An empirical investigation of the learning effect in concrete operations

Abstract

Purpose The purpose of this paper is to focus on productivity as it unfolds during the execution of a particular task, i.e., reinforced concrete operations. The main aim is understanding whether the learning effect explaining the improvement of productivity in subsequent cycles of a given repetitive construction process is mainly attributable to a pure worker learning (independent on the specific site) or to the experience developed by the crew on the site conditions. Design/methodology/approach The authors conduct a research that empirically investigates and compares the change in productivity data of a single worker during his/her working life and that of a crew involved in specific repetitive work, such as the concreting activities of a multi-storey building. Findings The findings suggest differentiating between productivity gain as a result of the learning effect of the individual worker throughout his/her working life (which is independent of the specific project and site) and that of a crew composed by more workers which repeat reinforced concrete operations in a given specific project. Research limitations/implications Despite the great attention reserved to learning in construction, few researchers discuss on the real applicability of the learning curve (LC) theory in the construction industry. The authors contribute to this literature by empirically investigating the contributions that the learning effect of the individual worker and that of a crew repeating a given task (i.e. reinforced concrete operations) in a given project have on the productivity improvement for subsequent cycles of the repetitive construction process. Practical implications The findings of this study have important managerial implications. The shape of the LC of the individual worker implies that learning increases relatively slowly in his/her working life (particularly after one to two years), while the effects of the crew experience are immediately significant in a time range of few weeks. This means that a single “one-off” multi-storey building project will show in the first storey the “historical,” individual productivity of the individual workers (i.e. not going to vary significantly in the next few weeks). The productivity improvement in the further storeys will only depend on the project-specific (and collective, for the crew) “learning” due, for example, to better coordination or to other issues that are progressively solved moving from the first storey to the following ones. So, the project-specific LC increases in a faster way than the individual one, and the overall productivity can be improved by accelerating the project-specific learning rate with more accurate project-specific design and management. Originality/value This paper enhances the understanding of the contributions that the learning effect of the individual worker and that of a crew repeating a given task (i.e. reinforced concrete operations) in a given project have on the productivity improvement for subsequent cycles of the repetitive construction process. This will contribute to improve the planning and control of site work activities, avoiding time and money wastefulness.

Avaliação Do Comportamento Das Curvas De Aprendizado De Soldadores: Produtividade Média Versus Produtividade Ideal

“…Tendo em vista que a "Produtividade Média" apresentou as melhores condições de ajuste, se avaliou o efeito da aprendizagem com base neste indicador. Assim, se observou, nas duas faixas de diâmetro, que não se houve melhoria da "Produtividade Média", o que está em desacordo com a literatura, tanto para a soldagem, quanto para outras atividades da indústria da construção (Ammar & Samy, 2015;Anzanello, 2004;Cadaval Júnior et al, 2013;(Pellegrino et al, 2012;Jarkas, 2016;(Pellegrino & Constantino, 2018;Raman & Varghese, 2016;Srour et al, 2016;Ralli et al, 2020). A melhoria da produtividade a partir do 10 o dia não se verificou (Martins, 2011;PROMINP, 2009).…”

“…A melhoria da produtividade a partir do 10 o dia não se verificou (Martins, 2011;PROMINP, 2009). Esperava-se que esta melhora viesse a ocorrer, ao menos, em função da aclimatação dos trabalhadores às condições do local de trabalho (Pellegrino & Constantino, 2018;Ralli et al, 2020). Cabe destacar, que a soldagem das juntas de tubulações são atividades individuais, dependem da habilidade de cada soldador e a amostra estudada considera a média diária dos soldadores e não produto de um trabalho de equipe.…”

“…A produtividade é um fator-chave para o crescimento econômico e a prosperidade em qualquer país (Vogl e Wahab, 2015;Arditi e Machtar, 2000;Kapelko, Horta, Camanho, & Lansink, 2015) além de impactar, decisivamente, no sucesso dos projetos de construção (Islam & Khadem, 2013;Mahamid, 2013;Loosemore, 2014;Pellegrino & Constantino, 2018).…”

Investigation and Comparative Analysis of Learning Curve Models on Construction Productivity: The Case of Caisson Fabrication Process

“…Therefore, it has been observed that when executing repetitive construction activities (e.g. high-rise building construction) each subsequent production cycle may be improved form a productivity stance due to the learning phenomenon that is developed in relation to the resources that are deployed in the project (Thomas et al, 1986;Panas and Pantouvakis, 2014;Pellegrino and Costantino, 2018;Srour et al, 2018). In other words, the productivity of repetitive tasks is improved as the experience of the deployed crews is increased (Pellegrino et al, 2012).…”

“…Taking into account learning phenomena when studying construction productivity enhances the accuracy of time and cost management (Lutz et al, 1994;Ammar and Abdel-Maged, 2018), improves project control and programming (Pellegrino et al, 2012), as well as provides the required scientific evidence for claiming lost workhours (Thomas, 2009). The impact of the learning effect on labor productivity is graphically expressed by the learning curves, which are quantitatively analyzed by mathematical models (Pellegrino and Costantino, 2018) known as the learning curve models.…”