Ramesh Pandi R *1, Rajesh S *2, Pothinathan S.K.M *3 123* Department of civil engineering, Kalasalingam University,

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1 Planning and Controlling of Materials Waste in Building Construction - A Regression & Correlation Analysis Ramesh Pandi R *1, Rajesh S *2, Pothinathan S.K.M *3 123* Department of civil engineering, Kalasalingam University, Krishnankoil, Tamilnadu, India Abstract: Past research into the causes of waste in construction projects indicate that waste can arise at any stage of the construction process. Waste minimization and management on construction project will help and reduce the significant quantities of construction waste. The efficient procurement of quality of materials represents a key role in the successful completion of the work. Poor planning and control of material, lack of material when needed, improper record keeping, excess handling of materials, improper storage, poor workmanship, lake of site maintains, rework, and occurrence of theft are all cause losses in productivity. That can indirectly increase total project costs and materials waste. Effective management of materials can reduce the project costs and minimize the materials waste. The excessive wastage of materials, improper management on-site and low awareness of the need for waste reduction are common in the local construction sites in India. The aim of this paper identifying the main sources and causes of materials waste especially cement and steel on construction sites arising from improper storage, excess handling, poor workmanship, site management, rework, etc., of high waste generating in the building construction projects. The aim of the study is to advance knowledge on construction site waste minimization through the application of wastage reducing principles. The objectives of the study of identification of sources and causes of material wastes on construction sites, assessment of level of knowledge of the concept among construction contractors and identification of barriers to successful implementation of project. The main tools for the collection of data included questionnaires, interviews and site observations. The factor which had major effect on the material waste were identified and to be analyzed using SPSS 16 (Statistical package for social sciences version16) software. Statistical package for social scientists was employed to analyze data obtained. Mean score rankings were adopted to analyze data on sources and causes of materials waste respectively. Then we can use Correlation and Regression analyses to wastage causing various factors and compare the results using mathematical model. By using these identification source and causes, construction works may become conscious of how the waste is generated and how this can avoid. It will give the great benefit for not only the construction industry but also the country in terms of economic and social protection of the environment. Keywords: Wastage minimization, cement, Reinforcement steel,correlation, regression, construction materials, materials waste, ranking. I. INTRODUCTION This research is focused on waste minimization in construction that influences the economic. Besides that this study is also intended to identify methods to reduce the waste in the construction site. In this chapter the basic elements of study are presented. Basically this chapter covers the problem statement, aims and objectives, scope of the study, and significance of the study. The product of waste which occurs at every step of the construction activities and practices on site will be taken seriously because it s affecting and big problem to the environment. Waste generated by construction operations need to be taken seriously because construction industry contributes a significant waste to the overall waste volume in a country. This waste if minimized will help not only in reduction of project cost but also benefits the environment. In addition to the need to be a well-informed society on waste, it is necessary to effectively communicate and develop adequate understanding on waste minimization. Now waste management is necessary. Generally, the materials cost contributes to about 40% of the total project cost of which cement and steel account for 60% of the cost. Hence it is necessary to curb wastages in this area to have control over the economy of the project cost. It is observed that, 5-10 percent of construction material end up as waste on construction sites III. LITERATURE REVIEW A. Objectives of Material Management Material management system can bring following objectives Efficient material planning Buying or Purchasing Procuring and Receiving Storing and Inventory Control Supply and distribution of material Quality and assurance Improved efficiency Good supplier relationship To fulfill all these objectives, it is necessary to establish a good coordination between all the employees of material management department B. Benefits of Material Management An effective material management system can bring following benefits

2 Reducing the overall costs of material Better handling of material Reduction in duplicated orders Material is on site when needed and in the quantities required Improvements in labor productivity Improvements in project schedule Quality control Better field material control Better relations with suppliers C. Process of Material Management Material management process initiates from need generated from site then this information conveyed to store department and material is ordered in the store, indent is generated. Vendor selection is to be carried out for the least value and best items. Materials are received at store department and inspection is carried out. FINDINGS AND DISCUSSION The summary of information gathered is represented from Table I to Table IV S. No. Table I: Actual Wastage in Cement (in bags): Description Cement Theoretic al Qty. (in bags) Cement Executed Qty. (in bags) Excess (in bags) Excess (in %) 1 Footing Plinth beam Column Slab and beam Lift raft Lift Pardi Aim, Objective and Scope of The Study Questionanaires Interview Analysis Data in Spss Software IV. METHODOLOGY This chapter describes the research method adopted in this study. It discusses the design of the survey questionnaire and the selection of sample respondents for the questionnaire survey. The statistical tools for the data analysis are also discussed. This section describes the research process from start to end. The section explains the step by step methodology that was used in order to answer the research questions. The objectives and scope were determined in collaboration with departmental Engineers, supervisors and the building construction organizations currently involved in construction activities in and around the site. Literature review was performed in parallel with the data collection in order to develop a theoretical background connected to the research topic. Finally, the data was analyzed, discussed and conclusions and recommendations were drawn. Factor Indecate to waste in construction site Collection of Data and Site Obsevation Discussion of Result Conclusions Table II: Ratings Given As Per a 10 Point Scale for the Questionnaire Survey for Cement Wastage Table III: Actual Wastage in steel (MT): Sr. No. Descri p-tion Steel Theor etical Qty. (in MT) Steel Execut ed Qty. (inmt) Exces s (in MT) Exces s (in %) 1 8mm mm mm mm mm mm Sr. No. Wa stage (%) DC (1) ST (2) MH (3) RM (4) PW (5) PC (6) P (7)

3 VI. INTERPRETATION FOR CORRELATION Table IV: Ratings given on 10 Point Scale based on questionnaire survey for steel wastage S. No. Wastage (in %) DC (1) PW (2) CP (3) SM (4) SS (5) V (6) RM (7) Using the input data given in Table II, the correlations are given as follows: 1. Correlation between wastage in cement and design changes (DC) r = i.e. correlation is positive and very week among wastage in cement and design changes factor. 2. Correlation between wastage in cement and storage (ST) r = i.e. correlation is positive and medium strong among wastage in cement and storage factor. 3. Correlation between wastage in cement and material handling (MH) r = i.e. correlation is positive and medium strong among wastage in cement and material handling factor 4. Correlation between wastage in cement and Record keeping Mistake (RM) r = i.e. correlation is positive and medium strong among wastage in cement and Recordkeeping mistake factor 5. Correlation between wastage in cement and poor workman-ship (PW) r = i.e. correlation is positive and very strong among wast-age in cement and poor workmanship factor. 6. Correlation between wastage in cement and planning and controlling (PC) r = i.e. correlation is positive and week among wastage in cement and planning and controlling factor. 7. Correlation between wastage in cement and Procurement error (P) r = i.e. correlation is positive and medium strong among wastage in cement and Procurement error factor. Poor workmanship has strong positive corre-lation with wastage in cement (r = 0.860) and design changes has very week correlation with wastage in cement. (r = 0.038). A. Correlations analysis using spss16: Correlation for wastage in steel using the input data from Table IV for SPSS 16 software, follow-ing correlation observed between various factors and wastage in steel. Table VI: SPSS16 Output for Correlation between Wastage of steel and poor workmanship (PM): Poor Wastage Workmanship Wastage - Persons Correlation Sig. (2-tailed) N 6 6 Poor workmanship- Persons Correlation Sig. (2-tailed) N 6 6 Using the input data given in Table IV, the correlations are given as follows: 1. Correlation between wastage in steel and design changes (DC): r = i.e. correlation is positive and very week among wastage in steel and design changes factor. 2. Correlation between wastage in steel and poor workmanship (PW): r = i.e. correlation is positive and very strong among wast-age in steel and poor workmanship factor. 3. Correlation between wastage in steel and Cutting un economical pieces(cp): r = i.e. correlation is positive and medium strong among wastage in steel and Cutting uneconomical pieces. 4. Correlation between wastage in steel and site management(sm) r = i.e. correlation is positive and medium strong among wastage in steel and site management factor. 5. Correlation between wastage in steel and short supply(ss): r = i.e. correlation is positive and very week among wastage in steel and short supply factor.

4 6. Correlation between wastage in steel and Vandalism(V) r = i.e. correlation is positive and very week among wastage in steel and Vandalism factor 7. Correlation between wastage in steel and Recordkeeping Mis-take (RM): r = i.e. correlation is negative and very week with very low degree of certainty for wastage in steel and recordkeeping mis- take factor VII. INTERPRETATION FOR REGRESSION Poor workmanship has strong positive corre-lation with wastage in steel (r = 0.838) and record keeping mis-take has negative correlation i.e. very week correlation with wastage in steel. (r=-0.492) B. Regression analysis using spss16: In this analysis equation is formed considering all the factors that affect the dependent variable simultaneously. The ratings taken for analysis are the same as that used in the correlation analysis. 1. Wastage in cement: The data table is same as used in correlation analysis of wastage in cement. Refer Table II. The output from SPSS software is as shown in Table VII. Table VII: SPSS16 Output for Regression analysis of Wastage of cement and other factors: Coefficients Regression equation for wastage in cement is as below: 1. Wastage in steel The data table is same as used in correlation analysis of wastage in steel. Refer Table IV. The output from SPSS software is as shown in Table VIII. Table VIII: SPSS16 Output for Regression analysis of Wastage of steel and other factors: Coefficients Model Constant Design Changes Unstandarized Coef-ficients B Std. Error Standarized Coefficients Beta t Sig Poor Workmanship Site management Vandalism Recordkeepin g mistake Regression equation for wastage in steel is as below: Wastage in cement = (-) (storage) (Record keeping mistake) (Poor workmanship) (Planning and controlling) (Procurement error) VIII. VERIFICATION FOR CORRELATION This equation shows us that Poor workman-ship is a main factor that affects wastage linearly, i.e. as Poor workmanship it affects the wastage in cement times. The factor of Variations in the design while construction is in progress (DC) and material handling (MH) is excluded from this analysis. Verification: From Table VII, wastage for cement is worked out using rating as given for 4th reading that shows maximum value of wastage (8.05) Wastage in cement = 8.05 = (-) *(5) *(2) *(9) *(4) *(5) = 8.05~ 8.05 Hence above equation is verified. Wastage in steel = (-) (Design changes) (Poor workmanship) (-) (site management) (-) (Van-dalism) (-) (Record keeping mistake). IX. VERIFICATION FOR REGRESSION This equation shows us that Poor workmanship is a main factor that affects wastage linearly, i.e. as Poor workmanship it affects the wastage in steel times. The factor cutting into uneconomical pieces (CP) and short Unstandardized standardized Coefficients Coefficients Model t Sig. Std. B Beta Error Constant Storage Recordkeepin g mistake Poor workmanship Planning and con-trolling Procurement Error

5 supply (SS) is excluded from this analysis. Verification: From table VII, wastage for steel is worked out using rating as given for 3rd reading that shows maximum value of wastage (5.29) Wastage in steel = 5.29 = *(1) *(7) *(3) *(4) *(1) = 5.29~ 5.29 Hence above is verified. RESULTS Table XI: Summary of Results obtained by Correlation and Re-gression for Wastage in Cement Factor Variations in design while construc-tion is in progress (DC) Wastage in Cement Correlation Regre ssion Storage (ST) Material Hadling (MH) Recordkeeping Mistakes (RM) Poor Workmanship (PW) Planning and Controlling (PC) Procurement Error (P) Site Management (SM) Short Supply (SS) Vandalism (V) Recordkeeping Mistake (RM) By method of correlation, poor workmanship have strong correlation with cement wastage and other factors such as material handling, storage, recordkeeping mistake and procurement error have medium positive correlation with total cement wastage. In case of regression analysis, poor workmanship identifies as main factors for wastage of cement. Wastage in reinforcement has strong cor-relation with poor workmanship and medium positive correlation with cutting uneconomical pieces, and site management. For regression, poor workmanship identified major factors. Through this analysis, we can say that controlling these factors will give us minimum wastage in cement and reinforcement steel. X. CONCLUSION From the results obtained from the Correlation and Regression Analysis using SPSS16 software, it is concluded that it is possible to obtain the different factors and their contribution in the overall construction wastes. If this methodology is applied, it is quite possible to predict the likely wastages which may occur in the residential project. The Planning Engineer can take adequate steps, in advance, to take care of factors, which have major impact / contribution in overall construction wastes, such poor workman-ship, material handling, storage, record keeping mistake and procurement error and cutting uneconomical shapes. This may vary on account of site conditions on different construction sites / projects. Table XII: Summary of Results obtained by Correlation and Regression for Wastage in Reinforcement Steel. Wastage in Steel Factor Variations in design while construc-tion is in progress (DC) Correlation Regress ion Poor Workmanship (PW) Cutting uneconomical shapes (CP) It gives variation in different weight ages in the coefficients obtained by the Correlation and Regression analysis. However, this will helps the Engineers to concentrate on those factors and plan the works respectively. The limitation to this project is the small dataset as contractors generally unwilling / hesitates to pro-vide data regarding construction material used and actual waste generated during execution of a project on construction site. ACKNOWLEDGMENT I express my profound gratitude to my project guide Prof. Mr.S.Rajesh for her invaluable guidance, encouragement and supervision. It is my sincere feeling of

6 respect to express my gratitude to KALASALINGAM UNIVERSITY,KRISHNANKOVIL for giving me an opportunity to carry out this project. I would like to thank Mr.M.Muthukannan HOD Civil for extending her complete support and encouraging me in every aspect related to project that enabled us to put my best efforts. 9. Kofi Agyekum1, Joshua Ayarkwa1 & Emmanuel Adin-yira1, Consultants Perspectives on Materials Waste Re-duction in Ghana, Engineering Management Research Vol. 1, No. 1; May 2012 REFERENCE 1. Archana Khorate, Prof. S. V. Pataskar, (2014) Management and Minimization of Construction Waste for Residential Site, International Journal of Scientific & Engineering Research, Volume 5, Issue 7, July A. Al-Hajj, PhD, Heriot-Watt UniversityK. Hamani, MSc, Heriot-Watt University, (2011) Material waste in the UAE construction industry: main causes and minimization / B.A.Bossink and H.J.H. Brouwers, Construction waste: Quantification and source evaluation, Journal Of Con-struction Engineering And Management / March 1996/55 4. Carlos T. Formoso1; Lucio Soibelman M.ASCE2; Clau-dia De Cesare3; and Eduardo L. Isatto4, Material waste in Building Industry: Main causes and Prevention, Jour-nal of Construction Engineering and Management / Ju-ly/August Formoso, C. T., Soibelman L., Cesare, C. D. and Isatto, E. L., (2002). Material Waste in Building Industry: Main Causes and Prevention. Journal of construction Engineering and Management, Vol. 128, No Ferry Firmawan*, Fadil Othman, Khairulzan Yahya, (2012) Improving project performance and waste reduction in construction projects: a case study of a government institutional building project81310 UTM Johor Bahru (2012) 2: ISSN IJTech Ismail Abdul Rahman1, Ade Asmi2, Aftab Hameed Memon1, Rosli Mohammad Zin (2012) Identifying Causes of Construction Waste - Case of Central Region of Peninsula Malaysia Sasitharan Nagapan1, Vol. 4 No. 2 (2012) p Katz. A and H. Baum, (2011) "A Novel Methodology to Estimate the Evolution of Construction Waste in Construction Sites," Journal of Waste Management, vol. 31, pp , 2011