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.     

Construction Project Risk Assessment Using Existing Database and Project-Specific Information

This paper develops a risk assessment methodology for construction projects by combining existing large quantities of data and project-specific information through updating approaches. Earlier studies have indicated that risk assessment is still difficult for practicing engineers to use due to the requirement of data on too many input variables. However, the availability of existing large quantities of data and project-specific information makes it possible to simplify the risk assessment procedure. Two main ideas are pursued in this paper to facilitate practical implementation: identify and evaluate the critical risk events, and develop a systematic updating methodology. Both epistemic and aleatory types of uncertainties in the data are considered, and corresponding updating procedures are developed. The proposed methodology is illustrated for the construction risk assessment of a cable-stayed bridge.     

Fuzzy Analytical Hierarchy Process Risk Assessment Approach for Joint Venture Construction Projects in China

Research and practice show that construction joint venture (JV) activities in China are opportunities that can bring potential benefits but at the same time may generate many risks. While research has studied these risks and presented useful advice for managing individual risks, the methodologies used to analyze the risks were mainly qualitatively based, and there is a gap in using the quantitative method that can integrate a risk expert’s knowledge to assess the risks associated with JV projects. This paper sets up a hierarchy structure of the risks and then develops a fuzzy analytical hierarchy process (AHP) model for the appraisal of the risk environment pertaining to the JVs to support the rational decision making of project stakeholders. An empirical case study is used to demonstrate the application of the proposed fuzzy AHP model. It is concluded that the fuzzy AHP model is effective in tackling the risks involved in JV projects. The information presented in this paper should be shown to all parties considering JV business opportunities in China, and the proposed approach should be applicable to the research and analysis of risks associated with any type of construction projects.     

Risk Management in the Chinese Construction Industry

There has been an increase in research on risk management practice in the construction industry. However, little research has been conducted to systematically investigate the overall aspects of risk management on the perspectives of various project participants. This paper reports the findings of an empirical Chinese industry survey on the importance of project risks, application of risk management techniques, status of the risk management system, and the barriers to risk management, which were perceived by the main project participants. The risk management strategies adopted in the Three Gorges Project were also studied. The study reveals that: Most project risks are commonly of concern to project participants; the industry has shifted from risk transfer to risk reduction; current risk management systems are inadequate to manage project risks; and lack of joint risk management mechanisms is the key barrier to adequate risk management. Future studies should be conducted to systematically improve the risk management in construction by different approaches that facilitate equitable sharing of rewards through effective risk management among participants. Such studies should also consider the establishment of an open communication risk management process to permit the corporate experience of all participants, as well as their personal knowledge and judgment, to be effectively utilized.     

Predicting Industrial Construction Labor Productivity Using Fuzzy Expert Systems

The objective of this technical note is to illustrate the application of fuzzy expert systems to the modeling of a practical problem—that of predicting the labor productivity of two common industrial construction activities: rigging pipe and welding pipe. This note illustrates how to develop and test such a model, given the realistic constraints of subjective assessments, multiple contributing factors, and limitations on data sets. The factors that affect the productivity of each activity are identified, and fuzzy membership functions and expert rules are developed. The models are validated using data collected from an actual construction project. The resulting models are found to have high linguistic prediction accuracies. This note is of relevance to researchers by demonstrating how a fuzzy expert system can be developed and tested. It is of relevance to industry practitioners by illustrating how fuzzy logic and expert systems modeling can be exploited to help them solve real world problems.     

Object-Oriented Evolutionary Fuzzy Neural Inference System for Construction Management

Problems in construction management are complex, full of uncertainty, and vary with environment. Fuzzy logic, neural networks, and genetic algorithms (GAs) have been successfully applied in construction management to solve various kinds of problems. Considering the characteristics and merits of each method, this paper combines the above three techniques to develop an Evolutionary Fuzzy Neural Inference Model (EFNIM). Integrating these three methods, the EFNIM uses GAs to simultaneously search for the fittest membership functions with the minimum fuzzy neural network (FNN) structure and optimum parameters of FNN. Thus, the best adaptation mode is automatically identified. Furthermore, this research work integrates the EFNIM with an object-oriented (OO) computer technique to develop an OO Evolutionary Fuzzy Neural Inference System for solving construction management problems. Simulations are conducted to demonstrate the application potential of the EFNIS. This system could be used as a multifarious intelligent decision support system for decision-making to solve manifold construction management problems.     

Overview of the Application of “Fuzzy Techniques” in Construction Management Research

During the last decade, “fuzzy techniques” have been increasingly applied to the research area of construction management discipline. To date, however, no paper has attempted to summarize and present a critique of the existing “fuzzy” literature. This paper, therefore, aims to comprehensively review the fuzzy literature that has been published in eight selected top quality journals from 1996 to 2005, these being Journal of Construction Engineering and Management, ASCE; Journal of Management in Engineering, ASCE; Construction Management and Economics; Engineering, Construction and Architectural Management; International Journal of Project Management; Building Research and Information; Building and Environment; and Benchmarking: An International Journal. It has been found that fuzzy research, as applied in construction management discipline in the past decade, can be divided into two broad fields, encompassing: (1) fuzzy set/fuzzy logic; and (2) hybrid fuzzy techniques, with the applications in four main categories, including: (1) decision making; (2) performance; (3) evaluation/assessment; and (4) modeling. The comprehensive review provided in this paper offers new directions for fuzzy research and its application in construction management. Based on a comprehensive literature review on the applications of fuzzy set/fuzzy logic, and hybrid fuzzy techniques in construction management research, an increasing trend of applying these techniques in construction management research is observed. Therefore, it is suggested that future research studies related to fuzzy techniques can be continuously applied to these four major categories. Fuzzy membership functions and linguistic variables in particular can be used to suit applications to solving problems encountered in the construction industry based on the nature of construction, which are widely regarded as complicated, full of uncertainties, and contingent on changing environments. Moreover, hybrid fuzzy techniques, such as neurofuzzy and fuzzy neural networks, can be more widely applied because they can better tackle some problems in construction that fuzzy set/fuzzy logic alone may not best suit. For example, neural networks are strong in pattern recognition and automatic learning while fuzzy set and fuzzy logic are strong in modeling certain uncertainties. Their combination can assist in developing models with uncertainty under some forms of pattern. Finally, an increasing trend of applying fuzzy techniques in the building science and environmental disciplines is also observed; it is believed that the application of fuzzy techniques will go beyond the construction management area into these disciplines as well.     

Managing Construction Projects Using the Advanced Programmatic Risk Analysis and Management Model

Risk management is an important part of construction management, yet the risk-based decision support tools available to construction managers fail to adequately address risks relating to cost, schedule, and quality together in a coherent framework. This paper demonstrates the usefulness of the Advanced Programmatic Risk Analysis and Management Model (APRAM) originally developed for the aerospace industry, for managing schedule, cost, and quality risks in the construction industry. The usefulness of APRAM for construction projects is demonstrated by implementing APRAM for an example based on an actual building construction project and comparing the results with other risk analysis techniques. The results show that APRAM simultaneously addresses cost, schedule, and quality risk together in a coherent, probabilistic framework that provides the information needed to support decision making in allocating scarce project resources.     

Project Scheduling Using Fuzzy Set Concepts

Probabilistic methods are being used increasingly in construction engineering. However, when a parameter is expressed in linguistic rather than mathematical terms, classical probability theory fails to incorporate the information. The linguistic variables can be translated into mathematical measures using fuzzy set and system theory. A construction management problem, i.e., estimation of the duration of an activity, is solved using this theory. In order to implement the proposed technique, various membership functions need to be estimated using judgment or with the assistance of experts. The proposed technique is not sensitive to small variations in the membership values. This is a very desirable property. However, the method is sensitive to the choice of the fuzzy relations. The uncertainty in the fuzzy relations can be modeled along with other sources of uncertainty. The mean and variance of the parameters involved in the problem under consideration are estimated here using a new method. The method maximizes the product of the sum of the membership associations for a certain frequency of occurrence and the corresponding frequency of occurrence. One of the main advantages of the proposed technique is that it can be easily implemented in existing computer programs for project scheduling.     

Portfolio Cash Assessment Using Fuzzy Systems Theory

Gaps between cash outflows and inflows throughout the life cycle of construction projects can create extended periods of low cash availability for a construction contractor, jeopardizing the financial stability of the business. A number of researchers have therefore attempted to model cash availability at a project level. However, at a firm level, financial stability is more thoroughly examined as a function of the cash flows related to multiple projects. This paper proposes a methodology on the basis of fuzzy systems theory to forecast cash requirements of a portfolio of projects for a construction firm, taking into account the effect of changing portfolio composition on portfolio cash-flow risk. Portfolio cash-flow risk is calculated from a variance matrix created by using covariance among cash flows of pairs of projects. Expert opinions of a group of highway construction contractors regarding project selection, project risk assessment and cash control were collected to create a fuzzy proportional derivative (PD) model that predicts portfolio risk for a construction firm. The model was assessed by the same group of contractors for overall logic (if/then rule base), appropriateness of cash-flow calculations (moving weights of cost categories), and practicality through application on a hypothetical test case. The paper concludes that a fuzzy proportional derivative model can be an effective tool to establish trends in cash-flow availability and risk across a portfolio of construction projects.     

Fuzzy Intellectual Capital Index for Construction Firms

Construction firms are now operating in a new era. Gaining and sustaining competitive advantage in this era primarily depends on effective and efficient management of knowledge assets. This paper proposes a performance evaluation model called fuzzy intellectual capital index (FICI) that can guide construction business executives to effectively and efficiently manage their knowledge assets. FICI incorporates an intellectual capital performance measurement model with fuzzy set theory to adequately handle imprecision, vagueness, and uncertainty that prevail in this process. FICI uses the fuzzy-weighted average algorithm to compute the intellectual capital performance of architectural/engineering/construction (A/E/C) firms. It is an internal reporting model that can guide executives of A/E/C firms to evaluate their firm’s ability to achieve their strategic objectives and to pinpoint their firm’s strengths and weaknesses in order to neutralize threats and to exploit opportunities presented by today’s construction business environment. A real-world case study is presented to illustrate the implementation and utility of the proposed model. Implications for practitioners and directions for future research are discussed.     

Float Allocation Using the Total Risk Approach

Float ownership is one of the controversial issues in the litigation of delay claims. As float time does not always affect the overall project completion time, many believe that this time can be used by any of the project parties and that it does not belong to a particular party. This study introduces the “total risk approach” for float allocation, a new approach that integrates several current approaches to allocate float among project parties. The approach is based on the basic concept that the party who has the greatest risk in a project should be entitled to float ownership and deserves compensation from other project parties who increase the risk associated with the project by consuming the float. This new approach takes into consideration the changes in float that may occur as a result of actions that delay or accelerate the project’s schedule.     

Fuzzy Approach to Prequalifying Construction Contractors

Construction contractor prequalification (CCPQ) is a crucial decision making process to select capable potential bidders and ensure the success of construction projects. The purpose of CCPQ is to guarantee a contractor’s characteristic to meet the construction project’s requirements, which has been established worldwide as a standard practice. However, existing methods, i.e., marking method, subjective judgment method, etc., for contractor prequalification have been inadequate because it is difficult for decision makers to investigate contractor’s capabilities against inexact, vagueness, and qualitative criteria. The objective of this paper is to propose a fuzzy framework-based fuzzy number theory to solve construction contractor prequalification issues, which include decision criteria analysis, weights assessment, and decision model development. Finally, a case study for a tunnel construction project was used to demonstrate the feasibility of fuzzy approaches.     

Evaluation of Solid Waste Management System Using Fuzzy Composition

Evaluating the best alternative for a solid waste management system often requires decision makers to consider conflicting, vague, and uncertain information. Fuzzy set theory offers a possible means of managing these kinds of data or information. In this study, we propose a systematic approach to evaluating a solid waste management system in a fuzzy environment. The approach employs three main concepts: linguistic variables, fuzzy numbers, and an analytic hierarchy process. The linguistic variables are used to represent the degree of appropriateness of decision criteria, which are vague or uncertain. These linguistic variables are then translated into fuzzy numbers to reflect their uncertainties and aggregated into the final fuzzy decision value using a hierarchical structure. Through a case study, the approach is applied to the evaluation of a solid waste management system consisting of four different treatment alternatives. The results demonstrate that the developed approach can be a useful tool for evaluating a solid waste management system, where criteria are vague or imprecise.     

Application of Fuzzy Logic to Simulation for Construction Operations

This paper describes the application of fuzzy logic to discrete event simulation in dealing with uncertainties of construction operations. The uncertainties in the quantity of resources required to activate an activity are modeled with fuzzy sets in linguistic terms. The fuzzy logic if-then rule is built to control the activation of activities. The duration of the activity that varies with the quantities of resources involved is determined through the fuzzy logic rule-based model. The fuzzy logic control of activities is incorporated with the activity scanning simulation strategy to implement the fuzzy simulation system for construction operations. In addition, the fuzzy activity element is adopted in the graphical modeling process. Examples are given that illustrate uses of the fuzzy simulation system and the impact of flexible demand of resources on productivity.     

Understanding and Improving Your Risk Management Capability: Assessment Model for Construction Organizations

Implementing risk management in construction projects and organizations may bring a number of benefits and therefore it is necessary to have risk management as an integral part of a construction organization’s management practice. The aim of this paper is to develop a risk management maturity assessment model for construction organizations. The paper describes the development process of a Web-based RM3 (risk management maturity model), including its contents, its validation and testing, as well as its applications. The RM3 developed has five attributes namely, management, risk culture, ability to identify risk, ability to analyze risk, and application of standardized risk management process/system. These attributes are measured against four levels: initial, repeated, managed, and optimized. It is found that the proposed RM3 was suitable and useful. Using the RM3, it is found that the Australian construction industry’s overall risk management maturity level was relatively low (where 32% rated at Level 2 and 52% rated at Level 3). Furthermore, it is found that the weakest attribute was “analyzing risks” followed by “application of standardized risk management process.” It is therefore necessary to provide more training on qualitative and quantitative risk analysis to construction personnel and to develop and apply standardized enterprise risk management. It is concluded that the proposed RM3 is suitable for construction organizations to assess their risk management maturity levels and find ways for improvement.     

Project Management in the Chinese Construction Industry: Six-Case Study

Originating from the West, project management was introduced into China after the country’s economic reforms in the 1980’s and has since spread quickly throughout the whole country, particularly in the construction industry. However, despite the wide adoption of project management practices by construction organizations and the growing recognition of the importance of project management as an enabler of organizational success, empirical studies on project management in the context of the Chinese construction industry have been inadequate. This paper presents the results of an empirical study of six Chinese construction organizations in order to come to a more comprehensive and sophisticated understanding of project management practices in the Chinese construction industry. The findings revealed: (1) a good appreciation of the role of projects and project management and satisfaction with current project management practices; (2) 11 key aspects of project management implementation; (3) 12 resultant value and benefits; and (4) five aspects of the main challenges facing the organizations. Meanwhile, variations in project management practices and the resultant organizational value were identified, first between the three owner- and the three contractor-case study organizations, then between the two construction contractor organizations and the one design contractor organization.     

Incentives in the Chinese Construction Industry

Incentives have been increasingly applied to align the objectives of participants in the delivery of construction projects. However, little research has been undertaken to systematically study the use of such incentives. This paper reports the findings of an empirical survey of the Chinese construction industry on: the need to apply incentives; frequency of the usage of incentives; how the incentive schemes are decided; and their effectiveness in application. The incentive schemes of the Three Gorges Project is also studied, from which an incentive matrix is presented that has measures tied not only to the final results but also extended to the whole construction process to facilitate providing early warnings, obtain continuous improvement, and ultimately achieve satisfactory project results for participants. It is recommended that future studies be encouraged to develop incentives according to project features such as project type, delivery system, project risk, and participants’ needs and their experience, enabling incentives to be applied broadly by participants to improve the efficiency of project delivery.     

Developing a Fuzzy Risk Allocation Model for PPP Projects in China

Equitable allocation of risks between the government and the private sector in concession agreement is essential to the success of public-private partnership (PPP) projects. The decision-making process, based on the established risk allocation principles expressed in linguistic terms, requires qualitative judgment and experiential knowledge of construction experts. However, it is subjective, partial, and implicit in actual application. This paper aims to develop a fuzzy synthetic evaluation model for determining an equitable risk allocation between the government and the private sector. By doing so, it assists the PPP project practitioners to transform the risk allocation principles in linguistic terms into a more usable and systematic quantitative-based analysis using fuzzy set. Twenty-three principles and influencing factors for risk allocation were identified through a comprehensive literature review. Nine critical risk allocation criteria (RACs) that evaluate the risk carrying capability of project participants were further identified, validated, and compiled based on the experts’ knowledge via face-to-face interviews. On the other hand, the weighting for each critical risk allocation criterion was determined through a two-round Delphi questionnaire survey. A set of knowledge-based fuzzy inference rules was then established to set up the membership function for the nine RACs. Based on the research findings, a fuzzy synthetic evaluation model was finally established to determine an equitable risk allocation between the government and the private sector.     

Model for Fostering Trust and Building Relationships in China’s Construction Industry

Trust is an underlying psychological condition that can cause cooperation or risk-taking. Trust is considered as a predominant feature and a central mechanism in business transactions, especially among Chinese. Trust-based relationships create advantages in conducting business such as lowering cost, shortening duration, and improving performance. Indispensable conditions for trust to arise are relationships and risks. Different risks surface as a result of different levels of relationships. Sustained trust is therefore fostered by various means to counterbalance those risks. In order to assess the links between distinct trust-related features, a model is constructed and tested through a questionnaire survey in China. The findings generally support the model in terms of explaining the dominant relationships, inherent risks, and trust-fostering tools. It is recommended that firms adopt the refined model and utilize successful practices verified in this paper to foster trust and relationships and in turn secure project success.