The S-curve for forecasting waste generation in construction projects

Waste Management

Volumn 56, Issue , 2016, Pages 23-34

  Lu, Weisheng ^a   Peng, Yi ^b   Chen, Xi ^a   Skitmore, Martin ^c   Zhang, Xiaoling ^d  

^a UNIVERSITY OF HONG KONG   (Hong Kong)

^b ZHEJIANG UNIVERSITY OF FINANCE AND ECONOMICS   (China)

^c QUEENSLAND UNIVERSITY OF TECHNOLOGY   (Australia)

^d CITY UNIVERSITY OF HONG KONG   (Hong Kong)

Author keywords

Construction waste management; Curve fitting; Forecast; S curve; Waste generation quantification

Indexed keywords

CURVE FITTING; FORECASTING; NEURAL NETWORKS; PROJECT MANAGEMENT; WASTE DISPOSAL;

CONSTRUCTION AND DEMOLITION; CONSTRUCTION WASTE GENERATIONS; CONSTRUCTION WASTE MANAGEMENTS; LOGISTIC DISTRIBUTIONS; PROJECT CHARACTERISTICS; PROJECT COST MANAGEMENT; S CURVE; WASTE GENERATION;

WASTE MANAGEMENT;

BUILDING CONSTRUCTION; FORECASTING METHOD; MODELING; WASTE DISPOSAL; WASTE MANAGEMENT;

ARTICLE; ARTIFICIAL NEURAL NETWORK; BENCHMARKING; BUILDING INDUSTRY; CONTROLLED STUDY; COST BENEFIT ANALYSIS; CURVE FITTING; FORECASTING; HONG KONG; PLOTS AND CURVES; PUBLIC-PRIVATE PARTNERSHIP; S CURVE; SOLID WASTE MANAGEMENT; STATISTICAL ANALYSIS; WASTE; WASTE GENERATION; ANALYSIS; INDUSTRIAL WASTE; PROCEDURES; THEORETICAL MODEL; WASTE MANAGEMENT;

CHINA; HONG KONG;

INDUSTRIAL WASTE;

CONSTRUCTION INDUSTRY; FORECASTING; HONG KONG; INDUSTRIAL WASTE; MODELS, THEORETICAL; NEURAL NETWORKS (COMPUTER); WASTE MANAGEMENT;

EID: 85011094654     PISSN: 0956053X     EISSN: 18792456     Source Type: Journal    
DOI: 10.1016/j.wasman.2016.07.039     Document Type: Article

References (54)

1. Balkau, B.J., A financial model for public works programmes. Paper to National ASOR Conference, Sydney, 25–27 August 1975, 1975.
2. Bergsdal, H., Bohne, R.A., Brattebo, H., Projection of construction and demolition waste in Norway. J. Ind. Ecol. 11:3 (2007), 27–39.
3. Berny, J., Howes, R., Project management control using real-time budgeting and forecasting models. Constr. Pap. 2:1 (1982), 19–40.
4. Boiral, O., Henri, J.F., Modelling the impact of ISO 14001 on environmental performance: a comparative approach. J. Environ. Manage. 99 (2012), 84–97.
5. Boussabaine, A.H., The use of artificial neural networks in construction management: a review. Constr. Manage. Econ. 14:5 (1996), 427–436.
6. Boussabaine, A.H., Kaka, A.P., A neural networks approach for cost flow forecasting. Constr. Manage. Econ. 16:4 (1998), 471–479.
7. Brian, M., 2008. The Site Waste Management Plans Regulations 2008, Regulatory Update, Compliance, (online) www.wastefile.com/news.Site Waste Management Plan Regulations 2008 (accessed 04/02/2008).
8. Bromilow, F.J., Henderson, J.A., Procedures for Reckoning and Valuing Performance of Building Contracts. 1974, CSIRO Division of Building Research.
9. Bromilow, F.J., Henderson, J.A., Procedures for Reckoning the Performance of Building Contracts. second ed., 1977, CSIRO, Division of Building Research, Highett, Australia.
10. Chao, L.C., Chien, C.F., Estimating project S-curves using polynomial function and neural networks. J. Constr. Eng. Manage. 135:3 (2009), 169–177.
11. Chao, L.C., Skibniewski, M.J., Neural network method of estimating construction technology acceptability. J. Constr. Eng. Manage. 121:1 (1995), 130–142.
12. Cheng, J.C., Ma, L.Y., A BIM-based system for demolition and renovation waste estimation and planning. Waste Manage. 33:6 (2013), 1539–1551.
13. Chinese Matlab Forum, Thirty Cases of Artificial Neural Networks with Matlab. 2010, Bei Hang University Press, Beijing (in Chinese).
14. Cochran, K.M., Townsend, T.G., Estimating construction and demolition debris generation using a materials flow analysis approach. Waste Manage. 30:11 (2010), 2247–2254.
15. Coelho, A., de Brito, J., Influence of construction and demolition waste management on the environmental impact of buildings. Waste Manage. 32 (2012), 532–541.
16. De Groot, A.D., Methodology: Foundation of Inference and Research in the Behavioral Sciences. 1969, Mouton & Co., Belgium.
17. De Guzmán Báez, A., Sáez, P.V., del Río Merino, M., Navarro, J.G., Methodology for quantification of waste generated in Spanish railway construction works. Waste Manage. 32:5 (2012), 920–924.
18. Drake, B.E., A mathematical model for expenditure forecasting post contract. Proceedings of the Second International Symposium on Organization and Management of Construction, 1978, Technion Israel Institute of Technology, Haifa, Israel, 163–183.
19. Hardy, J.V., Cash flow forecasting for the construction industry. MSc Report, 1978, Department of Civil Engineering, Loughborough University of Technology.
20. Hong Kong Development Bureau (HKDB), Works Bureau Technical Circular No 29/2000, Waste Management Plan. 2000, Works Bureau (now HKDB), Hong Kong SAR Government.
21. Hong Kong Environmental Protection Department (HKEPD), 2009. Waste Reduction Guidelines. Hong Kong Environmental Protection Department. Extracted from website: http://www.epd.gov.hk/epd/misc/cdm/guidelines6.htm (accessed 04/06/2014).
22. Hudson, K.W., D.H.S.S. expenditure forecasting method. Chart. Surv. Build. Quant. Surv. Q. 5:3 (1978), 42–45.
23. Hudson, K.W., Maunick, J., Capital Expenditure Forecasting on Health Building Schemes or a Proposed Method of Expenditure Forecast. Research Report, 1974, Surveying Division, Research Section, Department of Health and Social Security, UK.
24. Jepson, W.B., Financial control of construction and reducing the element of risk. Contract J. 24 (1969), 862–864.
25. Kaka, A.P., The development of a benchmark model that uses historical data for monitoring the progress of current construction projects. Eng. Constr. Archit. Manage. 6:3 (1999), 256–266.
26. Katz, A., Baum, H., A novel methodology to estimate the evolution of construction waste in construction sites. Waste Manage. 31 (2011), 353–358.
27. Kenley, R., Wilson, O.D., A construction project net cash flow model. Constr. Manage. Econ. 7 (1989), 3–18.
28. Khosrowshahi, F., Simulation of expenditure patterns of construction projects. Constr. Manage. Econ. 9 (1991), 113–132.
29. Kim, Y.W., Ballard, G., Is the earned-value method an enemy of work flow?. Proceedings Eighth Annual Conference of the International Group for Lean Construction, vol. 6, 2000.
30. Li, J.L., Ding, Z.K., Mi, X.M., Wang, J.Y., A model for estimating construction waste generation index for building project in China. Resour. Conserv. Recycl. 74 (2013), 20–26.
31. Li, Y., Zhang, X., Ding, G., Feng, Z., Developing a quantitative construction waste estimation model for building construction projects. Resour. Conserv. Recycl. 106 (2016), 9–20.
32. Lu, W., Tam, V.W., Construction waste management policies and their effectiveness in Hong Kong: a longitudinal review. Renew. Sustain. Energy Rev. 23 (2013), 214–223.
33. Lu, W., Yuan, H., Exploring critical success factors for waste management in construction projects of China. Resour. Conserv. Recycl. 55:2 (2010), 201–208.
34. Lu, W., Yuan, H., Li, J., Hao, J., Mi, X., Ding, Z., An empirical investigation of construction and demolition waste generation rates in Shenzhen city, South China. Waste Manage. 31:4 (2011), 680–687.
35. Lu, W.S., Peng, Y., Shen, Q.P., Li, H., A generic model for measuring benefits of BIM as a learning tool in construction works. J. Constr. Eng. Manage. 139:2 (2013), 195–203.
36. Lu, W., Chen, X., Peng, Y., Shen, L., Benchmarking construction waste management performance using big data. Resour. Conserv. Recycl. 105 (2015), 49–58.
37. Lu, W., Webster, C., Peng, Y., Chen, X., Zhang, X., Estimating and calibrating the amount of building-related construction and demolition waste in urban china. Int. J. Constr. Manage., 2016, 1–12.
38. MathWorks, The Language of Technical Computing, 2012, The MathWorks, Inc. .
39. Ministry of the Presidency, 2008. National Decree 105/2008, 1 February, which Regulates the Production and Management of the Construction and Demolition Waste. Edited by Ministry of the Presidency, Spanish Government, 2008.
40. Miskawi, Z., An S-curve equation for project control. Constr. Manage. Econ., 7, 1989, 1150125.
41. Nagalli, A., The sustainability of Brazilian construction and demolition waste management system. Electron. J. Geotech. Eng. 18 (2013), 1755–1759.
42. Oliver, J.C., Modeling Cash Flow Projections using a Standard Micro-computer Spreadsheet Program. MSc Project in Construction Management, 1984, Loughborough University of Technology.
43. Poon, C.S., Yu, T.W.A., Jaillon, L., Reducing building waste at construction sites in Hong Kong. Constr. Manage. Econ. 22:5 (2004), 461–470.
44. Project Management Institute, A Guide to the Project Management Body of Knowledge (PMBOK® Guide). 2013, Project Management Institute (incorporated).
45. Runyan, W.M., Idiographic goals and methods in the study of lives. J. Pers. 51 (1983), 413–437.
46. Sáez, P.V., Merino, M., Porras-Amores, C., González, A.S., Assessing the accumulation of construction waste generation during residential building construction works. Resour. Conserv. Recycl. 93 (2014), 67–74.
47. Singh, S., Woon, P.W., Cash flow trends for high-rise building projects. Proceedings of the 4th International Symposium on Organization and Management of Construction, 1984, University of Waterloo, Canada.
48. Skitmore, M., Parameter prediction for cash flow forecasting models. Constr. Manage. Econ. 10:5 (1992), 397–413.
49. Skitmore, M., A method for forecasting owner monthly construction project expenditure flow. Int. J. Forecast. 14 (1998), 17–34.
50. Srinivas, H., Waste Management Fact Sheet, 2003 (accessed 04/06/2014).
51. Thomae, H., The nomothetic-idiographic issue: some roots and recent trends. Int. J. Group Tens. 28:1 (1999), 187–215.
52. Tucker, S.N., A single alternative formula for the Department of Health and Social Security S-curves. Constr. Manage. Econ. 6 (1988), 13–23.
53. Wang, J., Yuan, H., Kang, X., Lu, W., Critical success factors for on-site sorting of construction waste: a China study. Resour. Conserv. Recycl. 54:11 (2010), 931–936.
54. Wu, Z., Ann, T.W., Shen, L., Liu, G., Quantifying construction and demolition waste: an analytical review. Waste Manage. 34:9 (2014), 1683–1692.