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Choice of Optimum Combination of Construction Machinery Using Modified Advanced Programmatic Risk Analysis and Management Model
Choice of Optimum Combination of Construction Machinery Using Modified Advanced Programmatic Risk Analysis and Management Model
- Source :
- Scientia Iranica.
- Publication Year :
- 2017
- Publisher :
- SciTech Solutions, 2017.
-
Abstract
- Since the proper use of construction machinery in infrastructure projects is important, it is essential to employ an optimum selection of machinery in these projects. Advanced programmatic risk analysis and management model (APRAM) is one of recently developed methods that can be used for risk analysis and management purposes considering schedule, cost and quality, simultaneously. In this paper, first the APRAM method is introduced and then modified in order to consider environmental risks. This method can consider potential risks that might occur over the entire life cycle of the project, and can be employed as an efficient decision-support tool for construction managers selecting machinery for an infrastructure project where various alternatives might be technically feasible. A case study of three possible combinations of excavation machines is then discussed. All project risks related to cost, time, quality and environment are identified, considering the capital costs which should be spent on each combination. Finally, some graphs which are derived from the method are taken into account in order to decrease each combination’s risks and to optimize the selection of excavating machinery. The outcomes highlight the efficiency of the APRAM model for the optimal selection of machinery in construction projects.
- Subjects :
- Engineering
business.industry
media_common.quotation_subject
General Engineering
020101 civil engineering
02 engineering and technology
Schedule (project management)
0201 civil engineering
020303 mechanical engineering & transports
0203 mechanical engineering
Risk analysis (engineering)
Order (exchange)
Systems engineering
Capital cost
Entire life cycle
Quality (business)
business
Risk analysis and management
Selection (genetic algorithm)
media_common
Subjects
Details
- ISSN :
- 23453605
- Database :
- OpenAIRE
- Journal :
- Scientia Iranica
- Accession number :
- edsair.doi...........435a30eaeec0988254c5aca43e1a801b
- Full Text :
- https://doi.org/10.24200/sci.2017.4197