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Ahmed Laaroussi, Bruno Fiès, Rémi Vankeisbelckt, Julien Hans

Ontology-aided FMEA for construction products

Abstract: The goal of improving the quality and the maintenance of building products, and the will to integrate the sustainable development objectives led us to propose an original method based on the use and adaptation of the Failure Modes Effects and Criticality Analysis (FMEA). This method relies among others on ontology use. It facilitates the FMEA proceeding. This paper aims to introduce innovative software specifically developed to perform more easily FMEA on building components. This software takes advantages of a structured knowledge base and an inference rule engine that allow a complete and formal description of the product to be analysed and an exhaustive analysis of all failures (degradations) that may occur.

Keywords: FMEA, ontological approach, knowledge capitalisation, degradation analysis, construction product

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Series: w78:2007 (browse)
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Alarcon L F, Bastias A

Computer aided strategic planning

Abstract: Modelling concepts developed to analyse project strategic decisions have been extended and implemented in a computer system leading to a generalised methodology that allows modelling and evaluation of strategic decisions in almost any decision area. Some recent application areas of this modelling system are: strategic planning, evaluation of environmental policy impacts and evaluation of risks in owner contractor relationships . The system uses concepts of cross-impact analysis and probabilistic inference as the core of the analysis procedure. A modular model structure and a simplified knowledge acquisition procedure has been designed to avoid the excessive cognitive demands imposed to the users by the original cross-impact methodology. A simple questioning process is used to guide the discussion and elicit information in an ordered manner. The result is a powerful but easy to use computer modelling system where managers, or other potential users, are not exposed to the complexities of the mathematical model. The computer system is implemented in a Windows 95 platform and it provides a graphical interface to help the users in building a conceptual model for the decision problem. The model is a simplified structure of the variables and interactions that influence the decisions being analysed. Influences and interactions assessed by experts or decisions makers are stored in a knowledge base. The system provides powerful analysis capabilities, such as: sensitivity analysis, to identify the most important variables in the decision problem; scenario analysis, to test decision under different environmental conditions; prediction of selected performance outcomes; risk analysis, to identify the risk involved in different alternatives; comparative analysis of the effects of alternative actions on individual or combined performance measures; explanatory capabilities through the model causal structure; etc. The computer model can translate expertise collected from multiple experts into a prediction of significant outcomes for decision-making. The model allows management to test different combinations of options and predict expected performance impacts associated with the decisions under analysis. The use of this decision-support tool can provide valuable insights on alternative options for strategic decision-making

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Full text: content.pdf (360,296 bytes) (available to registered users only)

Series: w78:1998 (browse)
Cluster: papers of the same cluster (result of machine made clusters)
Class: class.strategies (0.068425) class.impact (0.056619) class.environment (0.054697)
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Permission to reproduce these papers has been graciously provided by Royal Institute of Technology, Stockholm, Sweden. The assistance of the editors, Prof. Bo-Christer Björk and Dr. Adina Jägbeck, is gratefully appreciated.


C Changxin Wang,

Ontology based Knowledge Retrieving in a Web Collaboration Environment for Construction Industry

Abstract: As the amount of information and knowledge that we deal with in construction projects are huge, computerized collaboration and management systems have been seen as effective tools for construction project participants. While a vast amount of information and knowledge can be stored in these systems, how to retrieve knowledge when needed is a challenge. Traditional keyword search usually results in high returns but low precision, as context and terminology difference are not considered. This research implements construction domain ontology into a web collaboration environment. Domain ontology provides a common understanding of a domain (a particular area) in which people and the application system communicates with each other. The ontology is composed of a network of concepts, which are clearly defined and interlinked based on their context. Knowledge items published in the web are annotated according to the ontology, and enable the semantic inference to locate a particular knowledge items during the retrieval process. In this paper, some knowledge items (knowledge stories) are published as blog entries in the web collaboration systems, and a comparison between traditional keyword search and ontology based retrieval is reported. The ontology based knowledge retrieving gives much more accurate returns, and therefore can facilitate the web-based knowledge sharing practice more efficiently in the construction industry.

Keywords: Ontology, Knowledge management, Knowledge retrieving, Construction industry, Web-based collaboration.

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Series: w78:2011 (browse)
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Ciftcioglu O, Durmisevic S, Sariyildiz S

Soft computing in construction information technology

Abstract: Purpose: With this paper a data driven model of knowledge representation for use in construction information technology (CIT) is introduced as a novel implementation and it is effectively implemented by artificial intelligence methods. Although for CIT knowledge base systems as a general framework is available where the user can place the information. Such systems are eventually mere data warehouses or in a more sophisticated form they are decision support systems in the form of rule based expert systems. However, in the case of a framework structure to organise the knowledge base is difficult and cumbersome task to establish an effective product. In the case expert systems, the inference is deductive and therefore the effectiveness of the system is limited to the prescribed rules. Therefore in place of high level data base management software like Prolog ©, the integration of new computational information processing methods and technologies into CIT would be much informative and therefore they are much effective and finally desirable. From the viewpoint of computation, CIT the data are rather soft requiring special methods and techniques to deal with. In this respect, computational intelligence is one of the emerging technologies, which provides CIT with ample possibilities and techniques for the enhancement of CIT products. Computational intelligence is a part of artificial intelligence (AI) and can be defined as a branch of soft computing methodologies including Expert Systems, Fuzzy Logic, Artificial Neural Networks and Evolutionary Computation. Methodology: For the CIT data soft computing methods are invoked. Soft Computing is an emerging approach to computing which parallels the remarkable ability of the human mind to reason and learn in an environment of uncertainty and imprecision. In plain terms, it is the processing of uncertain information with the methods, methodologies, and paradigms of artificial NN, fuzzy logic and evolutionary algorithms. The equivalence of neural networks and fuzzy logic applications is well established. However, the effectiveness of either method is still dependent on the application itself. Each method has its strong merits. However, in general, best performance is obtained when both methods are used in hybrid form. Especially neural system can cope with complex systems while it is relatively difficult for fuzzy systems. On the contrary, it is easier to deal with linguistic variables by fuzzy systems. Such a hybrid model is implemented in the knowledge model accomplished. Results: A novel concept of soft computing in CIT is introduced using actual building design data for design evaluation. The knowledge base contains all the local and global information and their inherent relationships among themselves. The knowledge representation is performed by means of a series of fuzzy systems having their both fuzzy input space and output space. The associations between the spaces are established by learning techniques of AI using the data at hand. Such an 'intelligent' knowledge base can make inference resulting in 'intelligent' due outcomes, which are not explicitly coded, in advance. In other words this is an inductive and computational inference for decision-making compared to conventional knowledge base systems where inference is deductive prescribed by rules. Conclusions: The soft computing in CIT is an important step for processing the relevant effectively and efficiently. In this respect, the paper describes ongoing advanced research and its verifications by actual data at hand.

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Full text: content.pdf (204,669 bytes) (available to registered users only)

Series: w78:2001 (browse)
Cluster: papers of the same cluster (result of machine made clusters)
Class: class.analysis (0.064489) class.synthesis (0.025964) class.deployment (0.019220)
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Permission to reproduce these documents have been graciously provided by CSIR Building and Construction Technology. The assistance of the editors, Mr. Gustav Coetzee and Mr. Frances Boshoff, is gratefully appreciated.


H Kim, B Elhamim, H Jeong, C Kim, H Kim

On-Site Safety Management Using Image Processing and Fuzzy Inference

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Series: w78:2014 (browse)
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Jaggar D M

Expert system technology in construction management

Abstract: This paper describes the development of a micro computer aid driven by a suite of programs which allow the design identified solution for a given building project to be transposed into information reflecting the construction solution. The 'modus operandi' of the computer aid is the use of an Expert System which can access and manipulate data contained in a data base and to submit back to a data base, for subsequent user retrieval, information about the particular building project under consideration at various stages during its realization. The system is initiated by the creation of a design situation model which is held in a relational data base in the form of information concerning the descriptions and quantities of the finished work required to achieve the building project. The Expert System, through the logic contained in the inference engine, organises the design stated situation model describing the construction solution in terms of construction activities, the resources needed and their cost implications. Thus the system is intended to provide an interface between the product related design solution and the process related construction solution and has the aim of aiding the following: 1. Resource and financial management by design team 2. Resource and financial management by the construction team

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Full text: content.pdf (2,480,147 bytes) (available to registered users only)

Series: w78:1988 (browse)
Cluster: papers of the same cluster (result of machine made clusters)
Class: class.synthesis (0.058494) class.analysis (0.032486) class.man-software (0.018331)
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Permission to reproduce these documents has been graciously provided by the Lund University and the Swedish Building Centre. The assistance of the editors, Prof. Per Christiansson and Prof. Henry Karlsson, is gratefully appreciated.


Jørgensen K A

Product family modelling in the construction industry

Abstract: In general, the demand for customised products has increased radically and, as a result, the need for definition and specification of products by configuration has become more important than ever. This development is also related to the construction industry, where there is a clear interest in configuration of products related to building modelling. In this paper, an overview is given about the relationships between building models and product models and a methodology is presented for developing product family models, which are suitable for generation of advanced product configurators. A model of this kind contains definitions of different types of attributes, product modules and product components. The behaviour of the model is defined as different types of constraints and an inference algorithm.

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Full text: content.pdf (152,039 bytes) (available to registered users only)

Series: w78:2003 (browse)
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Permission to reproduce these papers has been graciously provided by the University of Auckland. The assistance of the editor who provided the full texts and the structured metadata, Dr. Robert Amor, is gratefully appreciated.


Shigenori Tanaka, Ichizou Mikami

A kbes combining cbr and rbr to select repalr and retftoflt methods for fatigue damage on steel bridges

Abstract: We have studied the knowledgebased expert system (KBES) to select repairing and retrofitting methods for fatigue damage of steel bridges. The case-based reasoning (CBR) system can solve the problem of howledge acquisition and perform efficient inference based on similar cases, w h e m the rulebased reasoning (RBR) system has the difficulty in acquiring knowledge bases. In the present paper, we constructed a KBES, in whicb CBR and RBR were combined, to select repairing and retrofitting methods for steel bridges‘ fatigue damage. The inference results obtained from this system are discussed to prove its usefulness, and subjects for the future are identified.

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Series: ecce:1997 (browse)
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