AN IMPACT OF EQUIPMENT SELECTION ON CONSTRUCTION PROJECTS: CASE STUDY OF A ROAD PROJECT IN EGYPT

  • Elbadr Osman Construction and Building Engineering Department, College of Engineering and Technology, Arab Academy for Science, Technology and Maritime Transport (AASTMT) Alexandria, Egypt
  • Amr A. Mohy Construction and Building Engineering Department, College of Engineering and Technology, Arab Academy for Science, Technology and Maritime Transport (AASTMT) Alexandria, Egypt
Keywords: construction equipment management, equipment selection, equipment production rate, projects cost and time, excavation activity, backhoe

Abstract


The use of equipment in the construction industry has expanded in recent years due to the equipment’s ability to complete most work items such as excavation work, casting, and more in a relatively short period of time. However, the real challenge would be selecting the appropriate equipment and accurately predicting the productivity of the equipment. In most projects, the choice of equipment to execute any work is based mainly on the expertise of contractors without taking into account any aspect of equipment’s life. Therefore, any insufficient construction equipment planning and management would have a huge undesirable effect on the time and cost of any project. The main aim of this research is to study the impact of equipment selection on the productivity of construction excavation sites and its effect on time and cost through a road project in Egypt as a case study. A highway road excavation project in Egypt with a total length of 7.2 km (4.5 miles). The impact would be determined by monitoring the progress of earthmoving activities and conducting a comparison between the estimated and actual productivity of equipment (long boom backhoe). The progress data was collected over 30 days for eight working hours per day for each piece of equipment. As a result of the poor equipment management, the actual productivity was 50% of the predicted rate, and that impacted the project’s cost by a 71.5% increase and by a 72% increase in the duration.

References

lang=EN-US>

style='mso-ansi-language:DE'> ADDIN

ZOTERO_BIBL

{"uncited":[],"omitted":[],"custom":[]}

CSL_BIBLIOGRAPHY Gransberg DD, Rueda-Benavides JA (2020). Construction Equipment Management for Engineers, Estimators, and Owners, 2nd ed. CRC Press, Boca Raton

Mohane AP, Ambre HP (2019). Equipment Planning and Management in Road Construction Project

Shehadeh A, Alshboul O, Tatari O, et al (2022). Selection of heavy machinery for earthwork activities: A multi-objective optimization approach using a genetic algorithm. Alex Eng J 61:7555—7569. https://doi.org/10.1016/j.aej.2022.01.010>

Zidane YJ-T, Andersen B (2018). The top 10 universal delay factors in construction projects. Int J Manag Proj Bus

Cha HS, Kim KH (2018). Measuring project performance in consideration of optimal best management practices for building construction in South Korea. KSCE J Civ Eng 22:1614—1625

Mellado F, Lou EC (2020). Building information modeling, lean and sustainability: An integration framework to promote performance improvements in the construction industry. Sustain Cities Soc 61:102355

He Q, Wang T, Chan AP, Xu J (2021). Developing a list of key performance indicators for benchmarking the success of construction megaprojects. J Constr Eng Manag 147:04020164

Marcelino P, Lurdes Antunes M de, Fortunato E (2018). Comprehensive performance indicators for road pavement condition assessment. Struct Infrastruct Eng 14:1433—1445

Mathewos M (2017). A Study on Construction Equipment Planning and Management Problems in Road Construction Project (A Case Study: The Addis Ababa City Roads Authority). Dep Constr Technol Manag Sch Civ Environ Eng Addis Ababa Inst Technol Addis Ababa Univ Addis Ababa Ethiop

Mohane AP, Ambre HP (2019). Equipment Planning and Management in Road Construction Project. Int Res J Eng Technol 960:

Al-Janabi AM, Abdel-Monem MS, El-Dash KM (2020). Factors causing rework and their impact on projects’ performance in Egypt. J Civ Eng Manag 26:666—689

Shibani A, Mahadel O, Hassan D, et al (2021). Causes of time overruns in the construction industry in Egypt. Int Res J Mod Eng Technol Sci IRJMETS 3:510—531

CAPMAS E (2022). Central Agency for Public Mobilization and Statistics. https://www.capmas.gov.eg/HomePage.aspx. Accessed 5 Mar 2022

Schaufelberger JE, Migliaccio GC (2019). Construction Equipment Management. Routledge

Giri K, Bhonde BK, Patil A (2020). Time and Cost Overruns in the Construction Industry Due to Downtime of the Construction Equipment and Machineries.

Kusimo H, Oyedele L, Akinade O, et al (2019). Optimization of resource management in construction projects: a big data approach. World J Sci Technol Sustain Dev

Leuva S (2012). Importance Of Road Equipment & Road Construction Machinery

Sepasgozar SM, Li H, Shirowzhan S, Tam VW (2019). Methods for monitoring construction off-road vehicle emissions: A critical review for identifying deficiencies and directions. Environ Sci Pollut Res 26:15779–15794

Day DA, Benjamin NB (1991). Construction equipment guide. John Wiley & Sons

Hazır Ö, Ulusoy G (2020). A classification and review of approaches and methods for modeling uncertainty in projects. Int J Prod Econ 223:107522

PHAM CP, NGUYEN PT, PHAN PT, et al (2020). Risk factors affecting equipment management in construction firms. J Asian Finance Econ Bus 7:347—356

Pheng LS, Meng CY (2018). Managing productivity in construction: JIT operations and measurements. Routledge

Sahu D (2022). Effective Criterion for Equipment Management in Construction Industry. In: Recent Developments in Sustainable Infrastructure (ICRDSI-2020)—Structure and Construction Management. Springer, pp 185–199

Kumar KP, Mouli TC (2019). Impact of Construction Equipment Downtime in Indian Construction Sector. https://www.semanticscholar.org/paper/Impact-of-Construction-Equipment-Downtime-in-Indian-Kumar-Mouli/519e7d9b00d8f74e39c987a16053705e93586865. Accessed 4 Mar 2022

Waris M, Shahir Liew Mohd, Khamidi MohdF, Idrus A (2014). Criteria for the selection of sustainable on-site construction equipment. Int J Sustain Built Environ 3:96—110. https://doi.org/10.1016/j.ijsbe.2014.06.002>

Gransberg DD, Shane JS (2015). Defining Best Value for Construction Manager/General Contractor Projects: The CMGC Learning Curve. J Manag Eng 31:04014060. https://doi.org/10.1061/ (ASCE) ME.1943-5479.0000275

Czarnowski J, Dąbrowski A, Maciaś M, et al (2018). Technology gaps in human-machine interfaces for autonomous construction robots. Autom Constr 94:179—190

Yap JBH, Goay PL, Woon YB, Skitmore M (2021). Revisiting critical delay factors for construction: Analysing projects in Malaysia. Alex Eng J 60:1717—1729

Sakhare MV, Chougule MB (2019). Construction Equipment Monitoring: By Using Relative Important Indices (Rii) Analysis

Khan A, Deep S, Asim M (2017). Analysis of maintenance records of construction equipments and their importance in minimizing equipments breakdown during project execution phase to lessen time overrun. Int J Civ Eng Technol 8:11—23

Abdel-Hamid M, Mohamed Abdelhaleem H (2020). Impact of poor labor productivity on construction project cost. Int J Constr Manag 1–8

Chong A, Galdo J, Saavedra J (2007). Informality and Productivity in the Labor Market: Peru 1986–2001. Inter-American Development Bank, Research Department

Panas A, Pantouvakis J-P (2018). On the use of learning curves for the estimation of construction productivity. Int J Constr Manag 18:301—309

Manikandan M, Adhiyaman M, Pazhani KC (2018). A study and analysis of construction equipment management used in construction projects for improving productivity. Int Res J Eng Technol IRJET 5:1297—1303

Atnaw SM, Singh L, Hagos FY, Yousuf A (2016). Road Construction Equipment Management: A Case Study on Selected Industry. Int J Eng Technol Sci 3:91—97

Harris F, McCaffer R (1995). Modern Construction Management,‖ Oxford

Lema NM, Samson M (1995). Construction of labour productivity modeling. Univ Dar Elsalaam 1:

Olomolaiye PO, Jayawardane AK, Harris F (1998). Construction productivity management. Prentice Hall

Shewhart WA (1931). Statistical method from an engineering viewpoint. J Am Stat Assoc 26:262—269

Gartner WB, Naughton MJ (1988). The Deming theory of management

Montgomery DC, Mastrangelo CM (1991). Some statistical process control methods for autocorrelated data. J Qual Technol 23:179—193

Khot S, Patil S (2020). Factors Affecting the Equipments on Site

"Arial",sans-serif;mso-fareast-font-family:"Times New Roman";mso-bidi-font-family:

"Times New Roman";mso-ansi-language:EN-US;mso-fareast-language:EN-US;

mso-bidi-language:AR-SA'>

Alaghbari W, Al-Sakkaf AA, Sultan B (2019). Factors affecting construction labour productivity in Yemen. Int J Constr Manag 19:79—91

Published
2022/10/16
Section
Original Scientific Paper