An Efficient Design Support System based on Automatic Rule Checking and Case-based Reasoning

A well building design support system can not only meet the rules but also automatically recommend the appropriate alternatives for designers, but most modifications now are conducted in the manual way. Although the method of automatic rule checking can effectively identify the compliance of rules in Building Information Modeling (BIM) models, recommendation supports are still lacked in applications. This paper aims to propose a design support system, using automatic rule checking to identify the compliance of rules and adopting case-based reasoning to provide recommendations via ontology and semantics. The AHP-TOPSIS (Analytic hierarchy process-Technique for Order Preference by Similarity to an Ideal Solution) method is used to give reliable recommendations rank. A real case is adopted as an illustrative example. Results show that the proposed system can increase the design efficiency in both design checking and modifying. Similar applications can be extended to other fields and rules.

[1]  Zenonas Turskis,et al.  Decision Making in Construction Management: AHP and Expert Choice Approach , 2017 .

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

[3]  Kyoo-Jin Yi,et al.  Scheduling-based risk estimation and safety planning for construction projects , 2006 .

[4]  Alex Delis,et al.  Automatic Fire-Code Checking Using Expert-System Technology , 1995 .

[5]  Zhiliang Ma,et al.  Ontology- and freeware-based platform for rapid development of BIM applications with reasoning support , 2017, Automation in Construction.

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

[7]  Song Wu,et al.  Construction risk knowledge management in BIM using ontology and semantic web technology , 2016 .

[8]  Ching-Lai Hwang,et al.  Methods for Multiple Attribute Decision Making , 1981 .

[9]  Charles M. Eastman,et al.  BIM-based fall hazard identification and prevention in construction safety planning , 2015 .

[10]  Abdul Kareem Almarshad,et al.  Case-based reasoning and BIM systems for asset management , 2015 .

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

[12]  Moses Olubayo Babatunde,et al.  A fuzzy-TOPSIS approach for techno-economic viability of lighting energy efficiency measure in public building projects , 2018 .

[13]  H. S. Byun,et al.  A decision support system for the selection of a rapid prototyping process using the modified TOPSIS method , 2005 .

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

[15]  Syahrul Nizam Kamaruzzaman,et al.  Ranking the indicators of building performance and the users’ risk via Analytical Hierarchy Process (AHP): Case of Malaysia , 2016 .

[16]  Paul Chinowsky,et al.  Exploiting Knowledge Management: The Engineering and Construction Perspective , 2006 .

[17]  Charles M. Eastman,et al.  Automatic rule-based checking of building designs , 2009 .

[18]  Chia-Chi Sun,et al.  A performance evaluation model by integrating fuzzy AHP and fuzzy TOPSIS methods , 2010, Expert Syst. Appl..

[19]  Ravi Kant,et al.  A fuzzy AHP-TOPSIS framework for ranking the solutions of Knowledge Management adoption in Supply Chain to overcome its barriers , 2014, Expert Syst. Appl..

[20]  Abdul Kareem Almarshad,et al.  A knowledge-based BIM system for building maintenance , 2013 .

[21]  Charles M. Eastman,et al.  Building Information Modeling (BIM) and Safety: Automatic Safety Checking of Construction Models and Schedules , 2013 .

[22]  Ramona Quattrini,et al.  Knowledge-based data enrichment for HBIM: Exploring high-quality models using the semantic-web , 2017 .

[23]  Li-Ru Chen,et al.  Measuring the Quality of Financial Electronic Payment System: Combined with Fuzzy AHP and Fuzzy TOPSIS , 2017 .

[24]  Daniela Fuchs-Hanusch,et al.  A bibliometric-based survey on AHP and TOPSIS techniques , 2017, Expert Syst. Appl..

[25]  Yusuf Tansel Iç,et al.  Development of a multi-level performance measurement model for manufacturing companies using a modified version of the fuzzy TOPSIS approach , 2018, Soft Comput..

[26]  Salman Nazari Shirkouhi,et al.  A fuzzy decision making methodology based on fuzzy AHP and fuzzy TOPSIS with a case study for information systems outsourcing decisions , 2017, J. Intell. Fuzzy Syst..

[27]  Ching-Lai Hwang,et al.  Multiple Attribute Decision Making: Methods and Applications - A State-of-the-Art Survey , 1981, Lecture Notes in Economics and Mathematical Systems.

[28]  Charles M. Eastman,et al.  Classification of rules for automated BIM rule checking development , 2015 .

[29]  Moumita Das,et al.  A BIM-based web service framework for green building energy simulation and code checking , 2014, J. Inf. Technol. Constr..

[30]  Ali GhaffarianHoseini,et al.  Application of nD BIM Integrated Knowledge-based Building Management System (BIM-IKBMS) for Inspecting the Post-construction Energy Efficiency , 2017 .

[31]  Charles M. Eastman,et al.  Implementation of a BIM Domain-specific Language for the Building Environment Rule and Analysis , 2015, J. Intell. Robotic Syst..