction of long-span bridges, industrial complexes, etc. These were, however, captive plants

which formed an integral part of the construction projects. It was during 1970s when the Indian

construction industry spread its tentacles overseas, particularly in the Gulf region, that an awareness

of ready mixed concrete was created among Indian engineers, contractors, and builders. Indian

contractors in their works abroad started using RMC plants of 15 to 60 m3/h, and some of these

plants were brought to India in 1980s. Currently there are many ready mix plants operating in

different parts of India, especially in metropolitan cities and towns. [4]

NEED OF READY MIXED CONCRETE SELECTION USING ANALYTIC HIERARCHY

PROCESS

The conventional Ready Mixed Concrete selection approach may sometime towards

improper Ready Mixed Concrete selection which brings partial failure of the project. Present Ready

Mixed Concrete selection process of construction companies in Central Gujarat Region of India was

studied in the beginning of this Research work. Present approach lacks scientific methodology and

does not consider multi-criteria in decision making. There is a need of scientific methodology for

Ready Mixed Concrete selection approach. Such approach will provide the best selection of Ready

Mixed Concrete considering all aspects of the process.

Hence, the need of this Research work based upon various utility measures like quality control, cost,

delivery, quantity at which owners or plant manager have to concentrate for enhancing profit as well

as maintaining standard by Analytic Hierarchy Process (AHP) which will help the decision maker to

understand the problem systematically.



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ADVANTAGES OF READY MIXED CONCRETE

Advantages of Ready Mixed Concrete are well recognized. Some of these are given below:

� Uniform and assured quality of concrete: Since RMC is factory produced, the raw material

and production process quality is better than conventional site mixed concrete.

� Durability of concrete: RMC can ensure correct W/C ratio to be maintained. Hence the

durability of RMC is consistent and better.

� Faster construction speed: In site mixed concrete, the contractor needs to mobilize labour for

mixing as well as placing. In RMC, fresh concrete is supplied in a place able condition and can

directly be placed by pumping. Hence a faster construction speed can be achieved.

� Elimination of storage needs at the construction site: In case of site mixed concrete; all raw

materials such as aggregates, sand, and cement have to be stored at the site. In urban situations

and when the work is progressing close to the highways, there is a problem of storage of raw

materials affecting smooth flow of traffic. In case of RMC, this problem is completely avoided

as the storage of materials takes place at the central plant.

� Easier admixture addition: In RMC admixtures can be added in a controlled manner because

of the use of sophisticated computer-controlled methods of releasing exact quantities needed.

This is not possible in normal concreting.

� Documentation of mix designs: The contractor purchases fresh concrete from the supplier of

RMC, who is responsible not only for documentation but also for maintaining the records.

� Reduction in wastage of material: In RMC materials are stored in bulk and used in bulk.

Hence wastage that occurs in loose handling of cement, etc. is completely avoided.

� RMC is eco-friendly: The production of RMC is done in an environmentally assessed and

licensed central plant. Hence, dust and noise pollution which is inevitable in concrete is avoided. [4]

DISADVANTAGES OF READY MIXED CONCRETE

Disadvantages of RMC are well recognized. Some of these are given below:

� Need huge initial investment.

� Not affordable for small projects (small quantity of concrete).

� Needs effective transportation system from R.M.C. to site.

� Traffic jam or failure of the vehicle creates a problem if the proper dose of retarder is not given.

� Labors should be ready on site to cast the concrete in position to vibrate it and compact it.

� Double handling, this results in additional cost and losses in weight, requirement of go downs

for storage of cement and large area at site for storage of raw materials.

� Aggregates get mixed and impurities creep in because of wind, weather and mishandling at site.

� Improper mixing at site, as there is ineffective control and intangible cost associated with

unorganized preparation at site are other drawbacks of RMC.

� There are always possibilities of manipulation; manual error and mischief as concreting are done

at the mercy of gangs, who manipulate the concrete mixes and water cement ratio. [2]

OF THE STUDY

This paper has an objective to develop criteria framework which contributes to Bricks

selection. Secondly, it suggests a case study based Analytic Hierarchy Process (AHP) for Bricks

selection.



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A CASE STUDY BASED CRITERIA FRAMEWORK FOR BRICKS SELECTION

Bricks selection depends upon many factors. Literature study and interview with construction

professionals were carried out to prepare the hierarchical framework for bricks selection. Criteria

which contribute towards bricks selection are divided in four major groups such as: Clay bricks,

Human hair bricks, Fly ash (FAL-G) bricks, Sugarcane bassage ash bricks. These criteria are further

subdivided into sub criteria. A final framework for Brick selection criteria is given in Figure 3.

Figure 3: Framework for bricks selection (a case study) – Indian context

The purpose of this research paper is to develop a ranking of criteria which are responsible

for bricks selection (a case study). According to the Analytical Hierarchy Process (AHP),

development of the Criteria Framework (Figure 3) in Indian context is having total 4 numbers of sub-

criteria’s which are identified for each type of bricks typically which are Quality, Quantity, Delivery

and Cost which affect the bricks selection problem. Main Criteria for bricks selection are: Fly ash

(FAL-G) bricks, Sugarcane bassage ash bricks, Human hair bricks, Clay bricks.

� ABRAVIATION

� CL – Clay Bricks � CS - Cost

� TM - Time

� QL - Quality

� QN – Quantity

� HHB - Human Hair Bricks � CS - Cost

� TM - Time

� QL - Quality

� QN – Quantity

� FAB - Fly Ash (FAL –G) Bricks � CS - Cost

� TM - Time

� QL - Quality

� QN – Quantity

� SBAB - Sugarcane Bassage Ash

Bricks � CS - Cost

� TM - Time

� QL - Quality

� QN - Quantity



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ANALYTIC HIERARCHY PROCESS

Analytic Hierarchy Process has been a tool at the hands of decision makers and researchers;

and it is the most widely used multiple criteria decision making tools [19]

. The AHP method is

developed by Thomas L. Saaty in 1980 [16]

. AHP is very popular and widely applicable in various

fields due to its simplicity, ease of use and flexibility [17]

. AHP is a reliable tool to facilitate

systematic and logical decision making processes and determine the significance of a set of criteria

and sub-criteria. AHP method is very suitable for complex social issue in which intangible and

tangible factors cannot be separated [11]

. AHP helps in reducing bias in decision-making and it can

minimize common pitfalls of team decision-making process, such as lack of focus, planning,

participation or ownership, which ultimately are costly distractions that can prevent teams from

making the right choice [5, 6, and 7]

.

The AHP is based on the experience gained by its developer, T. L. Saaty, while directing

research projects in the US Arms Control and Disarmament Agency. It was developed as a reaction

to the finding that there is a miserable lack of common, easily understood and easy-to-implement

methodology to enable the taking of complex decisions. Since then, the simplicity and power of the

AHP has led to its widespread use across multiple domains in every part of the world. The AHP has

found use in business, government, social studies, R&D, defence and other domains involving

decisions in which choice, prioritization or forecasting is needed. [12]

Owing to its simplicity and ease of use, the AHP has found ready acceptance by busy

managers and decision-makers. It helps structure the decision-maker’s thoughts and can help in

organizing the problem in a manner that is simple to follow and analyze. Broad areas in which the

AHP has been applied include alternative selection, resource allocation, forecasting, business process

re-engineering, quality function deployment, balanced scorecard, benchmarking, public policy

decisions, healthcare, and many more. Basically the AHP helps in structuring the complexity,

measurement and synthesis of rankings. These features make it suitable for a wide variety of

applications. The AHP has proved a theoretically sound and market tested and accepted

methodology. Its almost universal adoption as a new paradigm for decision-making coupled with its

ease of implementation and understanding constitute its success. More than that, it has proved to be a

methodology capable of producing results that agree with perceptions and expectations. [12]

The importance of the AHP, its variants, and the use of pairwise comparisons in decision

making is best illustrated in the more than 1,000 references cited in [Saaty, 1994]. A number of

special issues in refereed journals have been devoted to the AHP and the use of pairwise

comparisons in decision making. These issues are: Socio-Economic Planning Sciences [Vol. 10,

No.6, 1986]; Mathematical Modeling [Vol. 9, No. 3-5, 1987]; European Journal of Operational

Research [Vol. 48, No.1, 1990]; and Mathematical and Computer Modeling [Vol. 17, No. 4/5, 1993].

Also, four international symposia (called ISAHP) have been dedicated on the same topic so far and

one such event is now scheduled every two years. [12]

STEP BY STEP PROCEDURE OF ANALYTIC HIERARCHY PROCESS

The procedure for using the AHP can be summarized as:

� Define the problem and determine the kind of knowledge sought.

� Structure the decision hierarchy from the top with the goal of the decision, then the objectives

from a broad perspective, through the intermediate levels (criteria on which subsequent elements

depend) to the lowest level (which usually is a set of the alternatives).

� Construct a set of pairwise comparison matrices. Each element in an upper level is used to

compare the elements in the level immediately below with respect to it.



116

� Use the priorities obtained from the comparisons to weigh the priorities in the level immediately

below. Do this for every element. Then for each element in the level below add its weighed

values and obtain its overall or global priority. Continue this process of weighing and adding

until the final priorities of the alternatives in the bottom most level are obtained. [15]

To make comparisons, Researchers need a scale of numbers that indicates how many times more

important or dominant one element is over another element with respect to the criterion or

property with respect to which they are compared. Table No. 1 exhibits the scale.

Table No. 1: Fundamental Scale of Absolute Numbers

INTENSITY OF

IMPORTANCE DEFINATION EXPLATION

1 Equal Importance Two activities contribute equally to the

objective

2 Weak or slight

3 Moderate importance Experience and judgement slightly

favour one activity over another 4 Moderate plus

5 Strong importance Experience and judgement strongly

favour one activity over another 6 Strong plus

7 Very strong or

Demonstrated importance

An activity is favoured very strongly over

another; its dominance demonstrated in

practice 8 Very, very strong

9 Extreme importance

The evidence favouring one activity over

another is of the highest possible order of

affirmation

RESIPROCALS OF

ABOVE (1-9)

If activity i has one of the above non-

zero numbers assigned to it when

compared with activity j, then j has the

reciprocal value when compared with i

A reasonable assumption

1.1–1.9 If the activities are very close

May be difficult to assign the best value

but when compared with other

contrasting activities the size of the small

numbers would not be too noticeable, yet

they can still indicate the relative

importance of the activities.

(Source: Saaty, T.L. (2008) ‘Decision making with the analytic hierarchy process’, Int. J. Services

Sciences, Vol.1, No.1, pp.83–98) [15]

APPLICATION OF ANALYTIC HIERARCHY PROCESS

It is widely used for decision making. AHP technique is widely applied to various fields as given

below:

� Choice - The selection of one alternative from a given set of alternatives, usually where there

are multiple decision criteria involved.

� Ranking - Putting a set of alternatives in order from most to least desirable.

� Prioritization - Determining the relative merit of members of a set of alternatives, as opposed to

selecting a single one or merely ranking them.

� Resource allocation - Apportioning resources among a set of alternatives.



117

� Benchmarking - Comparing the processes in one’s own organization with those of other best-

of-breed organizations.

� Quality management - Dealing with the multidimensional aspects of quality and quality

improvement.

� Conflict resolution - Settling disputes between parties with apparently incompatible goals or

positions. [1]

ADVANTAGES OF ANALYTIC HIERARCHY PROCESS

It illustrates how possible changes in priority at the upper levels have an effect on the priority

of criteria at lower levels.

The method is able to rank criteria according to the needs of the buyer which also leads to more

precise decisions concerning supplier selection.

It provides the buyer with an overview of criteria, their function at the lower levels and goals

at the higher levels.

PROPOSED READY MIXED CONCRETE SELECTION PROCESS

Ready Mixed Concrete selection is a multi-criteria decision making problem and hence AHP

fits to it. It is suggested to use AHP technique for Ready Mixed Concrete selection. So, a survey

questionnaire can be prepared based on AHP technique. It will require the experts to compare

various criteria and sub-criteria on 1 to 9 scales. While doing this comparison they have to use their

past knowledge and information of criteria as well as available Ready Mixed Concrete Plants.

Figure 4 - Explains proposed AHP based Ready Mixed Concrete selection process.

WEIGHTS ALLOCATION

With the help of AHP approach, by doing pair wise comparisons from all respondents,

weights for all sub-criteria’s are calculated. Eigen vector method (EM) is used to derive local

weights for each sub-criterion. The preference weights given by each respondent is aggregated by

Geometric mean method (GMM), as GMM is more consistent with the meanings of both judgments

& priorities in AHP [9]

. When the GMM is used as the prioritization procedure, the group

inconsistency is at least as good as the worst individual inconsistency for aggregation approaches [9]

.

In AHP, two different approaches can be adopted for group decision making: the aggregation of

individual judgments (AIJ) and the aggregation of individual priorities (AIP) [14]

. In this research,

AIP method is used; as each respondent is acting in his or her rights and not working together as

team member. In addition, group member are considered to be of equal importance.

Priorities from individual expert are synthesized into a single priority through geometric

mean in order to get an overall estimate of the priorities for each criterion in every level of hierarchy.

The geometric mean for synthesizing individual priorities is expressed in Eq. (1) and (2).

=

… (1)

= … (2)



118

Here,

G = Geometric mean of individual priorities,

a = Priority weight given by expert

n = Number of experts

The Global weight of each sub-criteria is calculated as per Eq. (3) [13]

… (3)

Where:

i = 1, 2, 3…….n = main criteria, sub-criteria at each level

WM, i = Local Weight of Main criteria, W S, i = Local Weight of Sub-criteria

At every level

= 1

= 1 …..

(4)

According to the AHP the best alternative (in the maximization case) is indicated by the following

relationship [8]

..…(5)

Figure 4: Proposed AHP based Ready Mixed Concrete selection process



119

A CASE STUDY BASED ON BRICKS SELECTION USING ANALYTIC HIERARCHY

PROCESS (AHP)

i. Pairwise Comparison Matrices for the main criteria and its analysis

Table No. 2: Pairwise Comparison Matrices for the Main Criteria

Criteria Clay bricks Human hair bricks Fly ash (FAL - G)

bricks

Sugarcane bassage

ash bricks

Clay bricks 1.00 1.00 0.25 0.20

Human hair bricks 1.00 1.00 0.25 0.33

Fly ash (FAL - G)

bricks 4.00 4.00 1.00 3.00

Sugarcane bassage ash

bricks 5.00 3.00 0.33 1.00

TOTAL 11.00 9.00 1.83 4.53

Now, Normalised matrices is found by dividing each component of matrices by appropriate column

sum.

Table No. 3: Normalised Matrices for Main Criteria

Criteria Clay bricks

(CB)

Human hair

bricks (HHB)

Fly ash (FAL -

G) bricks (FAB)

Sugarcane

bassage ash

bricks

(SBAB)

Row

average

Clay bricks (CB) 0.09 0.11 0.14 0.04 0.10

Human hair bricks

(HHB) 0.09 0.11 0.14 0.07 0.10

Fly ash (FAL - G)

bricks (FAB) 0.36 0.44 0.55 0.66 0.50


bricks (SBAB) 0.45 0.33 0.18 0.22 0.30

TOTAL 1.00 1.00 1.00 1.00 1.00

Therefore, local weights of the criteria’s are as follows.

LWCB = 0.10, LWHHB = 0.10, LWFAB = 0.50, LWSBAB = 0.30,

Now, check the consistency of the result.

Lemna max. = sum of [Wi * sum of each column]

Lemna max. = 4.25, and n = 4

Now, find Consistency index (CI) = {Lemna max - n} / (n - 1)

CI = 0.08 and now, Consistency Ratio (CR) = CI / RI

Where, RI (Random Index) = 0.90 (for n = 4),

CR = 0.09 < 0.1 hence OK. (According to T. Satty – the founder of the AHP method)

ii. Pairwise Comparison Matrices for the Criteria-Clay bricks (CB)

Table No. 4: Pairwise Comparison Matrices for the Criteria-Clay bricks

Criteria Quality Control

(QC) Quantity (QN) Delivery (DL) Cost (CS)

Quality Control (QC) 1.00 1.00 1.00 0.25

Quantity (QN) 1.00 1.00 1.00 1.00

Delivery (DL) 1.00 1.00 1.00 0.33

Cost (CS) 4.00 1.00 3.00 1.00

TOTAL 7.00 4.00 6.00 2.58



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Table No. 5: Normalised Matrices for the Criteria-Clay bricks

Criteria Quality Control (QC) Quantity (QN) Delivery

(DL) Cost (CS) Row average

Quality Control (QC) 0.14 0.25 0.17 0.10 0.16

Quantity (QN) 0.14 0.25 0.17 0.39 0.24

Delivery (DL) 0.14 0.25 0.17 0.13 0.17

Cost (CS) 0.57 0.25 0.50 0.39 0.43

TOTAL 1.00 1.00 1.00 1.00 1.00


LWQC = 0.16, LWQN = 0.24, LWDL = 0.17, LWCS = 0.43,



Lemna max = 4.23, and n = 4


CI = 0.08

Now, Consistency Ratio (CR) = CI / RI



iii. Pairwise Comparison Matrices for the Criteria- Human Hair Bricks (HHB)

Table No. 6: Pairwise comparison matrices for the Criteria-Human hair bricks

Criteria Quality Control (QC) Quantity (QN) Delivery (DL) Cost (CS)

Quality Control

(QC) 1.00 1.00 1.00 1.00

Quantity (QN) 1.00 1.00 2.00 2.00

Delivery (DL) 1.00 1.00 1.00 1.00

Cost (CS) 1.00 0.50 1.00 1.00

TOTAL 4.00 3.50 5.00 5.00

Table No. 7: Normalised Matrices for the Criteria-Human Hair Bricks


(QC)

Quantity

(QN)

Delivery

(DL) Cost (CS)

Row

average

Quality Control

(QC) 0.25 0.29 0.20 0.20 0.23

Quantity (QN) 0.25 0.29 0.40 0.40 0.33

Delivery (DL) 0.25 0.29 0.20 0.20 0.23

Cost (CS) 0.25 0.14 0.20 0.20 0.20

TOTAL 1.00 1.00 1.00 1.00 1.00







CI = 0.02






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iv. Pairwise Comparison Matrices for the Criteria- Fly ash (FAL-G) Bricks (FAB)

Table No. 8: Pairwise Comparison matrices for the Criteria - Fly Ash (FAL-G) Bricks (FAB)




Quantity (QN) 1.00 1.00 2.00 1.00

Delivery (DL) 1.00 0.50 1.00 2.00

Cost (CS) 1.00 1.00 0.50 1.00

TOTAL 4.00 3.50 4.50 5.00

Now, Normalised matrices are found by dividing each component of matrices by appropriate column

sum.

Table No. 9: Normalised Matrices for the Criteria-Fly Ash (FAL-G) Bricks [FAB]


(QC) Quantity (QN)

Delivery

(DL) Cost (CS) Row average


Quantity (QN) 0.25 0.29 0.44 0.20 0.30

Delivery (DL) 0.25 0.14 0.22 0.40 0.25

Cost (CS) 0.25 0.29 0.11 0.20 0.21

TOTAL 1.00 1.00 1.00 1.00 1.00







CI = 0.06




v. Pairwise Comparison Matrices for the Criteria - Sugarcane Bassage Ash Bricks (SBAB)

Table No. 10: Pairwise Comparison matrices for the Criteria – Sugarcane Bassage Ash Bricks

(SBAB)




Quantity (QN) 1.00 1.00 1.00 1.00

Delivery (DL) 0.50 1.00 1.00 1.00

Cost (CS) 1.00 1.00 1.00 1.00

TOTAL 3.50 4.00 5.00 4.00



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Table No. 11: Normalised matrices for the Criteria – Sugarcane Bassage Ash Bricks (SBAB)


(QC)

Quantity

(QN)

Delivery

(DL)

Cost

(CS)

Row

average


Quantity (QN) 0.29 0.25 0.20 0.25 0.25

Delivery (DL) 0.14 0.25 0.20 0.25 0.21

Cost (CS) 0.29 0.25 0.20 0.25 0.25

TOTAL 1.00 1.00 1.00 1.00 1.00







CI = 0.02




vi. Overall Global Weight Of The Criteria Of The Case Study

Table No. 12: Overall Global Weight of the Criteria

SR.

NO. DESCRIPTION SUB CRITERIAS R1 R2 R3 R4 GMM

1.

Main Criteria

Clay bricks 0.0956 0.1253 0.0809 0.0600 0.0798

Human hair bricks 0.1030 0.1000 0.1000 0.1000 0.0932

Fly ash (FAL - G) bricks 0.5038 0.4193 0.4675 0.4742 0.4576


bricks 0.5028 0.3485 0.3257 0.3543 0.3695

2.

Clay bricks

Quality 0.1641 0.3944 0.4476 0.2470 0.3045

Quantity 0.2367 0.2389 0.1565 0.2887 0.2385

Delivery 0.1721 0.1972 0.1000 0.1756 0.1699

Cost 0.4271 0.1694 0.2673 0.2887 0.2870

3.

Human hair

bricks

Quality 0.2464 0.1614 0.2200 0.3000 0.2382

Quantity 0.2964 0.3035 0.3400 0.3000 0.3214

Delivery 0.2464 0.2480 0.2339 0.1964 0.2421

Cost 0.2107 0.2872 0.2000 0.1000 0.1984

4.

Fly ash (FAL - G)

bricks

Quality 0.2395 0.2470 0.2964 0.2875 0.2687

Quantity 0.2950 0.2887 0.2464 0.2375 0.2680

Delivery 0.2538 0.2887 0.2000 0.2375 0.2451

Cost 0.2117 0.1756 0.2464 0.2375 0.2182

5.

Sugarcane

bassage ash

bricks

Quality 0.2964 0.2950 0.2396 0.2417 0.2727

Quantity 0.2464 0.2000 0.4063 0.1917 0.2549

Delivery 0.2107 0.2395 0.1771 0.2417 0.2215

Cost 0.2464 0.2538 0.1771 0.3250 0.2509



123

vii. LOCAL AND GLOBAL WEIGHT OF THE CRITERIA

Table No. 13: Composite priority weights for ‘Main Criteria – Sub Criteria of Bricks in Indian

context

SN. CRITERIA LOCAL

WEIGHTS SUB CRITERIA

LOCAL

WEIGHTS

GLOBAL

WEIGHTS RANK

1. Clay bricks 0.0798

Quality 0.3045 0.0243 10

Quantity 0.2385 0.0190 14

Delivery 0.1699 0.0136 16

Cost 0.2870 0.0229 11

2. Human hair

bricks 0.0932

Quality 0.2382 0.0222 13

Quantity 0.3214 0.0299 9

Delivery 0.2421 0.0225 12

Cost 0.1984 0.0185 15

3. Fly ash bricks 0.4576

Quality 0.2687 0.1230 1

Quantity 0.2680 0.1226 2

Delivery 0.2451 0.1122 3

Cost 0.2182 0.0999 5

4.

Sugarcane

bassage ash

bricks

0.3695

Quality 0.2727 0.1008 4

Quantity 0.2549 0.0942 6

Delivery 0.2215 0.0819 8

Cost 0.2509 0.0927 7

TOTAL 1.0000

viii. Bricks Manufacturers Overall Ranking

Table No. 14: Summarizes of priority weights of each alternative of Bricks selection

Bricks Selection Criteria Global

weights

Brick Manufacturer 1 Brick Manufacturer 2 Brick Manufacturer 3 Brick Manufacturer

4

Local

weights

Global

weights

Local

weights

Global

weights

Local

weights

Global

weights

Local

weights

Global

weights

Clay

bricks

Quality 0.0243 0.1641 0.0040 0.3944 0.0096 0.4476 0.0109 0.2470 0.0060

Quantity 0.0190 0.2367 0.0045 0.2389 0.0045 0.1565 0.0030 0.2887 0.0055

Delivery 0.0136 0.1721 0.0023 0.1972 0.0027 0.1000 0.0014 0.1756 0.0024

Cost 0.0229 0.4271 0.0098 0.1694 0.0039 0.2673 0.0061 0.2887 0.0066

Human

hair

bricks

Quality 0.0222 0.2464 0.0055 0.1614 0.0036 0.2200 0.0049 0.3000 0.0067

Quantity 0.0299 0.2964 0.0089 0.3035 0.0091 0.3400 0.0102 0.3000 0.0090

Delivery 0.0225 0.2464 0.0056 0.2480 0.0056 0.2339 0.0053 0.1964 0.0044

Cost 0.0185 0.2107 0.0039 0.2872 0.0053 0.2000 0.0037 0.1000 0.0018

Fly ash

(FAL -

G) bricks

Quality 0.1230 0.2395 0.0294 0.2470 0.0304 0.2964 0.0365 0.2875 0.0354

Quantity 0.1226 0.2950 0.0362 0.2887 0.0354 0.2464 0.0302 0.2375 0.0291

Delivery 0.1122 0.2538 0.0285 0.2887 0.0324 0.2000 0.0224 0.2375 0.0266

Cost 0.0999 0.2117 0.0211 0.1756 0.0175 0.2464 0.0246 0.2375 0.0237

Sugarca

ne

bassage

ash

bricks

Quality 0.1008 0.2964 0.0299 0.2950 0.0297 0.2396 0.0241 0.2417 0.0244

Quantity 0.0942 0.2464 0.0232 0.2000 0.0188 0.4063 0.0383 0.1917 0.0180

Delivery 0.0819 0.2107 0.0172 0.2395 0.0196 0.1771 0.0145 0.2417 0.0198

Cost 0.0927 0.2464 0.0228 0.2538 0.0235 0.1771 0.0164 0.3250 0.0301

Total scores 1.0000 0.2528 0.2516 0.2524 0.2495

Rank 1st 3rd 2nd 4th



124

CONCLUSIONS

From this research work, following conclusion are drawn � The main contribution of the work was the identification of the important criteria for the bricks

selection (above case study). Then a multi-criteria decision model for evaluating and selecting a

bricks manufacturer was developed. The model for bricks manufacturer evaluation and selection

was developed using the AHP method. The AHP model is assessing decision-makers to identify

and evaluate the bricks manufacturer selection.

� Finally, the developed model is tested on four bricks manufacturer selection problems. The

results show the models are able to assist decision-makers to examine the strengths and

weaknesses of bricks manufacturer selection by comparing them with appropriate main criteria

and sub-criteria.

� The developed model has not been implemented yet. It is just tested on four bricks manufacturer

selection problems as mentioned, but the outcome implies that the quality of fly ash (FAL-G)

bricks criterion has the majority weight among other criteria.

� A case study of bricks selection based on AHP approach can be applied to four types of selected

bricks which are made of industrial waste such as Fly ash (FAL-G) bricks, Sugarcane Bassage

ash bricks, Human hair bricks, Clay bricks.

� Present Approach of bricks selection in construction projects has certain shortcomings and it is

required to improve by application of scientific technique. Present approach does not consider

multiple objectives, Present approach does not collect sufficient data to evaluate bricks selection.

Therefore, Analytical Hierarchy Process (AHP) was suggested and applied due to its

applicability to the shortcomings.

� According to the Analytical Hierarchy Process (AHP), development of the Criteria Framework

in Indian context is prepared for a case study of bricks selection. Total 4 nos. of sub-criteria’s

are identified for each type of bricks typically which are Quality, Quantity, Delivery and Cost

which affect the bricks selection problem. Main Criteria for bricks selection are: Fly ash (FAL-

G) bricks, Sugarcane bassage ash bricks, Human hair bricks, Clay bricks.

� For above mentioned case study of brick selection, 4 different bricks manufacturers were

evaluated through AHP based approach. There is found that Bricks Manufacturer No. 1 is best,

Customer can be placed order for fly ash bricks because of top three criteria of fly ash bricks are

Quality, Quantity, Delivery which weights are highest in descending order and affects the bricks

selection and cost of fly ash (FAL-G) bricks is on 5th

rank therefore there can be an

improvement in the decision for fly ash bricks selection for profit maximization and cost

optimization.

� By using Analytic Hierarchy Process (AHP) complete ranking with scores can be applied on

selected criteria.

� With the help of Analytic Hierarchy Process (AHP) further research work can be carried out on

Ready Mixed Concrete selection as per case study.

� The proposed methodology can also be applied to any other selection problem involving

multiple and conflicting criteria.

ACKNOWLEDGEMENT

The Authors thankfully acknowledge to Dr. C. L. Patel, Chairman, Charutar Vidya Mandal,

and Er. V. M. Patel, Hon. Jt. Secretary, Charutar Vidya Mandal, Dr. F. S. Umrigar, Principal, B.V.M.

Engineering College, Prof. J. J. Bhavsar, Associate professor and coordinator PG (Construction

Engineering & Management), Civil Engineering Department, B.V.M Engineering College, Er.

Yatinbhai Desai, Jay Maharaj Construction, Vallabh Vidyanagar, Gujarat, India for their motivations

and infrastructural support to carry out this research.



125

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126

AUTHOR’S BIOGRAPHY

Ashish Harendrabhai Makwana was born in 1988 in Jamnagar District,

Gujarat. He received his Bachelor of Engineering degree in Civil Engineering

from the Charotar Institute of Science and technology in Changa, Gujarat

Technological University in 2012. At present he is Final year student of Master`s

Degree in Construction Engineering and Management from Birla Vishwakarma

Mahavidyalaya, Gujarat Technological University. He has papers published in

international journals.

Prof. Jayeshkumar R. Pitroda was born in 1977 in Vadodara City. He

received his Bachelor of Engineering degree in Civil Engineering from the Birla

Vishvakarma Mahavidyalaya, Sardar Patel University in 2000. In 2009 he

received his Master's Degree in Construction Engineering and Management from

Birla Vishvakarma Mahavidyalaya, Sardar Patel University. He joined Birla

Vishvakarma Mahavidyalaya Engineering College as a faculty where he is

Assistant Professor of Civil Engineering Department with a total experience of

12 years in the field of Research, Designing and education. He is guiding M.E.

(Construction Engineering & Management) Thesis work in the field of Civil/ Construction

Engineering. He has published papers in National Conferences and International Journals.

10120130405014

Business

ready mixed concrete

supply of ready mixed

concrete production

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ready mixed supplier

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condition ready