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10120130405014
10120130405014
10120130405014
10120130405014
10120130405014
10120130405014
10120130405014
10120130405014
10120130405014
10120130405014
10120130405014
10120130405014
10120130405014
10120130405014
10120130405014
10120130405014
10120130405014
10120130405014
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10120130405014

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  • 1. International Journal of Management (IJM), ISSN 0976 – MANAGEMENT (IJM) INTERNATIONAL JOURNAL OF 6502(Print), ISSN 0976 - 6510(Online), Volume 4, Issue 5, September - October (2013) ISSN 0976-6502 (Print) ISSN 0976-6510 (Online) Volume 4, Issue 5, September - October (2013), pp. 109-126 © IAEME: www.iaeme.com/ijm.asp Journal Impact Factor (2013): 6.9071 (Calculated by GISI) www.jifactor.com IJM ©IAEME READY MIXED CONCRETE SELECTION FOR INFRASTRUCTURE DEVELOPMENT THROUGH ANALYTIC HIERARCHY PROCESS (AHP) IN THE NEW MILLENNIUM Ashish H. Makwana1, Prof. Jayeshkumar Pitroda2 1 Student 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 readymixed 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. 109
  • 2. International Journal of Management (IJM), ISSN 0976 – 6502(Print), ISSN 0976 - 6510(Online), Volume 4, Issue 5, September - October (2013) 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] 110
  • 3. International Journal of Management (IJM), ISSN 0976 – 6502(Print), ISSN 0976 - 6510(Online), Volume 4, Issue 5, September - October (2013) 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 111
  • 4. International Journal of Management (IJM), ISSN 0976 – 6502(Print), ISSN 0976 - 6510(Online), Volume 4, Issue 5, September - October (2013) 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. 112
  • 5. International Journal of Management (IJM), ISSN 0976 – 6502(Print), ISSN 0976 - 6510(Online), Volume 4, Issue 5, September - October (2013) 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. 113
  • 6. International Journal of Management (IJM), ISSN 0976 – 6502(Print), ISSN 0976 - 6510(Online), Volume 4, Issue 5, September - October (2013) 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. 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 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 subcriteria’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. 114
  • 7. International Journal of Management (IJM), ISSN 0976 – 6502(Print), ISSN 0976 - 6510(Online), Volume 4, Issue 5, September - October (2013) 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. 115
  • 8. International Journal of Management (IJM), ISSN 0976 – 6502(Print), ISSN 0976 - 6510(Online), Volume 4, Issue 5, September - October (2013) 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 1 Equal Importance 2 Weak or slight 3 Moderate importance 4 Moderate plus 5 Strong importance 6 Strong plus 7 Very strong or Demonstrated importance 8 Very, very strong 9 Extreme importance RESIPROCALS OF ABOVE (1-9) If activity i has one of the above nonzero numbers assigned to it when compared with activity j, then j has the reciprocal value when compared with i A reasonable assumption 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. 1.1–1.9 EXPLATION Two activities contribute equally to the objective Experience and judgement slightly favour one activity over another Experience and judgement strongly favour one activity over another An activity is favoured very strongly over another; its dominance demonstrated in practice The evidence favouring one activity over another is of the highest possible order of affirmation (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. 116
  • 9. International Journal of Management (IJM), ISSN 0976 – 6502(Print), ISSN 0976 - 6510(Online), Volume 4, Issue 5, September - October (2013) Benchmarking - Comparing the processes in one’s own organization with those of other bestof-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) 117
  • 10. International Journal of Management (IJM), ISSN 0976 – 6502(Print), ISSN 0976 - 6510(Online), Volume 4, Issue 5, September - October (2013) 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 118
  • 11. International Journal of Management (IJM), ISSN 0976 – 6502(Print), ISSN 0976 - 6510(Online), Volume 4, Issue 5, September - October (2013) 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 1.00 1.00 Fly ash (FAL - G) bricks 0.25 0.25 Sugarcane bassage ash bricks 0.20 0.33 4.00 4.00 1.00 3.00 5.00 3.00 0.33 1.00 11.00 9.00 1.83 4.53 Criteria Clay bricks Human hair bricks Clay bricks Human hair bricks Fly ash (FAL - G) bricks Sugarcane bassage ash bricks TOTAL 1.00 1.00 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) TOTAL Clay bricks (CB) Human hair bricks (HHB) Fly ash (FAL G) bricks (FAB) 0.09 0.11 0.14 Sugarcane bassage ash bricks (SBAB) 0.04 0.09 0.11 0.14 0.07 0.10 0.36 0.44 0.55 0.66 0.50 0.45 0.33 0.18 0.22 0.30 1.00 1.00 1.00 1.00 1.00 Row average 0.10 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) TOTAL Quality Control (QC) 1.00 1.00 1.00 4.00 7.00 Quantity (QN) Delivery (DL) 1.00 1.00 1.00 1.00 4.00 1.00 1.00 1.00 3.00 6.00 119 Cost (CS) 0.25 1.00 0.33 1.00 2.58
  • 12. International Journal of Management (IJM), ISSN 0976 – 6502(Print), ISSN 0976 - 6510(Online), Volume 4, Issue 5, September - October (2013) Table No. 5: Normalised Matrices for the Criteria-Clay bricks Criteria Quality Control (QC) Quality Control (QC) Quantity (QN) Delivery (DL) Cost (CS) TOTAL 0.14 0.14 0.14 0.57 1.00 Delivery (DL) 0.17 0.17 0.17 0.50 1.00 Quantity (QN) 0.25 0.25 0.25 0.25 1.00 Cost (CS) Row average 0.10 0.39 0.13 0.39 1.00 0.16 0.24 0.17 0.43 1.00 Therefore, local weights of the criteria’s are as follows. LWQC = 0.16, LWQN = 0.24, LWDL = 0.17, LWCS = 0.43, Now, check the consistency of the result. Lemna max. = sum of [Wi * sum of each column] Lemna max = 4.23, and n = 4 Now, find Consistency index (CI) = {Lemna max - n} / (n - 1) CI = 0.08 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) 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) TOTAL Quality Control (QC) Quantity (QN) Delivery (DL) Cost (CS) 1.00 1.00 1.00 1.00 1.00 1.00 1.00 4.00 1.00 1.00 0.50 3.50 2.00 1.00 1.00 5.00 2.00 1.00 1.00 5.00 Table No. 7: Normalised Matrices for the Criteria-Human Hair Bricks Criteria Quality Control (QC) Quantity (QN) Delivery (DL) Cost (CS) TOTAL Quality Control (QC) Quantity (QN) Delivery (DL) Cost (CS) Row average 0.25 0.29 0.20 0.20 0.23 0.25 0.25 0.25 1.00 0.29 0.29 0.14 1.00 0.40 0.20 0.20 1.00 0.40 0.20 0.20 1.00 0.33 0.23 0.20 1.00 Therefore, local weights of the criteria’s are as follows. LWQC = 0.23, LWQN = 0.33, LWDL = 0.23, LWCS = 0.20, Now, check the consistency of the result. Lemna max. = sum of [Wi * sum of each column] Lemna max. = 4.06, and n = 4 Now, find Consistency index (CI) = {Lemna max - n} / (n - 1) CI = 0.02 Now, Consistency Ratio (CR) = CI / RI Where, RI (Random Index) = 0.90 (for n = 4), CR = 0.02 < 0.1 hence OK. (According to T. Satty – the founder of the AHP method) 120
  • 13. International Journal of Management (IJM), ISSN 0976 – 6502(Print), ISSN 0976 - 6510(Online), Volume 4, Issue 5, September - October (2013) 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) Quality Control (QC) Quality Control (QC) 1.00 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 Criteria Quantity (QN) Delivery (DL) Cost (CS) 1.00 1.00 1.00 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] Criteria Quality Control (QC) Quantity (QN) Delivery (DL) Cost (CS) Row average Quality Control (QC) 0.25 0.29 0.22 0.20 0.24 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 Therefore, local weights of the criteria’s are as follows. LWQC = 0.23, LWQN = 0.33, LWDL = 0.23, LWCS = 0.20, Now, check the consistency of the result. Lemna max. = sum of [Wi * sum of each column] Lemna max. = 4.19, and n = 4 Now, find Consistency index (CI) = {Lemna max - n} / (n - 1) CI = 0.06 Now, Consistency Ratio (CR) = CI / RI Where, RI (Random Index) = 0.90 (for n = 4), CR = 0.07 < 0.1 hence OK. (According to T. Satty – the founder of the AHP method) 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) Criteria Quality Control (QC) Quantity (QN) Delivery (DL) Quality Control (QC) 1.00 1.00 2.00 1.00 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 4.00 121 Cost (CS)
  • 14. International Journal of Management (IJM), ISSN 0976 – 6502(Print), ISSN 0976 - 6510(Online), Volume 4, Issue 5, September - October (2013) Table No. 11: Normalised matrices for the Criteria – Sugarcane Bassage Ash Bricks (SBAB) Criteria Quality Control (QC) Quantity (QN) Delivery (DL) Cost (CS) TOTAL Quality Control (QC) 0.29 0.29 0.14 0.29 1.00 Quantity (QN) 0.25 0.25 0.25 0.25 1.00 Delivery (DL) 0.40 0.20 0.20 0.20 1.00 Cost (CS) 0.25 0.25 0.25 0.25 1.00 Row average 0.30 0.25 0.21 0.25 1.00 Therefore, local weights of the criteria’s are as follows. LWQC = 0.30, LWQN = 0.25, LWDL = 0.21, LWCS = 0.25, Now, check the consistency of the result. Lemna max. = sum of [Wi * sum of each column] Lemna max. = 4.06, and n = 4 Now, find Consistency index (CI) = {Lemna max - n} / (n - 1) CI = 0.02 Now, Consistency Ratio (CR) = CI / RI Where, RI (Random Index) = 0.90 (for n = 4), CR = 0.02 < 0.1 hence OK. (According to T. Satty – the founder of the AHP method) 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 Clay bricks 5. Sugarcane bassage ash bricks 0.5038 0.4193 0.4675 0.4742 0.4576 0.5028 0.3485 0.3257 0.3543 0.3695 0.1641 0.3944 0.4476 0.2470 0.3045 0.2367 0.2389 0.1565 0.2887 0.2385 Delivery 0.1721 0.1972 0.1000 0.1756 0.1699 0.4271 0.1694 0.2673 0.2887 0.2870 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 0.2107 0.2872 0.2000 0.1000 0.1984 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 Fly ash (FAL - G) bricks Fly ash (FAL - G) bricks Sugarcane bassage ash bricks Quality 4. 0.0932 Cost Human hair bricks 0.0798 0.1000 Quality 3. 0.0600 0.1000 Cost Clay bricks 0.0809 0.1000 Quantity 2. Main Criteria 0.1253 0.1030 Quality 1. 0.0956 Human hair bricks 0.2117 0.1756 0.2464 0.2375 0.2182 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 122
  • 15. International Journal of Management (IJM), ISSN 0976 – 6502(Print), ISSN 0976 - 6510(Online), Volume 4, Issue 5, September - October (2013) 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 Quality 1. Clay bricks 0.0243 10 0.2385 0.0190 14 Delivery 0.0798 0.3045 Quantity 0.1699 0.0136 16 Cost 11 0.0222 13 Quantity 0.3214 0.0299 9 Delivery 0.0932 0.0229 0.2382 0.2421 0.0225 12 Cost Human hair bricks 2. 0.2870 Quality 0.1984 0.0185 15 Quality Sugarcane bassage ash bricks 4. 0.0999 0.2727 0.1008 4 0.2549 0.0942 6 Delivery 0.3695 0.2182 2 3 5 Quantity 0.4576 1 0.1226 0.1122 0.2215 0.0819 8 Cost Fly ash bricks 0.1230 0.2680 0.2451 Quality 3. 0.2687 Quantity Delivery Cost 0.2509 0.0927 7 TOTAL viii. 1.0000 Bricks Manufacturers Overall Ranking Table No. 14: Summarizes of priority weights of each alternative of Bricks selection Bricks Selection Criteria Global weights Local weights Global weights Local weights Global weights Local weights Global weights Brick Manufacturer 4 Local Global weights weights Brick Manufacturer 1 Brick Manufacturer 2 Brick Manufacturer 3 Quality Clay bricks 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 0.1694 0.0039 0.2673 0.0061 0.2887 0.0066 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 0.0185 0.2107 0.0039 0.2872 0.0053 0.2000 0.0037 0.1000 0.0018 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 Sugarca ne bassage ash bricks 0.0098 0.2464 Quality Fly ash (FAL G) bricks 0.4271 0.0222 Cost Human hair bricks 0.0229 Quality 0.0999 0.2117 0.0211 0.1756 0.0175 0.2464 0.0246 0.2375 0.0237 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 Rank 1.0000 0.2528 0.2516 1st 3rd 123 0.2524 2nd 0.2495 4th
  • 16. International Journal of Management (IJM), ISSN 0976 – 6502(Print), ISSN 0976 - 6510(Online), Volume 4, Issue 5, September - October (2013) 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 (FALG) 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. 124
  • 17. International Journal of Management (IJM), ISSN 0976 – 6502(Print), ISSN 0976 - 6510(Online), Volume 4, Issue 5, September - October (2013) REFERENCES [1] Analytic hierarchy process, Wikipedia, the freeencyclopedia http://en.wikipedia.org/wiki/Analytic_hierarchy_process [2] Ashish H. Makwana1, Prof. Jayeshkumar Pitroda2, “An Approach for Ready Mixed Concrete Selection for Construction Companies through Analytic Hierarchy Process”, International Journal of Engineering Trends and Technology (IJETT), ISSN: 2231-5381, Volume-4, Issue-7, July 2013, Pg. 2878 - 2884. [3] M.S. SHETTY, Concrete Technology, Theory and Practice, S.Chand- New Delhi. [4] A.R.Santhkumar, Concrete Technology, chapter 16 – READY MIXED CONCRETE, Oxford higher education [5] Chang, K.F, C.M. Chiang and P.C. Chou, 2007, “Adapting aspects of GBTool 2005 - searching for suitability in Taiwan, Building and Environment”, 42: 310-316. [6] Chang, K.F., P.C. Chou, C.M. Chiang and I.C, Chen, 2005. “The revised version of the GBTool for subtropical Taiwan - from the barrier to success,” In: Proceeding of the 2005 world sustainable building conference (SB05Tokyo), Tokyo, pp: 1792-7. [7] Dweiri, F. and F.M. Al-Oqla, 2006, “Material selection using Analytic Hierarchy Process”, International J. Computer Applications in Technol"., 26(4): 182-189. [8] Evangelos Triantaphyllou – “Multi-Criteria Decision Making Methods: A Comparative Study (Applied Optimization, Volume 44)”, ISBN 978-1-4419-4838-0, ISBN 978-1-4757-3157-6 (eBook), DOI 10.1007/978-1-4757-3157-6, SPRINGER-SCIENCE+BUSINESS MEDIA B.V. [9] Forman, E. and K. Peniwati, 1998, “Aggregating individual judgments and priorities with the Analytic Hierarchy Process”, European J. Operational Res., 108: 165-169. [10] IS 4926 - 2003, Indian Standard, Ready mixed concrete – Code of Practice (Second Revision), BIS, New Delhi. [11] Lee, G.K.L. and E.H.W. Chatt, 2008, “The Analytic Hierarchy Process (AHP) approach for assessment of urban renewal proposals”, Soc. Indi. Res., 89: 155-168. [12] Navneet Bhushan and Kanwal Rai – “Strategic Decision Making - Applying the Analytic Hierarchy Process”, ISBN 1-85233-756-7, © Springer-Verlag London Limited 2004, Springer. [13] Pavlikakis, G.E. and V.A. Tsihrintzis, 2003, “A quantitative method for accounting human opinion, preferences and perceptions in ecosystem management”, J. Environmental Management, 68: 193-205. [14] Rigopoulos, G., J. Psarras and A. Dimitrios, 2008, “Web support system for group collaborative decisions”, J.Applied Sci., 8: 407-419. [15] Saaty, T.L. (2008), “Decision making with the analytic hierarchy process”, Int. J. Services Sciences, Vol.1, No.1, pp.83–98 [16] Saaty, T.L., 1980, “The Analytic Hierarchy Process: Planning, Priority Setting, Resource Allocation”, 1st edition, Mcgraw-Hill, New York, ISBN: 0070543712, Alibris ID: 9503413947. [17] Taleai, M. and A. Mansourian, 2008, “Using Delphi-AHP method to survey major factors causing urbah plan implementation failure”, J. Applied Sci., 8(15): 2746-2751. [18] T. Saaty, "A Scaling Method for Priorities in Hierarchical Structures," Journal of Mathematical Psychology, 15, 234-281 (1977). [19] Vaidya, O. and S. Kumar, 2006, “Analytic Hierarchy Process: An overview of applications”, European J. Operational Res., 169: 1-29. [20] Yaser N. Alsuwehri, “Supplier Evaluation and Selection by Using The Analytic Hierarchy Process Approach”, Engineering Management Field Project, Masters of Science, the Graduate School of The University of Kansas. [21] S Parul Gupta and R.K. Srivastava, “Analysis of Customer Satisfaction in Hotel Service Quality using Analytic Hierarchy Process (AHP)”, International Journal of Industrial Engineering Research and Development (IJIERD), Volume 2, Issue 1, 2011, pp. 59 - 68, ISSN Online: 0976 - 6979, ISSN Print: 0976 – 6987. [22] Rajnish Katarne and Dr. Jayant Negi, “Determination of Importance of Criteria: Analytic Hierarchy Process (AHP) in Technological Evolution of Automobile Steering”, International Journal of Industrial Engineering Research and Development (IJIERD), Volume 4, Issue 1, 2013, pp. 10 - 18, ISSN Online: 0976 - 6979, ISSN Print: 0976 – 6987. 125
  • 18. International Journal of Management (IJM), ISSN 0976 – 6502(Print), ISSN 0976 - 6510(Online), Volume 4, Issue 5, September - October (2013) 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. 126

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