Learning Curves in Construction: A Critical Review and New Model

Srour, F. Jordan; Kiomjian, Daoud; Srour, Issam

doi:10.1061/(asce)co.1943-7862.0001096

Cited by 28 publications

(19 citation statements)

References 37 publications

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“…The increasing pressure on improving productivity of the construction industry in today’s global economic conditions justifies the bulk of studies developed on this topic in last years (Jordan Srour et al , 2015; Harrington and Johnston, 2016).…”

Section: Literature Reviewmentioning

confidence: 99%

An empirical investigation of the learning effect in concrete operations

Pellegrino

Costantino

2018

ECAM

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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.

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Section: Literature Reviewmentioning

confidence: 99%

An empirical investigation of the learning effect in concrete operations

Pellegrino

Costantino

2018

ECAM

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“…Based on the potential model, Srour et al (2016) developed a model named "Recursive Model", which considers the learning acquired in past projects as well as the processes of forgetting and mechanising production. They considered a graph based on unitary data, which allows a better analysis of the evolution of learning as opposed to the use of cumulative ECAM 30,2 data.…”

Section: Literature Reviewmentioning

confidence: 99%

Welder learning curves behaviour: “focus on welding productivity with the TIG process of marine platforms stainless steel pipes”

Macedo

Ferreira

2021

ECAM

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PurposeThe purpose of the study is to analyse the feasibility of using the potential and exponential curve models to assess the learning of a group of welders, when welding stainless steel piping with the tungsten inert gas process.Design/methodology/approachThe welding productivity data grouped according to the requirements of the ASME SECTION IX code is organised into two groups: average productivity and baseline productivity. When processing the adjustment to the two models, the Excel software Solver tool was used. The criteria for assessing the quality of the fit were: least squared method, Spearman's correlation coefficient and graphical method. The impact of the variation coefficient on the average productivity and the amplitude (difference between the minimum and maximum productivity) was also evaluated on the baseline productivity.FindingsThe curves elaborated based on the average productivity presented better quality of adjustment than those constructed from the baseline productivity. The potential and exponential models presented similar adjustment conditions, with the second having a slightly superior performance. There were no productivity gains due to learning in the studied time interval. The grouping of the average daily productivity data based on the diameter range established in the ASME code section IX presented satisfactory results, enabling its use by the industry.Originality/valueThere is no news of work on piping welding with this focus. The proposal to group the productivity data according to the degree of difficulty of execution established by the ASME code section IX, widely used in the industry, is a significant contribution to monitoring the evolution of learning. In the same way, the results allow to adopt the average productivity determined from the first 20 days of realisation of a project, as a reasonable indicator to estimate the future performance of the work, helping to correct deadlines during the realisation of a project.

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“…In a construction site, the application of the learning curve results in the project manager surely having a cost-saving because there is a reduction in the labor force needed for work that has been repetitively done over time [21]. The planning of construction projects, monitoring of progress, improvement of productivity and more which lead to further cost savings and control during the administering of construction contracts are the rewards that can be expected as the learning curve theory is applied in the construction industry [27]. The reduction in cost that is attributed to the learning curve effect is a result of a repetitive work in which fewer laborhours are necessary to produce a unit of work as the production of units continues to increase [16].…”

Section: Benefits Of Adopting the Learning Curve In The Construction mentioning

confidence: 99%

Learning Curve for Improved Productivity in the South African Construction Industry

Somila¹,

Nokulunga²,

Didibhuku³

et al. 2020

Proceedings of the Creative Construction E-Conference 2020

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The South African construction industry has battled with productivity for years despite being the key contributors to the economy of the country. This paper aims to remedy this problem by introducing the learning curve tool into the South African construction industry. The study sought to deduce the level of awareness of the learning curve and determine the benefits of adopting the learning curve tool in the South African construction industry. The Quantitative Methodology was adopted for this study and participation from construction professionals was obtained through a well-structured questionnaire. A total of 106 questionnaires were sent out and 62 were received back representing a response rate of 58.5%. The findings revealed that there is a moderate awareness of the learning curve tool in the South African construction industry. Additionally, the findings revealed that the workers would become familiar with their job and sharpen their skills which would result in a higher quality of construction work and the reduction of time taken to complete a task with reduced cost. The adoption of the learning curve tool in the South African construction industry offers a solution to a lasting problem of productivity in the industry. This study will enlighten construction professionals on the concept of the learning curve and the benefits of the learning curve.

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Learning Curves in Construction: A Critical Review and New Model

Cited by 28 publications

References 37 publications

An empirical investigation of the learning effect in concrete operations

An empirical investigation of the learning effect in concrete operations

Welder learning curves behaviour: “focus on welding productivity with the TIG process of marine platforms stainless steel pipes”

Learning Curve for Improved Productivity in the South African Construction Industry

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