Modelling Masonry Crew Productivity Using Two Artificial Neural Network Techniques

Gerek, İbrahim Halil; Erdiş, Ercan; Mıstıkoğlu, Gülgün; Usmen, Mumtaz

doi:10.3846/13923730.2013.802741

Cited by 28 publications

(27 citation statements)

References 22 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Artificial neural network methodologies, such as Feed Forward Neural Network (FFNN), Radial Basis Neural Network (RBNN), and Self Organizing Maps (SOM) were employed to model the relationship between the productivity output and selected input factors. The results of these studies have been disseminated in (Oral et al 2008(Oral et al , 2012Oral, E. L., Oral, M. 2010;Gerek et al 2014). This paper extends this work into the use of DEA for evaluating the performance of the plastering crews in terms of both productivity and efficiency, and then supplementing the findings by applying cross tabulation analysis.…”

Section: Introductionmentioning

confidence: 78%

Evaluation of Plastering Crew Performance in Building Projects Using Data Envelopment Analysis

Gerek

Erdiş

Mıstıkoğlu

et al. 2014

Technological and Economic Development of Economy

Self Cite

View full text Add to dashboard Cite

The research question addressed in this study was how the performance of construction crews working in a certain project or locality could be evaluated, ranked and improved. To develop and demonstrate the relevant framework, data envelopment analysis (DEA) was applied to establish the relative efficiency of plastering crews working in building projects located in different cities around Turkey. Data were collected from 40 crews of varying characteristics, and their technical efficiency scores were computed using the Banker, Charnes and Cooper (BCC) model, which is based on variable returns-to-scale (VRS). The model yields efficiency scores that range between 0 and 1, and a company or crew is considered efficient if its score is 1.0 (100%). Efficient and inefficient crews were identified and ranked on this basis in the study. Cross tabulation analyses were subsequently conducted to gain further insights into the relationships between the efficiency scores and input factors of numbers of skilled and unskilled laborers, daily labor unit costs, work hours, average age of crew members, total crew experience, plastering location, plastering technique, and plaster type. No discernible relationship could be identified between the efficiency scores and productivity outputs of the crews. It was found that plastering technique, plastering location, and total crew experience had a significant association with crew efficiency. Efficiency improvement strategies identified included training, hiring experienced plasterers, adopting more advanced plastering technology, implementing better jobsite management practices, and enhancing workers’ knowledge, skills and attitude towards productivity and quality.

show abstract

Section: Introductionmentioning

confidence: 78%

Evaluation of Plastering Crew Performance in Building Projects Using Data Envelopment Analysis

Gerek

Erdiş

Mıstıkoğlu

et al. 2014

Technological and Economic Development of Economy

Self Cite

View full text Add to dashboard Cite

show abstract

“…Productivity is generally used to describe how the relationship between output and input that is related in the production process (Liou, 1986;Gerek, et al, 2015). In the construction industry, productivity is often referred to as labour productivity (Hajikazemi, et al, 2017).…”

Section: Literature Review Labour Productivitymentioning

confidence: 99%

Construction Labour Productivity on Campus Project in Palembang, Indonesia

Nurhendi¹,

Khoiry²,

Hamzah³

2021

ITII

View full text Add to dashboard Cite

Contruction labour productivity has relationship to determine the successful implementation of the construction project schedule. By looking at the importance of labour productivity in construction projects, this study aims to analyze labour productivity in construction projects on one campus in the city of Palembang, Indonesia. The campus is Universitas Islam Negeri Raden Fatah Palembang. This research method is work sampling method. Observations of work activities carried out paying attention to periods of time, namely during and after the month of Ramadan. The result show labours do work effectively, but construction labour productivity still needs to be improved, especially in flooring and scafolding works. This research also consludes labour productivity in months other than Ramadan is higher than labour productivity during Ramadan.

show abstract

“…Meanwhile this industry faces many challenges like time overrun, cost overrun, construction waste generation and management, health and safety challenges are the key challenges faced by this industry; however there is one predominant challenge of labor production which is the key concern for this industry (Oladiran, O. J. and Onatayo, D. 2019). labour production is severe concern which gives birth to time overrun and cost overrun problems within the construction projects (Gerek, İ. H., Erdis, E., Mistikoglu, G. & Usmen, M. 2015). Construction productivity is affected because of multiple factors and different causes.…”

Section: Introductionmentioning

confidence: 99%

Building Construction Labour Productivity in Arid Climate Environment

Bhatti

Abdullah

Nagapan

et al. 2019

Journal of Applied Engineering Sciences

View full text Add to dashboard Cite

Productivity is a significant aspect of construction industry that plays vital role for success and failure of any construction project. This industry generates 11% to 13% of GDP all around the globe and the cost of labour in any building project is 20% to 35% of the cost of Building. On daily basis labour utilizes 30% of time on productive activities rest 70% of the time is ruined in non-productive activities, there are multi factors which are affecting the labour production in construction industry hence this study provides an overview of productivity, Total Factor productivity, method used to measure accurate productivity in construction projects. The objective of this study is find out percentage up to what extent labour production is affected due to weather conditions, however this study is carried out in arid climate region in Month of June 2018, where minimum temperature was recorded 26.0 Celsius degree at 7:30 AM and Maximum was 47.80 Celsius degree at 3:00 PM. A descriptive survey research design approach was adopted using continuous observation method of study. Project work study manual served as the research instrument to collect the data on selected building sites for 30 working days. Data collected were analyzed using descriptive statics. The results show that average monthly production of mason gang was recorded with less production of 28.759%, Carpentry gang with average monthly loss of production 16.74% & steel fixer gang had average monthly loss of production was 12.188. This concludes that prior to signing the contract for construction project. The location, environment, topography of region, capacity of construction operatives must be kept in mind to decide the proper timeline for the successful of project.

show abstract

Modelling Masonry Crew Productivity Using Two Artificial Neural Network Techniques

Cited by 28 publications

References 22 publications

Evaluation of Plastering Crew Performance in Building Projects Using Data Envelopment Analysis

Evaluation of Plastering Crew Performance in Building Projects Using Data Envelopment Analysis

Construction Labour Productivity on Campus Project in Palembang, Indonesia

Building Construction Labour Productivity in Arid Climate Environment

Contact Info

Product

Resources

About