An intelligent simulation-based framework for automated planning of concrete construction works

PurposeThis paper proposes an innovative intelligent simulation-based construction planning framework that introduces a new approach to simulation-based construction planning.Design/methodology/approachIn this approach, the authors developed an ontological inference engine as an integrated part of a constraint-based simulation system that configures the construction processes, defines activities and manages resources considering a variety of requirements and constraints during the simulation. It allows for the incorporation of the latest project information and a deep level of construction planning knowledge in the planning. The construction planning knowledge is represented by an ontology and several semantic rules. Also, the proposed framework uses the project building information model (BIM) to extract information regarding the construction product and the relations between elements. The extracted information is then converted to an ontological format to be useable by the framework.FindingsThe authors implemented the framework in a case study project and tested its usefulness and capabilities. It successfully generated the construction processes, activities and required resources based on the construction product, available resources and the planning rules. It also allowed for a variety of analyses regarding different construction strategies and resource planning. Moreover, 4D BIM models that provide a very good understanding of the construction plan can be automatically generated using the proposed framework.Originality/valueThe active integration between BIM, discrete-event simulation (DES) and ontological knowledge base and inference engine defines a new class of construction simulation with expandable applications.

[1]  Martin Fischer,et al.  Method to produce field instructions from product and process models for cast-in-place concrete operations , 2009 .

[2]  Amr A. Oloufa,et al.  Algorithms for automated deduction of topological information , 2005 .

[3]  Paavo Kotinurmi,et al.  A review of XML-based supply-chain integration , 2004 .

[4]  Ernst Rank,et al.  Bridge construction schedule generation with pattern-based construction methods and constraint-based simulation , 2010, Adv. Eng. Informatics.

[5]  Noel Painting,et al.  Scientometric analysis of BIM-based research in construction engineering and management , 2019, Engineering, Construction and Architectural Management.

[6]  Mehdi Tavakolan,et al.  Automated Planning of Building Construction Considering the Amount of Available Floor Formwork , 2016 .

[7]  Pieter Pauwels,et al.  Semantic web technologies in AEC industry: A literature overview , 2017 .

[8]  Mehdi Tavakolan,et al.  Construction and Resource Short-Term Planning Using a BIM-Based Ontological Decision Support System , 2020 .

[9]  Xiaolong Xue,et al.  Failure Caused by Inappropriate Construction Methods: An Expensive Lesson , 2013 .

[10]  Esmatullah Noorzai,et al.  BIM-Based Combination of Takt Time and Discrete Event Simulation for Implementing Just in Time in Construction Scheduling under Constraints , 2020 .

[11]  David K. H. Chua,et al.  Automated construction sequencing and scheduling from functional requirements , 2013 .

[12]  Richard J. Mayer,et al.  Using Ontologies for Simulation Modeling , 2006, Proceedings of the 2006 Winter Simulation Conference.

[13]  Jochen Teizer,et al.  Ontology-based semantic modeling of construction safety knowledge: Towards automated safety planning for job hazard analysis (JHA) , 2015 .

[14]  Wei-Chih Wang,et al.  Integrating building information models with construction process simulations for project scheduling support , 2014 .

[15]  Markus König,et al.  Constraint-based simulation of outfitting processes in building engineering , 2007 .

[16]  Burcu Akinci,et al.  Proactive Productivity Management at Job Sites: Understanding Characteristics of Assumptions Made for Construction Processes during Planning Based on Case Studies and Interviews , 2014 .

[17]  L. Madrazo,et al.  Connecting building component catalogues with BIM models using semantic technologies: an application for precast concrete components , 2015 .

[18]  Markus König,et al.  Recognition of process patterns for BIM-based construction schedules , 2017, Adv. Eng. Informatics.

[19]  Pieter Pauwels,et al.  EXPRESS to OWL for construction industry: Towards a recommendable and usable ifcOWL ontology , 2016 .

[20]  Mohamed Al-Hussein,et al.  BIM-based integrated approach for detailed construction scheduling under resource constraints , 2015 .

[21]  Kincho H. Law,et al.  An ontology-based web service framework for construction supply chain collaboration and management , 2015 .

[22]  Luh-Maan Chang,et al.  A framework for an automated and integrated project scheduling and management system , 2013 .

[23]  Raimar J. Scherer,et al.  Construction processes configuration using process patterns , 2012, Adv. Eng. Informatics.

[24]  Wei Zhang,et al.  Causes of delays in the construction phase of Chinese building projects , 2018, Engineering, Construction and Architectural Management.

[25]  Cletus Moobela,et al.  Profiling causative factors leading to construction project delays in the United Arab Emirates , 2017 .

[26]  Sheryl Staub-French,et al.  Ontology-based feature modeling for construction information extraction from a building information model , 2013 .

[27]  Luh-Maan Chang,et al.  Simulation and analytical techniques for construction resource planning and scheduling , 2012 .

[28]  Frank van Harmelen,et al.  Web Ontology Language: OWL , 2004, Handbook on Ontologies.

[29]  Chung-Wei Feng,et al.  Using the MD CAD model to develop the time–cost integrated schedule for construction projects , 2010 .

[30]  Jung-Ho Yu,et al.  BIM and ontology-based approach for building cost estimation , 2014 .

[31]  George Agyekum-Mensah,et al.  The professionals’ perspective on the causes of project delay in the construction industry , 2017 .

[32]  Björn Johansson,et al.  A methodology for input data management in discrete event simulation projects , 2008, 2008 Winter Simulation Conference.

[33]  Peter E.D. Love,et al.  An ontological approach for technical plan definition and verification in construction , 2015 .

[34]  Hyunjoo Kim,et al.  Generating construction schedules through automatic data extraction using open BIM (building information modeling) technology , 2013 .

[35]  Mohamed Al-Hussein,et al.  An automatic scheduling approach: building information modeling-based onsite scheduling for panelized construction , 2014 .

[36]  Steffen Staab,et al.  What Is an Ontology? , 2009, Handbook on Ontologies.

[37]  David Greenwood,et al.  The adoption of 4D BIM in the UK construction industry: an innovation diffusion approach , 2017 .

[38]  Sven Spieckermann,et al.  Intelligent BIM-based construction scheduling using discrete event simulation , 2012, Proceedings Title: Proceedings of the 2012 Winter Simulation Conference (WSC).

[39]  Karl Beucke,et al.  Automated Generation of Construction Schedules based on the IFC Object Model , 2009 .

[40]  Thomas Olofsson,et al.  Building information modeling and discrete event simulation: Towards an integrated framework , 2014 .

[41]  Issa J. Ramaji,et al.  Investigation of Leveraging BIM Standards to Facilitate Sustainability Evaluations from Early Stages of Design , 2017 .

[42]  Jun Wang,et al.  A review of integrated applications of BIM and related technologies in whole building life cycle , 2020 .

[43]  David Arditi,et al.  Delay analysis in construction projects with no updated work schedules , 2020 .

[44]  Michael Healy,et al.  Theory and Applications of Ontology: Computer Applications , 2010 .

[45]  Karl Beucke,et al.  Knowledge-based schedule generation and evaluation , 2010, Adv. Eng. Informatics.

[46]  Zhipeng Zhou,et al.  Overview and Analysis of Ontology Studies Supporting Development of the Construction Industry , 2016, J. Comput. Civ. Eng..

[47]  Kuan Yew Wong,et al.  Comparison of Two Simulation Software for Modeling a Construction Process , 2011, 2011 Third International Conference on Computational Intelligence, Modelling & Simulation.

[48]  Simaan M. AbouRizk,et al.  Role of Simulation in Construction Engineering and Management , 2010 .

[49]  Charalampos Siristatidis,et al.  Artificial Intelligence in IVF: A Need , 2011, Systems biology in reproductive medicine.

[50]  Don V. Kerr.  Factors influencing the Development and Adoption of Knowledge Based Decision Support Systems for Small, Owner-Operated Rural Business , 2004, Artificial Intelligence Review.