English
Język Polski
Planning of construction projects taking into account the design risk
DOI:
https://doi.org/10.24425/ace.2023.144191Abstract
Complex construction projects require appropriate planning that allows for time and cost optimization, maximization of the use of available resources and appropriate investment control. Scheduling is a complicated process, due to the uncertainties and risks associated with construction works, the paper describes the development of the scheduling method traditionally used in Poland, based on data from KNR catalogs, by using the RiskyProject Professional program. In the RiskyProject Professional program, the risk and uncertainty with reference to a specific construction project were modeled, and the calculation results were compared with the real time of the project implementation. The conclusions from the work carried out confirm that the SRA (Schedule Risk Analysis) analysis of the base schedule allows for a more faithful representation of the actual conditions of a construction project. The probability of investment realization generated on the basis of the SRA analysis may be assumed at the level of 75÷90%.References
[1] S.A. Assaf and S. Al-Hejji, “Causes of delay in large construction projects”, International Journal of Project Management, vol. 24, no. 4, pp. 349-357, 2006, DOI: 10.1016/j.ijproman.2005.11.010.
[2] I. Mahamid, A. Bruland, and N. Dmaidi, “Causes of delay in road construction projects”, Journal of Management in Engineering, vol. 28, pp. 300-310, 2011, DOI: 10.1061/(ASCE)ME.1943-5479.0000096.
[3] F.D. Fugar and A.B. Agyakwah-Baah, “Delays in building construction projects in Ghana”, Australasian Journal of Construction Economics and Building, vol. 10, no. 1-2, pp. 103-116, 2010, DOI: 10.5130/AJCEB.v10i1-2.1592.
[4] R.F. Aziz, “Ranking of delay factors in construction projects after Egyptian revolution”, Alexandria Engineering Journal, vol. 52, no. 3, pp. 387-406, 2013, DOI: 10.1016/j.aej.2013.03.002.
[5] W. Jing, et al., “System dynamics modeling strategy for civil construction projects: the concept of successive legislation periods”, Symmetry, vol. 11, no. 5, 2019, DOI: 10.3390/sym11050677.
[6] A. Gondia, et al., “Machine learning algorithms for construction projects delay risk prediction”, Journal of Construction Engineering and Management, vol. 146, no. 1, 2020, DOI: 10.1061/(ASCE)CO.1943-7862.0001736.
[7] N. Kokkaew and W. Wipulanusat, “Completion delay risk management: A dynamic risk insurance approach”, KSCE Journal of Civil Engineering, vol. 18, pp. 1599-1608, 2014, DOI: 10.1007/s12205-014-1128-4.
[8] C. Rhodes, “Construction industry: statistics and policy”, House of Commons Library. [Online]. Available: https://commonslibrary.parliament.uk/research-briefings/sn01432/. [Accessed: 01.12.2022].
[9] B. Flyvbjerg, “What you should know about megaprojects and why: An overview”, Project Management Journal, vol. 45, no. 2, pp. 6-19, 2014, DOI: 10.1002/pmj.21409.
[10] Y. Liang and H. Wang, “Sustainable performance measurements for public-private partnership projects: empirical evidence from China”, Sustainability, vol. 11, no. 13, 2019, DOI: 10.3390/su11133653.
[11] X. Jiang, K. Lu, B. Xia, Y. Liu, and C. Cui, “Identifying significant risks and analyzing risk relationship for construction PPP projects in China using integrated FISM-MICMAC approach”, Sustainability, vol. 11, no. 19, art. no. 5206, 2019, DOI: 10.3390/su11195206.
[12] Y. Li and X.Y. Wang, “Using fuzzy analytic network process and ISM methods for risk assessment of public-private partnership: A China perspective”, Journal of Civil Engineering and Management, vol. 25, no. 2, pp. 168-183, 2019.
[13] B.K. Sovacool, A. Gilbert, and D. Nugent, “An international comparative assessment of construction cost overruns for electricity infrastructure”, Energy Research and Social Science, vol. 3, pp. 152-160, 2014, DOI: 10.1016/j.erss.2014.07.016.
[14] O. Awojobi and G.P. Jenkins, “Were the hydro dams financed by the World Bank from 1976 to 2005 worthwhile?”, Energy Policy, vol. 86, pp. 222-232, 2015, DOI: 10.1016/J.ENPOL.2015.06.040.
[15] A. Ansar, et al., “Should we build more large dams? The actual costs of hydropower megaproject development”, Energy Policy, vol. 69, pp. 43-56, 2014, DOI: 10.1016/j.enpol.2013.10.069.
[16] J.R.S. Cristóbal, “The S-curve envelope as a tool for monitoring and control of projects”, Procedia Computer Science, vol. 121, pp. 756-761, 2017, DOI: 10.1016/j.procs.2017.11.097.
[17] R. Atkinson, “Project Management: cost, time and quality, two best guesses and a phenomenon, it’s [its] time to accept other success criteria”, International Journal of Project Management, vol. 17, no. 6, pp. 337-342, 1999, DOI: 10.1016/S0263-7863(98)00069-6.
[18] M. Rogalska, Wieloczynnikowe modele w prognozowaniu czasu procesów budowlanych. Lublin, Poland: Wydawnictwo Politechniki Lubelskiej, 2016.
[19] P. Kostrzewa-Demczuk and M. Rogalska, “Anticipating the length of employees’ working time”, Symmetry, vol. 12, no. 3, art. no. 413, 2020, DOI: 10.3390/sym12030413.
[20] P. Kostrzewa and M. Rogalska, “Scheduling construction processes using the probabilistic time coupling method III”, IOP Conference Series: Materials Science and Engineering, vol. 471, art. no. 11207, 2019, DOI: 10.1088/1757-899X/471/11/112072.
[21] S. Bolotin, et al., “Harmonogramowanie przedsięwzięć budowlanych z uwzględnieniem modelu czasowo przestrzennego”, Przegląd Budowlany, no. 11, pp. 24-28, 2014.
[22] R.M. Choudhry, et al., “Cost and schedule risk analysis of bridge construction in Pakistan: establishing risk guidelines”, Journal of Construction Engineering and Management, 2014, vol. 140, no. 7, 2014, DOI: 10.1061/(ASCE)CO.1943-7862.0000857.
[23] PMI. A guide to the project management body of knowledge. PA, USA: Project Management Institute, Inc, 2017.
[24] P. Jaskowski, S. Biruk, and M. Krzemiński, “Proactive scheduling of repetitive construction processes to reduce crews idle times and delays”, Archives of Civil Engineering, vol. 67, no. 4, pp. 287-302, 2021, DOI: 10.24425/ace.2021.138500.
[25] J.C. Teixeria, et al., Zarządzanie ryzykiem w budownictwie. Warszawa, Polska: Wydawnictwo: Guimaraes, 2011.
[26] PMBOK guide. A guide to the project management body of knowledge. Pennsylvania, USA: Project Management Institute, PMI, 2000.
[27] P. Jaskowski, S. Biruk, and M. Krzemiński, “Planning repetitive construction processes to improve robustness of schedules in risk environment”, Archives of Civil Engineering, vol. 66, no. 3, pp. 643-657, 2020, DOI: 10.24425/ace.2020.134418.
[28] M. Vanhoucke, Project management with dynamic scheduling: baseline scheduling, risk analysis and project control. Ghent, Belgium: Springer Science & Business Media, 2013.
[29] S. Sackey and B.S. Kim, “Schedule risk analysis using a proposed modified variance and mean of the original program evaluation and review technique model”, KSCE Journal of Civil Engineering, vol. 23, pp. 1484-1492, 2019, DOI: 10.1007/s12205-019-1826-z.
[30] D. Nasir, B. Mccabe, and L. Hartono, “Evaluating risk in construction-schedule model (ERIC-S): construction schedule risk model”, Journal of Construction Engineering and Management, vol. 129, no. 5, pp. 518-527, 2003, DOI: 10.1061/(ASCE)0733-9364(2003)129:5(518).
[31] Ö. Ökmen and O. Öztas, “Construction project network evaluation with correlated schedule risk analysis model”, Journal of Construction Engineering and Management, vol. 134, no. 1, pp. 49-63, 2008, DOI: 10.1061/(ASCE)0733-9364(2008)134:1(49).
[32] Z.M. Yaseen, et al., “Prediction of risk delay in construction projects using a hybrid artificial intelligence model”, Sustainability, vol. 12, no. 4, art. no. 1514, 2020, DOI: 10.3390/su12041514.
[33] T.S. Glickman and F. Xu, “The distribution of the product of two triangular random variables”, Statistics and Probability Letters, vol. 78, pp. 2821-2826, 2008.
[34] K.E. Fairchild, L. Misra, and Y. Shi, “Using triangular distribution for business and finance simulations in Excel”, Journal of Financial Education, vol. 42, pp. 313-336, 2016.
[35] D. Johnson, “Triangular approximations for continuous random variables in risk analysis”, Journal of the Operational Research Society, vol. 53, no. 4, pp. 457-467, 2002, DOI: 10.1057/palgrave.jors.2601330.
[36] I.T. Yang, “Impact of budget uncertainty on project time-cost kradeoff”, IEEE Transactions on Engineering Management, vol. 52, no. 2, pp. 167-174, 2005, DOI: 10.1109/TEM.2005.844924.
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