A system boundary-based critical review on crane selection in building construction

Abstract This study presented a system boundary-based review to systematically investigate the existing research on crane selection in building construction. The system boundary model comprised 9 boundary elements, namely year, location, research source, project height, project typology, crane type, selection constraint, selection criteria, and selection method. Three detailed analyses were carried out with reference to the boundary elements. Firstly, distribution analysis reflected an increasing research trend in crane selection worldwide. Secondly, regression analysis, considering 25 real cases, indicated that tower crane is better suited for high-rise building construction. Thirdly, systematic analysis identified a total of 19 constraints, 71 criteria, and 8 methods adopted for crane selection. Subsequently, the relationships between crane selection constraints and criteria were revealed. Furthermore, this study disclosed the selection differences between tower and mobile cranes, and the best practices in crane type and model selection. The main future research opportunities include i) using advanced AI technologies for crane type selection; ii) developing simulation models for tower crane model selection; iii) establishing a hybrid method for crane selection; and iv) extending the selection considerations to a larger spatio-temporal and functional scope.

[1]  W. Pan System boundaries of zero carbon buildings , 2014 .

[2]  David K. H. Chua,et al.  Optimizing Crane Selection and Location for Multistage Construction Using a Four-Dimensional Set Cover Approach , 2017 .

[3]  Cliff Schexnayder,et al.  Tower Crane Selection at Jonathon W. Rogers Surface Water Treatment Plant Expansion , 2002 .

[4]  Howard I. Shapiro,et al.  Cranes and Derricks , 1980 .

[5]  C. Henjewele,et al.  Construction Project Management , 2005 .

[6]  Mohamed Marzouk,et al.  Tower cranes layout planning using agent-based simulation considering activity conflicts , 2018, Automation in Construction.

[7]  Madhu C. Reddy,et al.  The influence of boundary objects on group collaboration in construction project teams , 2009, GROUP.

[8]  Myung-Houn Jang,et al.  Selection of a Tower Crane Using Augmented Reality in Smart Devices , 2013 .

[9]  Awad S. Hanna,et al.  A fuzzy logic approach to the selection of cranes , 1999 .

[10]  Mohamed Al-Hussein,et al.  An algorithm for mobile crane selection and location on construction sites , 2001 .

[11]  Mohamed Al-Hussein,et al.  Evolution of the crane selection and on-site utilization process for modular construction multilifts , 2014 .

[12]  Anil Sawhney,et al.  IntelliCranes: an integrated crane type and model selection system , 2001 .

[13]  Paul Cilliers,et al.  Boundaries , Hierarchies and Networks in Complex Systems , 2005 .

[14]  Kenneth D. Bailey,et al.  Boundary maintenance in living systems theory and social entropy theory , 2007 .

[15]  Aviad Shapira,et al.  AHP-Based Equipment Selection Model for Construction Projects , 2005 .

[16]  L. Bertalanffy General system theory : foundations, development, applications , 1977 .

[17]  Ali Kaveh,et al.  An Upgraded Sine Cosine Algorithm for Tower Crane Selection and Layout Problem , 2020 .

[18]  Mohamed Al-Hussein,et al.  An integrated decision support model for selecting the most feasible crane at heavy construction sites , 2018 .

[19]  C. Y. Peng,et al.  An Introduction to Logistic Regression Analysis and Reporting , 2002 .

[20]  Mohamed Al-Hussein,et al.  Innovative 3D‐modelling for selecting and locating mobile cranes , 2004 .

[21]  R. Gameson,et al.  Construction Conflict Management and Resolution , 1992 .

[22]  Wendy L. Currie,et al.  Rethinking Management Information Systems: An Interdisciplinary Perspective , 1999 .

[23]  Mohamed Al-Hussein,et al.  3D-Based Crane Evaluation System for Mobile Crane Operation Selection on Modular-Based Heavy Construction Sites , 2017 .

[24]  Claes Wohlin,et al.  Guidelines for snowballing in systematic literature studies and a replication in software engineering , 2014, EASE '14.

[25]  Dumitru Erhan,et al.  Deep Neural Networks for Object Detection , 2013, NIPS.

[26]  Carl T. Haas,et al.  An Interactive Database System with Graphical Linkage for Computer Aided Heavy Lift Planning , 1995 .

[27]  Aviad Shapira,et al.  Selection of mobile cranes for building construction projects , 1999 .

[28]  Otto Rentz,et al.  Scheduling of deconstruction projects under resource constraints , 2002 .

[29]  Christian Blum,et al.  Metaheuristics in combinatorial optimization: Overview and conceptual comparison , 2003, CSUR.

[30]  Kok Lay Teo,et al.  A review of methods and algorithms for optimizing construction scheduling , 2013, J. Oper. Res. Soc..

[31]  Mohamed Al-Hussein,et al.  Innovative System for Off-the-Ground Rotation of Long Objects Using Mobile Cranes , 2011 .

[32]  Won Kee Hong,et al.  Optimum Tower Crane Selection and Supporting Design Management , 2014 .

[33]  Uttpal Rai Identification of Constraints in Construction Projects to Improve Performance , 2021 .

[34]  Bo Xu,et al.  A BIM-based approach for automated tower crane layout planning , 2015 .

[35]  Aviad Shapira,et al.  “Soft” Considerations in Equipment Selection for Building Construction Projects , 2007 .

[36]  Yourong Li,et al.  Study on dynamic optimum design of tower crane structure , 2011, 2011 Second International Conference on Mechanic Automation and Control Engineering.

[37]  Mohamed Al-Hussein,et al.  Productivity and CO2 emission analysis for tower crane utilization on high-rise building projects , 2013 .

[38]  Colin S. Gray,et al.  A model for the selection of the optimum crane for construction sites , 1984 .

[39]  Mohamed Al-Hussein,et al.  Interactive and Dynamic Integrated Module for Mobile Cranes Supporting System Design , 2010 .

[40]  Jürgen Schmidhuber,et al.  Deep learning in neural networks: An overview , 2014, Neural Networks.

[41]  Thomas L. Saaty What is the analytic hierarchy process , 1988 .

[42]  A. Warszawski,et al.  An Expert System for Crane Selection and Location , 1987 .

[43]  Fernanda Leite,et al.  Exploring approaches to improve the performance of autonomous monitoring with imperfect data in location-aware wireless sensor networks , 2014, Adv. Eng. Informatics.

[44]  Peter Manning Environmental design as a routine , 1995 .

[45]  Dirk Briskorn,et al.  Survey of quantitative methods in construction , 2017, Comput. Oper. Res..

[46]  Vernon Ireland,et al.  Optimal Selection and Location of Tower Crane for the Construction of Prefabricated Buildings with Different Prefabrication Ratios , 2019 .

[47]  Fernanda Leite,et al.  Automated tower crane planning: leveraging 4-dimensional BIM and rule-based checking , 2018, Automation in Construction.

[49]  Gang Zhao,et al.  Boundary Characteristic Research of Green Manufacturing System , 2017 .

[50]  Xin Wang,et al.  Algorithm of Crane Selection for Heavy Lifts , 2011 .

[51]  J. Donalek,et al.  The interview in qualitative research. , 2005, Urologic nursing.

[52]  W. Pan Rethinking construction productivity theory and practice , 2018, Built Environment Project and Asset Management.

[53]  Colin Gray Crane Location and Selection by Computer , 1987 .

[54]  Faris M. AL-Oqla,et al.  Application of the Analytic Hierarchy Process (AHP) in Multi- Criteria Analysis of the Selection of Cranes , 2010 .

[55]  Mohamed Marzouk,et al.  Decision support for tower crane selection with building information models and genetic algorithms , 2016 .

[56]  Ulrich Hermann,et al.  Automated Crane Planning and Optimization for modular construction , 2018, Automation in Construction.

[57]  Anil Sawhney,et al.  Adaptive Probabilistic Neural Network-Based Crane Type Selection System , 2002 .

[58]  Simaan M. AbouRizk,et al.  Auction-based Simulation for Industrial Crane Operations , 2019, Automation in Construction.

[59]  Aviad Shapira,et al.  Culture of Using Mobile Cranes for Building Construction , 1996 .

[60]  Mohamed Al-Hussein,et al.  Optimization Algorithm for Selection and on Site Location of Mobile Cranes , 2005 .

[61]  Brian C. Cronk,et al.  How to Use SPSS® , 2019 .

[62]  Dirk Briskorn,et al.  Mixed-integer programming models for tower crane selection and positioning with respect to mutual interference , 2019, Eur. J. Oper. Res..

[63]  Mohamed Al-Hussein,et al.  D-CRANE: a database system for utilization of cranes , 2000 .

[64]  Colin S. Gray,et al.  A systematic approach to the selection of an appropriate crane for a construction site , 1985 .

[65]  Mohamed Al-Hussein,et al.  Utilization of 3D Visualization of Mobile Crane Operations for Modular Construction On-Site Assembly , 2015 .

[66]  Heng Li,et al.  Application of the analytic hierarchy process (AHP) in multi-criteria analysis of the selection of intelligent building systems , 2008 .

[67]  Dirk Briskorn,et al.  Covering polygons with discs: The problem of crane selection and location on construction sites , 2020 .

[68]  Mohamed Al-Hussein,et al.  Constructing a Complex Precast Tilt-Up-Panel Structure Utilizing an Optimization Model, 3D CAD, and Animation , 2007 .

[69]  Ming Wei Liu,et al.  An upper-bound pushover analysis procedure for estimating the seismic demands of high-rise buildings , 2004 .

[70]  A. Mysterud,et al.  Social constraints in cross-boundary collaborative deer management , 2018 .

[71]  Abraham Warszawski,et al.  Expert systems for crane selection , 1990 .

[72]  N. Luhmann,et al.  System as Difference , 2006 .

[73]  W. Pan,et al.  Rethinking system boundaries of the life cycle carbon emissions of buildings , 2018, Renewable and Sustainable Energy Reviews.