ARCOM

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Abdirad, H and Dossick, C S (2019) Normative and descriptive models for COBie implementation: discrepancies and limitations. Engineering, Construction and Architectural Management, 26(08), 1820–36.

Almarri, K, Alzahrani, S and Boussabaine, H (2019) An evaluation of the impact of risk cost on risk allocation in public private partnership projects. Engineering, Construction and Architectural Management, 26(08), 1696–711.

Anson, M, Ying, K T and Siu, M F (2019) Analytical models towards explaining the difficulty in efficiently matching site concrete supply resources with placing crew needs. Engineering, Construction and Architectural Management, 26(08), 1672–95.

• Type: Journal Article
• Keywords: Scheduling; Simulation; Productivity; Construction planning; Construction site;
• ISBN/ISSN: 0969-9988
• URL: https://doi.org/10.1108/ECAM-02-2018-0049
• Abstract:
  For parts of the time on a typical construction site concrete pour, the site placing crew is idle waiting for the arrival of the next truckmixer delivery, whereas for other periods, truckmixers are idle on site waiting to be unloaded. Ideally, the work of the crew should be continuous, with successive truckmixers arriving on site just as the preceding truckmixer has been emptied, to provide perfect matching between site and concrete plant resources. However, in reality, sample benchmark data, representing 118 concrete pours of 69 m³ average volume, illustrate that significant wastage occurs of both crew and truckmixer time. The purpose of this paper is to present and explain the characteristics of the wastage pattern observed and provide further understanding of the effects of the factors affecting the productivity of this everyday routine site concreting system. Analytical algebraic models have been developed applicable to both serial and circulating truckmixer dispatch policies. The models connect crew idle time, truckmixer waiting time, truckmixer round trip time, truckmixer unloading time and truckmixer numbers. The truckmixer dispatch interval is another parameter included in the serial dispatch model. The models illustrate that perfect resource matching cannot be expected in general, such is the sensitivity of the system to the values applying to those parameters. The models are directly derived from theoretical truckmixer and crew placing time-based flow charts, which graphically depict crew and truckmixer idle times as affected by truckmixer emptying times and other relevant parameters. The models successfully represent the magnitudes of the resource wastage seen in real life but fail to mirror the wastage distribution of crew and truckmixer time for the 118 pour benchmark. When augmented to include the simulation of stochastic activity durations, however, the models produce pour combinations of crew and truckmixer wastage that do mirror those of the benchmark. The basic contribution of the paper consists of the proposed analytical models themselves, and their augmented versions, which describe the site and truckmixer resource wastage characteristics actually observed in practice. A further contribution is the step this makes towards understanding why such an everyday construction process is so apparently wasteful of resources.

Antwi-Afari, M F, Li, H, Wong, J K, Oladinrin, O T, Ge, J X, Seo, J and Wong, A Y L (2019) Sensing and warning-based technology applications to improve occupational health and safety in the construction industry. Engineering, Construction and Architectural Management, 26(08), 1534–52.

Au-Yong, C P, Chua, S J L, Ali, A S and Tucker, M (2019) Optimising maintenance cost by prioritising maintenance of facilities services in residential buildings. Engineering, Construction and Architectural Management, 26(08), 1593–607.

Charkhakan, M H and Heravi, G (2019) Evaluating the preventability of conflicts arising from change occurrence in construction projects. Engineering, Construction and Architectural Management, 26(08), 1777–800.

Gao, J, Ren, H, Ma, X, Cai, W and Shi, Q (2019) A total energy efficiency evaluation framework based on embodied energy for the construction industry and the spatio-temporal evolution analysis. Engineering, Construction and Architectural Management, 26(08), 1652–71.

He, Q, Wang, T, Chan, A P, Li, H and Chen, Y (2019) Identifying the gaps in project success research. Engineering, Construction and Architectural Management, 26(08), 1553–73.

Hilali, A, Charoenngam, C and Barman, A (2019) Barriers in contractual scope management of international development projects in Afghanistan. Engineering, Construction and Architectural Management, 26(08), 1574–92.

Hopkin, T, Lu, S, Sexton, M and Rogers, P (2019) Learning from defects in the UK housing sector using action research. Engineering, Construction and Architectural Management, 26(08), 1608–24.

Jin, R, Zou, Y, Gidado, K, Ashton, P and Painting, N (2019) Scientometric analysis of BIM-based research in construction engineering and management. Engineering, Construction and Architectural Management, 26(08), 1750–76.

Liang, R and Chong, H (2019) A hybrid group decision model for green supplier selection: a case study of megaprojects. Engineering, Construction and Architectural Management, 26(08), 1712–34.

Murillo, K P, Rocha, E and Rodrigues, M F (2019) Construction sectors efficiency analysis on seven European countries. Engineering, Construction and Architectural Management, 26(08), 1801–19.

Park, E, Kwon, S J and Han, J (2019) Antecedents of the adoption of building information modeling technology in Korea. Engineering, Construction and Architectural Management, 26(08), 1735–49.

Rajagopalan, G (2019) Durability of alumina silicate concrete based on slag/fly ash blends against corrosion. Engineering, Construction and Architectural Management, 26(08), 1641–51.

Silverio-Fernandez, M A, Renukappa, S and Suresh, S (2019) Evaluating critical success factors for implementing smart devices in the construction industry. Engineering, Construction and Architectural Management, 26(08), 1625–40.