Improving performance and the reliability of off-site pre-cast concrete production operations using simulation optimisation

Hdl Handle:
http://hdl.handle.net/10149/107461
Title:
Improving performance and the reliability of off-site pre-cast concrete production operations using simulation optimisation
Authors:
Al-Bazi, A. F. J. (Ammar); Dawood, N. N. (Nashwan); Dean, J. T. (John)
Affiliation:
University of Teesside. School of Science and Technology (SST). Centre for Construction Innovation Research (CCIR).
Citation:
Al-Bazi, A. F. J., Dawood, N. N. and Dean, J. T. (2010) 'Improving performance and the reliability of off-site pre-cast concrete production operations using simulation optimisation', Journal of Information Technology in Construction, 15, pp.335-336.
Publisher:
International Council for Research and Innovation in Building and Construction
Journal:
Journal of Information Technology in Construction
Issue Date:
Jul-2010
URI:
http://hdl.handle.net/10149/107461
Additional Links:
http://www.itcon.org/2010/25
Abstract:
The increased use of precast components in building and heavy civil engineering projects has led to the introduction of innovative management and scheduling systems to meet the demand for increased reliability, efficiency and cost reduction. The aim of this study is to develop an innovative crew allocation system that can efficiently allocate crews of workers to labour-intensive repetitive processes. The objective is to improve off-site pre-cast production operations using Multi-Layered Genetic Algorithms. The Multi-Layered concept emerged in response to the modelling requirements of different sets of labour inputs. As part of the techniques used in developing the Crew Allocation “SIM_Crew” System, a process mapping methodology is used to model the processes of precast concrete operations and to provide the framework and input required for simulation. Process simulation is then used to model and imitate all production processes, and Genetic Algorithms are embedded within the simulation model to provide a rapid and intelligent search. A Multi-Layered chromosome is used to store different sets of inputs such as crews working on different shifts and process priorities. A ‘Class Interval’ selection strategy is developed to improve the chance of selecting the most promising chromosomes for further investigation. Multi-Layered Dynamic crossover and mutation operators are developed to increase the randomness of the searching mechanism for solutions in the solution space. The results illustrate that adopting different combinations of crews of workers has a substantial impact on the labour allocation cost and this should lead to increased efficiency and lower production cost. In addition, the results of the simulation show that minimum throughput time, minimum process-waiting time and optimal resource utilisation profiles can be achieved when compared to a real-life case study.
Type:
Article
Language:
en
Keywords:
construction supply-chain; multi-layered genetic algorithms; simulation modelling; crew allocation system; precast industry
ISSN:
1874-4753
Rights:
ITcon is an Open Access journal and its articles can freely and with no charge be read by anybody who has an Internet connection. The copyright of the articles remains with the authors, from the start of 2009 using the Creative Commons standard licence. For full details see http://itcon.org/cgi-bin/news/Show?_id=11 [Accessed 12/07/2010]
Citation Count:
0 [Web of Science and Scopus, 12/07/2010]

Full metadata record

DC FieldValue Language
dc.contributor.authorAl-Bazi, A. F. J. (Ammar)en
dc.contributor.authorDawood, N. N. (Nashwan)en
dc.contributor.authorDean, J. T. (John)en
dc.date.accessioned2010-07-12T09:54:09Z-
dc.date.available2010-07-12T09:54:09Z-
dc.date.issued2010-07-
dc.identifier.citationJournal of Information Technology in Construction; 15:335-336en
dc.identifier.issn1874-4753-
dc.identifier.urihttp://hdl.handle.net/10149/107461-
dc.description.abstractThe increased use of precast components in building and heavy civil engineering projects has led to the introduction of innovative management and scheduling systems to meet the demand for increased reliability, efficiency and cost reduction. The aim of this study is to develop an innovative crew allocation system that can efficiently allocate crews of workers to labour-intensive repetitive processes. The objective is to improve off-site pre-cast production operations using Multi-Layered Genetic Algorithms. The Multi-Layered concept emerged in response to the modelling requirements of different sets of labour inputs. As part of the techniques used in developing the Crew Allocation “SIM_Crew” System, a process mapping methodology is used to model the processes of precast concrete operations and to provide the framework and input required for simulation. Process simulation is then used to model and imitate all production processes, and Genetic Algorithms are embedded within the simulation model to provide a rapid and intelligent search. A Multi-Layered chromosome is used to store different sets of inputs such as crews working on different shifts and process priorities. A ‘Class Interval’ selection strategy is developed to improve the chance of selecting the most promising chromosomes for further investigation. Multi-Layered Dynamic crossover and mutation operators are developed to increase the randomness of the searching mechanism for solutions in the solution space. The results illustrate that adopting different combinations of crews of workers has a substantial impact on the labour allocation cost and this should lead to increased efficiency and lower production cost. In addition, the results of the simulation show that minimum throughput time, minimum process-waiting time and optimal resource utilisation profiles can be achieved when compared to a real-life case study.en
dc.language.isoenen
dc.publisherInternational Council for Research and Innovation in Building and Construction-
dc.relation.urlhttp://www.itcon.org/2010/25en
dc.rightsITcon is an Open Access journal and its articles can freely and with no charge be read by anybody who has an Internet connection. The copyright of the articles remains with the authors, from the start of 2009 using the Creative Commons standard licence. For full details see http://itcon.org/cgi-bin/news/Show?_id=11 [Accessed 12/07/2010]en
dc.subjectconstruction supply-chainen
dc.subjectmulti-layered genetic algorithmsen
dc.subjectsimulation modellingen
dc.subjectcrew allocation systemen
dc.subjectprecast industryen
dc.titleImproving performance and the reliability of off-site pre-cast concrete production operations using simulation optimisationen
dc.typeArticleen
dc.contributor.departmentUniversity of Teesside. School of Science and Technology (SST). Centre for Construction Innovation Research (CCIR).en
dc.identifier.journalJournal of Information Technology in Constructionen
ref.citationcount0 [Web of Science and Scopus, 12/07/2010]en
or.citation.harvardAl-Bazi, A. F. J., Dawood, N. N. and Dean, J. T. (2010) 'Improving performance and the reliability of off-site pre-cast concrete production operations using simulation optimisation', Journal of Information Technology in Construction, 15, pp.335-336.-
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