Aminah Robinson Fayek

Risk Management in the Construction Industry Using Combined Fuzzy FMEA and Fuzzy AHP

Failure mode and effect analysis (FMEA) is recognized as one of the most beneficial techniques in reliability programs. FMEA is a structured technique that can help in identifying all failure modes within a system, assessing their impact, and planning for corrective actions. Although this technique has been widely used in many industries, it has some limitations. The purpose of this paper is to extend the application of FMEA to risk management in the construction industry. Fuzzy logic and fuzzy analytical hierarchy process (AHP) are used to address the limitations of traditional FMEA. In essence, this method explores the concept of fuzzy expert systems to map the relationship between impact (I), probability of occurrence (P), and detection/control (D) and the level of criticality of risk events. A case study is presented to validate the concept. The results obtained confirm the capability of fuzzy FMEA and fuzzy AHP to address several drawbacks of the traditional FMEA application. The use of this approach can support the project management team to establish corrective actions in a timely manner.

Fuzzy Monte Carlo Simulation and Risk Assessment in Construction

Monte Carlo simulation has been used extensively for addressing probabilistic uncertainty in range estimating for construction projects. However, subjective and linguistically expressed information results in added non-probabilistic uncertainty in construction management. Fuzzy logic has been used successfully for representing such uncertainties in construction projects. In practice, an approach that can handle both random and fuzzy uncertainties in a risk assessment model is necessary. This article discusses the deficiencies of the available methods and proposes a Fuzzy Monte Carlo Simulation (FMCS) framework for risk analysis of construction projects. In this framework, a fuzzy cumulative distribution function constructed as a novel way to represent uncertainty. To verify the feasibility of the FMCS framework and demonstrate its main features, the authors have developed a special purpose simulation template for cost range estimating. This template is employed to estimate the cost of a highway overpass project.

Initial metrics and pilot program results for measuring the performance of the Canadian construction industry

A study has been initiated by the Canadian Construction Innovation Council to support the measurement of the performance of the Canadian construction industry. Metrics have been established to cover aspects of cost, time, scope, quality, safety, innovation, and sustainability. The metrics were piloted with industry partners and applied to institutional building and infrastructure projects. The metrics were selected in recognition of other national and international efforts in benchmarking and with a view of supporting analysis at the project, organization, and industry level. The experience gained through the pilot project indicates that the metrics are reasonably well understood in their definition. While the cost, time, scope, and safety information is readily available, as expected, the information for quality innovation and sustainability is not or requires more detailed in-person interviews of project participants to obtain a complete picture of project performance. The data analysis and presentation...

A Survey of Tendering Practices in the Australian Construction Industry

AbstractThis paper presents the findings of a survey of the tendering practices of Australian civil engineering construction contractors. Common practices in assessing risks and opportunities, assessing the competition, setting margin, and developing competitive tendering strategies are discussed. A major conclusion is that much of the process is subjective and based on experienced judgement. Assessing the competition is almost always done on an informal basis without using historical competitor data. The margin-size decision (i.e. corporate overhead and profit) is usually done in the final few hours prior to tender submission with little or no formal methods of analysis. Most of the time, effort, and decision-making are directed towards estimating the direct costs, in formulating the construction methodology and design alternatives, and in assessing the risks and opportunities.

Fuzzy Reliability Analyzer: Quantitative Assessment of Risk Events in the Construction Industry Using Fuzzy Fault-Tree Analysis

Fault trees are deductive techniques constructed by taking a system failure event and deconstructing it into its root causes (basic events, gate events). Fault trees can be solved qualitatively, by determining minimal cut sets, and quantitatively, by calculating the probability of occurrence of the risk event. In conventional fault-tree analysis (FTA), the probability of occurrence for all basic events must be assessed in order to allow for quantitative fault-tree analysis. However, conducting quantitative fault-tree analysis, especially in construction projects, entails several difficulties owing to the lack of sufficient data, leading to an approximation of the probability of occurrence for some basic events. Assuming probabilities for any basic event will add further uncertainty to the analysis, resulting in a potentially questionable end result. To overcome the challenge of assessing probabilities, this paper presents a comprehensive framework in which experts can use linguistic terms rather than numerals to assess the probability of occurrence of basic events. Fuzzy arithmetic operations are used to perform quantitative fault-tree analysis. Fuzzy Reliability Analyzer (FRA) was developed to automate both qualitative and quantitative FTA. The method presented is demonstrated via a case study to quantify the probability of failure of horizontal directional drilling (HDD) in meeting project objectives. Fourteen minimal cut sets were identified and the fuzzy probability (FPro) of the top event (TE) was calculated. The proposed approach offers the advantage of allowing experts to express themselves linguistically to assess the probability of occurrence of basic events, which is more appropriate for the construction domain. In addition, the proposed method offers the risk analyst the advantage of ranking basic events according to their level of contribution to the probability of the risk event, which can help in establishing more effective risk response strategies.

Comprehensive Hybrid Framework for Risk Analysis in the Construction Industry Using Combined Failure Mode and Effect Analysis, Fault Trees, Event Trees, and Fuzzy Logic

AbstractThe nature of the construction industry is characterized by many risks and uncertainty inherent in every phase of the project life cycle. Risk management, therefore, is essential for a construction project to succeed in fulfilling its project objectives. In conventional event-tree analysis, the probability of the risk event, the probability of failure/success of different mitigation strategies, and the consequences of different paths must be assessed to allow for quantitative event-tree analysis. However, conducting quantitative event-tree analysis, especially in construction projects, entails several difficulties attributed to the lack of sufficient data. To overcome this challenge, this paper presents a comprehensive framework in which experts can use linguistic terms rather than numerical values to conduct event-tree analysis and calculate the expected monetary value (EMV) of risk events. The proposed framework is based on combining failure mode and effect analysis (FMEA), fault trees, event tr...

Methodology for integrating fuzzy expert systems and discrete event simulation in construction engineering

This paper demonstrates how fuzzy expert systems can be integrated within discrete event simulation models to enhance their modeling and predictive capabilities for construction engineering applications. A proposed methodology is presented for extracting the information from experts to develop the fuzzy expert system rules. The developed fuzzy expert system is integrated within a discrete event simulation model to enhance its modeling capability by explicitly accounting for the different factors affecting some of the simulation activities. A tunneling case study is used to illustrate the features of the integrated system. The outputs generated from the integrated system are very comparable to those from the original probabilistic simulation model. The integrated system represents a more realistic modeling scenario, since it thoroughly accounts for the different factors affecting the tunnel boring machine (TBM) advance rate. This paper is relevant to researchers because it provides an advance in combining ...

Fuzzy Similarity Consensus Model for Early Alignment of Construction Project Teams on the Extent of Their Roles and Responsibilities

A fuzzy similarity consensus (FSC) model is presented for alignment of construction project owner and contractor project teams to their roles and responsibilities, identifying and reducing fundamental problems of conflicts, duplication, and gaps in roles and responsibilities as early as the project initiation stage. The model achieves its objective by incorporating consensus and quality of construction project teams in aggregating their opinions to decide on the party responsible for every standard task of a construction project. The roles and responsibilities of the owner and contractors are described to different extents using seven linguistic terms defined by triangular membership functions and constructed using a three-step Delphi approach, which allows experts to develop common understanding of the meaning of the terms by determining their overlap on a fuzzy linguistic scale. A modified similarity aggregation method (SAM) aggregates experts’ opinions in a linguistic framework using a consensus weight...

SuretyAssist: Fuzzy Expert System to Assist Surety Underwriters in Evaluating Construction Contractors for Bonding

In construction, many owners mitigate the risk of unforeseen contractor default by accepting only bonded contractors who must endure a rigorous evaluation process by surety brokers and surety underwriters. This evaluation process includes a financial analysis and a review of work on hand and past performance, all of which have reliable structured methods for their evaluation. Additionally, a number of subjective criteria are considered that are more difficult to capture and assess objectively but which can be modeled effectively using fuzzy logic. The purpose of this paper is to illustrate how fuzzy logic and expert systems can be combined to provide a structured approach to evaluating contractors for surety underwriting purposes. Fuzzy logic is used to model both the objective and subjective factors considered in contractor evaluation using linguistic terms, and expert rules are used to capture the surety experts’ reasoning process. A fuzzy expert system, SuretyAssist, is presented that can be used to pr...

Predicting and Evaluating Construction Trades Foremen Performance: Fuzzy Logic Approach

This paper illustrates a fuzzy logic model for use in predicting and evaluating the performance of construction trades foremen. The model assists in measuring the effectiveness of a foreman, monitoring improvements in effectiveness over time, and identifying areas where a foreman requires training or mentoring to improve his/her performance. This paper also discusses the factors that affect the performance of a foreman in each area of responsibility. The structure of the model and the use of fuzzy logic are described. The model is validated using data collected from an actual construction company, illustrating its high level of linguistic accuracy. This model is relevant to researchers and makes a contribution to performance evaluation by developing a methodology for evaluating and predicting the performance of construction trades foremen. The model provides a complete approach for handling uncertainty inherent in performance evaluation by using fuzzy logic. The use of fuzzy logic in the model allows users to express themselves linguistically and to make assessments that are subjective in nature. It is relevant to construction industry practitioners since it provides them with a useful technique for evaluating the performance of foremen and identifying the factors that affect their performance on a daily basis. Last, the model offers the advantage of benchmarking foreman performance, allowing organizations to develop plans to improve the performance of their foremen over time.