Estimating the Probability Distribution of Construction Project Completion Times Based on Drum-Buffer-Rope Theory
Source abstract
Abstract
Various factors affecting the construction progress are regarded as bottlenecks giving rise to the project duration overrun. The contractor should combine the project schedule with the plan in order to reduce the uncertainty of the project activities. The present research describes the method derived from the theory of constraints (TOC) attempts to enhance the relationship among activities, to revise and further reduce the uncertainty of construction activities to improve the reliability of project progress. The elements of drum, buffer and rope (DBR) in TOC are added to PERT network schedule; through the identification of schedule in the bottleneck process, the implementation plan of the bottleneck is obtained. By measuring buffer time and calculating network schedule buffer time as well as feeding time, the relationship among activities and uncertainty of duration are also improved. To illustrate the impact of DBR applications on improving project schedule reliability, a case of hydropower station as an example is illustrated to show enhanced reliability of scheduling. As compared to program evaluation and review technique network (PERT) simulation, the simulation results showed that the uncertainty of construction progress could be reduced if the DBR are well cooperated mutually.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Operations Management Techniques · Resource-Constrained Project Scheduling · Urban Transport Systems Analysis
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
School of Civil Engineering, Suzhou University of Science and Technology, Suzhou 215000, China
School of Business, Suzhou University of Science and Technology, Suzhou 215000, China
Institute of Engineering Management, Hohai University, Nanjing 211100, China
Funding
Philosophy and Social Science Research in Colleges and Universities in Jiangsu Province · Fundamental Research Funds for the Central Universities · Jiangsu Provincial Construction System Science and Technology Project of Housing and Urban and Rural Development Department
References (57)
Show source-provided references
1. A multi-objective optimization method considering process risk correlation for project risk response planning10.1016/j.ins.2018.07.013 ↗
2. A Knowledge-Based Risk Measure from the Fuzzy Multicriteria Decision-Making Perspective10.1109/TFUZZ.2018.2838064 ↗
3. Selection of risk response actions considering risk dependency10.1108/K-05-2016-0096 ↗
4. Building information modeling as a risk transformer: An evolutionary insight into the project uncertainty10.1016/j.autcon.2018.03.032 ↗
5. A simulation-based risk interdependency network model for project risk assessment10.1016/j.dss.2021.113602 ↗
6. Project Management Using the Buffers of Time and Resources10.1016/j.sbspro.2016.11.014 ↗
7. Schedule Risk Analysis using a Proposed Modified Variance and Mean of the Original Program Evaluation and Review Technique Model10.1007/s12205-019-1826-z ↗
8. Scheduling Markovian PERT networks to maximize the net present value: New results10.1016/j.orl.2018.01.010 ↗
9. A robust optimization approach for the multi-mode resource-constrained project scheduling problem10.1016/j.ejor.2019.09.052 ↗
10. Using Schedule Risk Analysis with resource constraints for project control10.1016/j.ejor.2020.06.015 ↗
11. Debottlenecking cogeneration systems under process variations: Multi-dimensional bottleneck tree analysis with neural network ensemble10.1016/j.energy.2020.119168 ↗
12. A generic hierarchical clustering approach for detecting bottlenecks in manufacturing10.1016/j.jmsy.2020.02.011 ↗
13. The Effects of Different Activity Distributions on Project Duration in PERT Networks10.1016/j.sbspro.2014.03.086 ↗
14. The probability distribution of project completion times in simulation-based scheduling10.1007/s12205-013-0147-x ↗
15. Poshdar, M. (2016). A Probabilistic-Based Method to Determine Optimum Size of Project Buffer in Construction Schedules. J. Constr. Eng. Manag., 142.10.1061/(ASCE)CO.1943-7862.0001158 ↗
16. Project planning and control: An enhanced PERT network10.1016/0263-7863(93)90016-G ↗
17. Robust Reliability of Projects with Activity-Duration Uncertainty10.1061/(ASCE)0733-9364(1998)124:2(125) ↗
18. Construction delay: A quantitative analysis10.1016/S0263-7863(98)00060-X ↗
19. Simplified program evaluation and review technique (PERT)10.1061/(ASCE)0733-9364(1999)125:1(16) ↗
20. Playing chess or playing poker? Assessment of uncertainty propagation in open innovation projects10.1016/j.ijproman.2020.07.002 ↗
21. Choosing suitable project control modes to improve the knowledge integration under different uncertainties10.1016/j.ijproman.2019.07.002 ↗
22. Tsai, W.H., and Lai, S.Y. (2018). Green Production Planning and Control Model with ABC under Industry 4.0 for the Paper Industry. Sustainability, 10.10.3390/su10082932 ↗
23. Goldratt, E.M. (1997). Critical Chain, The North River Press Publishing Corporation.
24. A simulation comparison of traditional JIT and TOC manufacturing systems in a flow shop with bottlenecks
25. A framework for the systemic control of organizations10.1080/002075497195614 ↗
26. Drum-buffer-rope and buffer management: Impact on production management study and practices10.1108/01443579310039047 ↗
27. Optimum Production Technology (OPT) and the Theory of Constraints (TOC)—Analysis and Genealogy10.1080/00207549508930224 ↗
28. A Simulation Analysis of the Effectiveness of Drum-Buffer-Rope Scheduling in Furniture Manufacturing10.1016/0360-8352(94)90010-8 ↗
29. Project management applications of the theory of constraints beyond critical chain scheduling10.1016/S0263-7863(00)00054-5 ↗
30. The use of buffers in project management: The trade-off between stability and makespan10.1016/j.ijpe.2004.08.004 ↗
31. Incorporation of activity sensitivity measures into buffer management to manage project schedule risk10.1016/j.ejor.2015.08.066 ↗
32. Project buffer sizing of a critical chain based on comprehensive resource tightness10.1016/j.ejor.2015.07.009 ↗
33. Buffer sizing approach with dependence assumption between activities in critical chain scheduling10.1080/00207543.2011.649096 ↗
34. Goldratt, E.M., and Cox, J. (1992). The Goal: A Process of Ongoing Improvement, North River Press.
35. Theory of Constraints: A Literature Review10.1016/j.sbspro.2014.09.104 ↗
36. Developing a Novel Framework to Manage Schedule Contingency Using Theory of Constraints and Earned Schedule Method10.1061/(ASCE)CO.1943-7862.0001178 ↗
37. Analyzing Manufacturing Problems Using V-A-T Analysis
38. Determination of buffer sizes for drum-buffer-rope (DBR)-controlled production systems10.1080/00207540600922948 ↗
39. Drum-buffer-rope and workload control in High-variety flow and job shops with bottlenecks: An assessment by simulation10.1016/j.ijpe.2017.03.025 ↗
40. Project Management with Theory of Constraints10.1016/j.sbspro.2016.07.118 ↗
41. Critical chain: The theory of constraints applied to project management10.1016/S0263-7863(99)00019-8 ↗
42. Software development projects IRSE buffer settings and simulation based on critical chain10.1016/S1005-8885(09)60598-7 ↗
43. An investigation of buffer sizing techniques in critical chain scheduling10.1016/j.ejor.2004.10.019 ↗
44. Drum-buffer-rope scheduling and pictures for the yearbook
45. A comparison of buffer sizing techniques in the critical chain method case study
46. Resource-constrained project management using enhanced theory of constraint10.1016/S0263-7863(01)00063-1 ↗
47. Buffer Management: A Diagnostic Tool for Production Control
48. Synchronized Manufacturing as in Opt—From Practice to Theory10.1016/0360-8352(90)90017-G ↗
49. Multi-Project Scheduling and Control: A Process-Based Comparative Study of the Critical Chain Methodology and Some Alternatives10.1177/875697280403500206 ↗
50. Project portfolio management information systems’ positive influence on performance—The importance of process maturity10.1016/j.ijproman.2020.05.001 ↗
51. Organising and Managing boundaries: A structurational view of collaboration with Building Information Modelling (BIM)10.1016/j.ijproman.2019.01.010 ↗
52. Scheduling in the service industries: An overview10.1007/s11518-015-5266-0 ↗
53. How to go global: A transformative process model for the transition towards globally distributed software development projects10.1016/j.ijproman.2019.08.003 ↗
54. A Computerized Method for Delay Risk Assessment Based on Fuzzy Set Theory using MS Project™10.1007/s12205-018-0810-3 ↗
55. Accurate lead time demand modeling and optimal inventory policies in continuous review systems10.1016/j.ijpe.2015.02.017 ↗
56. A review of analytical models, approaches and decision support tools in project monitoring and control10.1016/j.ijproman.2014.09.005 ↗
57. Project-conceptualisation in technological innovations: A knowledge-based perspective10.1016/j.ijproman.2013.10.002 ↗