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.     

Developing decision support systems: a change in emphasis

Against a backdrop of many demonstrably proficient expert systems that are not routinely used, and a user community that is skeptical of the benefits of using such technology in healthcare, the AIM funded Dilemma project is attempting to introduce decision support technology into shared care environments within scenarios from the specialties of oncology and cardiology. This paper outlines the experiences of one work-package of the Dilemma project which is concerned with the development of applications with a decision support component for use in shared care of coronary artery disease patients. We suggest reasons why expert systems have failed to gain acceptance in the past, and conclude that a shift in emphasis from building expert systems to building clinically useful applications that have an expert system component may improve the chances of acceptance of this technology in the future.     

武钢1 700 mm热连轧机活套控制系统改造实践

阐述了武钢1 700 mm热连轧机活套控制系统改造中所做的实践性探索。通过对活套高度和张力控制模型的再认识,结合专家知识和实践经验提出理想活套控制特性。在实践中为实现其理想特征,采用了多种新方法,包括基于专家知识的活套智能综合补偿、基于多项式回归的非线性实时张力矩计算、基于统计方法的角加速度值估计等。经实际调试运行,优于改造前系统。     

Domain Taxonomy for Construction Concepts: Toward a Formal Ontology for Construction Knowledge

With the advancement of the semantic web, the construction industry is at a stage where intelligent knowledge management systems can be used. Such systems support more effective collaboration, where virtual teams of skilled users, not software, exchange ideas, decisions, and best practice. To achieve that, there is a need to create consistent semantic representation of construction knowledge. Existing representations, in the form of classification systems and product data models, lack effective modeling of concept semantics—a fundamental requirement for human-based exchange of knowledge. Toward this objective, this paper presents a domain taxonomy that was developed as part of the e-COGNOS project. The taxonomy was developed as a first step in the establishment of domain ontology for construction. The taxonomy was developed to be process-centered and to allow for utilization of already existing classification systems (BS6100, Master Format, and UniClass, for example). The taxonomy uses seven major domains to classify construction concepts: Process, Product, Project, Actor, Resource, Technical Topics, and Systems. The taxonomy was developed and validated through extensive interaction with domain experts. The taxonomy was used to develop a prototype ontology for the construction domain including semantic relationships and axioms. The ontology was used to support several applications in semantic knowledge management as part of the e-COGNOS portal, including semantic indexing and retrieval of information and ontology-based collaborative project development.     

Optimizing Implementation of Value Management Processes for Capital Projects

A variety of innovative management processes are increasingly being introduced into the capital facility projects, thereby causing a great concern about which to implement on a particular project among project stakeholders. It is essential to identify the most effective process because varying circumstances on each project determine the level of suitability. This paper details a new systematic approach to determining the best process from among the 44 value management processes (VMPs) that can proactively achieve the articulated 12 project value objectives (PVOs). Throughout this paper, identifying and quantifying the selection principles (e.g., targeted PVOs, timing of initiation, project characteristics, and relative impact), the detailed research methodology and the findings from industry survey and VMP expert input are also illustrated. A computerized tool, programmed by Visual Basic Application on MS Excel, is described, and its ongoing validation process is also discussed. As a first-ever research, this paper contributes to a growing area of research, not only by providing a comprehensive and structured knowledge on the subject of VMPs, but also by developing a new method to effectively select the most beneficial VMPs. From the industry perspective, the results of this study, specifically the computerized selection tool, facilitate the implementation of the VMPs on the construction industry and maximize the potential benefits to a particular project.     

Development of an expert system for pediatric auditory brainstem response interpretation

Expert systems are computer programs which incorporate artificial intelligence technology and are created to emulate the decision-making abilities of human experts. The advantage of such systems lies in their ability to capture and model expert problem solving knowledge in a domain and make it available to an unlimited number of consumers in an economic and efficient way. The purpose of this project was to develop an expert system to interpret infant auditory brainstem response data as entered by the user. The resulting system provides diagnostic conclusions regarding hearing status, type of hearing loss, and brainstem function at an accuracy level equal to that of a human expert.     

Medical expert systems]

Expert systems are software systems that can successfully compare to human experts. Their purpose is mostly advisory. Besides, they give explanation and advice to human experts when performing certain tasks. They are intelligent information systems, and are capable to explain and justify their conclusions. Knowledge systems are smaller software systems, and are usually less successful than human experts. Main reasons for expert systems development in medicine are: need for justification of decisions, need for enhancing performances in many uncertain relations; need for explaining of decision making process etc. One of the reasons of developing knowledge-based systems was that conventional statistic formalisms have not provided satisfactory solutions in medical decision making (MDM). Also, today, the relations between cases and conclusions are not universally valid. So, few causes can provide the same conclusion. Besides, data are not necessarily absolutely accurate. The area of applying expert systems is very wide: diagnosis, prognosis, self-education, directing etc. Basic structure of expert system consists of: knowledge, data base, inferring mechanism, explaining mechanism and user-interface. Though, expert systems also have certain bad features: primarily, they are not physicians i.e. they can not examine a patient. Furthermore, expert system that is good for one certain area is often not good for another one. There are some cases, when these systems can confuse a physician and make him to make a wrong decision. This occurs very often in two specific cases: when the clinical situation is urgent; and when accuracy of clinical information is not definite.     

Automated Classification of Construction Project Documents

The number of documents generated in a construction project and stored in interorganizational information systems is significant. Since a large percentage of these project documents are generated in text format, methods for organizing and improving access to the information contained in these types of documents become essential to construction information management. Information classification schemes can be used for this purpose. They provide a common framework to enact document organization and information exchange among project members. Current systems for document management rely on manual classification methods controlled by human experts. Due to the widespread use of information technologies for construction, the increasing availability of electronic documents, and the development of systems based on project object models, manual classification becomes unfeasible. This paper presents a unique way to improve information organization and access in interorganizational systems based on automated classification of construction project documents according to their related project components. Machine learning methods were used for this purpose. A prototype of a document classification system was developed to provide easy deployment and scalability to the classification process.     

Using Digital Socialization to Support Geographically Dispersed AEC Project Teams

In the field of knowledge management research, socialization means to convert individual into group tacit knowledge. This process matters from the outset of an architecture, engineering, and construction (AEC) project to enhance collaborative work. Face-to-face meetings and phone calls undoubtedly facilitate socialization. However, meetings can be hard to timetable and expensive when AEC teams are geographically dispersed, whereas phone calls are cheap but offer limited capabilities for problem solving. Further, both media are not good at supporting asynchronous socialization. This study investigates the extent Internet-based media can promote cross-firm socialization and enhance collaborative work. The cross fertilization of findings from an exploratory case study with theory in computer-supported collaborative work (CSCW) informs the development of a conceptual framework on digital socialization. This framework underpins IDRAK—a proof-of-concept of a rich Internet application prototype to promote socialization in AEC projects. Our main contribution is the design of a novel methodology to evaluate the usability of digital systems to support socialization at the early design stage of an AEC project. The results from our lab experiments suggest that IDRAK can satisfactorily and efficiently enhance collaborative work. However, more research is needed, first, to evaluate the effectiveness of IDRAK to improve design quality and asynchronous socialization; and second, to investigate how other CSCW features can improve the performance of IDRAK-like systems.     

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.     

Sensing and Field Data Capture for Construction and Facility Operations

Collection of accurate, complete, and reliable field data is not only essential for active management of construction projects involving various tasks, such as material tracking, progress monitoring, and quality assurance, but also for facility and infrastructure management during the service lives of facilities and infrastructure systems. Limitations of current manual data collection approaches in terms of speed, completeness, and accuracy render these approaches ineffective for decision support in highly dynamic environments, such as construction and facility operations. Hence, a need exists to leverage the advancements in automated field data capture technologies to support decisions during construction and facility operations. These technologies can be used not only for acquiring data about the various operations being carried out at construction and facility sites but also for gathering information about the context surrounding these operations and monitoring the workflow of activities during these operations. With this, it is possible for project and facility managers to better understand the effect of environmental conditions on construction and facility operations and also to identify inefficient processes in these operations. This paper presents an overview of the various applications of automated field data capture technologies in construction and facility fieldwork. These technologies include image capture technologies, such as laser scanners and video cameras; automated identification technologies, such as barcodes and Radio Frequency Identification (RFID) tags; tracking technologies, such as Global Positioning System (GPS) and wireless local area network (LAN); and process monitoring technologies, such as on-board instruments (OBI). The authors observe that although applications exist for capturing construction and facility fieldwork data, these technologies have been underutilized for capturing the context at the fieldwork sites as well as for monitoring the workflow of construction and facility operations.     

Success/Failure Factors and Performance Measures of Web-Based Construction Project Management Systems: Professionals’ Viewpoint

This paper presents the results of an empirical study conducted to refine the writers’ previous findings on potential factors that may influence performance of commercial Web-based project management systems (WPMSs) and potential measures that might be used to assess performance of such systems. Data used in this study were obtained from 39 professionals who had practical experience with WPMSs in construction projects. The results of the study confirm 42 factors that can potentially affect performance of WPMSs and 36 measures that can be used to evaluate such performance. These 42 factors are categorized into four distinct groups: characteristics of the project, the project team, the service provider, and the specific WPMS system used in the project. The 36 measures reflect performance of WPMSs in six different perspectives: strategic, schedule/time, cost, quality, risk, and communication. Findings presented in this paper can be used by researchers as a starting point for future research in the area of WPMS implementation and performance evaluation and may be used by practitioners in the industry as a useful guide to increase the likelihood of a successful WPMS adoption.     

Quantitative ultrasound techniques for the assessment of osteoporosis: expert agreement on current status. The International Quantitative Ultrasound Consensus Group

Quantitative ultrasound (QUS) methods have been introduced in recent years for the assessment of skeletal status in osteoporosis. The performance of QUS techniques has been evaluated in a large number of studies. Reviewing existing knowledge, an international expert panel formulated the following consensus regarding the current status of this technology. To date, evidence supports the use of QUS techniques for the assessment of fracture risk in elderly women. This has been best established for water-based calcaneal QUS systems. Future studies should include the predictive validity of other QUS systems. Additional clinical applications of QUS, specifically the assessment of rates of change for monitoring disease progression or response to treatment, require further investigation. Its low cost and portability make QUS an attractive technology for assessing risk of fractures in larger populations than may be suitable or feasible for bone densitometry. Additional investigations that assess innovative QUS techniques in well defined research settings are important to determine and utilize the full potential of this technology for the benefit of early detection and monitoring of osteoporosis.     

Management Thinking in the Earned Value Method System and the Last Planner System

Management theory has been neglected in the construction industry, which has rather focused on best practices. This paper investigates the theories implicit in two prevalent project control systems: the earned value method (EVM) and the last planner system (LPS). The study introduces two fundamental and competing conceptualizations of management: managing by means (MBM) and managing by results (MBR). The EVM is found to be based on MBR. However, project control based on MBR is argued to be inappropriate for managing at the operational level where tasks are highly interdependent. The LPS is found to be based on the MBM view. The empirical evidence from literature and case study suggested that the MBM view is more appropriate to manage works when it is applied to the operation level where each task is highly interdependent.     

Component-Based Framework for Implementing Integrated Architectural/Engineering/Construction Project Systems

Current practices and integration trends in the architectural/engineering/construction (A/E/C) industry are increasing the demands for the implementation and deployment of integrated project systems. Much of the research throughout the last decade was driven by the need to develop integrated project systems and standard industry-wide data models to support their development. This paper presents a multitier component-based framework that aims to facilitate the implementation of modular and distributed integrated project systems that would support multidisciplinary project processes throughout the project life cycle. The framework addresses the specific requirements of A/E/C projects, and highlights the required functionality and approach to develop integrated project systems. The framework defines a three-tier architecture: Applications tier, common domain-services tier, and project data-repository tier. The applications tier includes a set of function-specific software tools that interact with the domain-services-tier components via a set of adapters. Adapters map the applications’ internal proprietary-data models to and from a standard integrated data model. The domain-services-tier components implement a number of generic services, such as data management, transactions management, document management, and workflow management. The data-repository tier represents a centralized shared storage of all relevant project information. The paper also discusses the implementation of a prototype software system that demonstrates the use of the framework’s reusable components and the industry foundation classes data model in typical building projects.     

Innovation in Construction Engineering Education Using Two Applications of Internet-Based Information Technology to Provide Real-Time Project Observations

Improvements in construction engineering education result when innovative information technologies are incorporated into academic curricula. Through the use of internet-based communication technologies, no longer must students physically travel to a construction project site to observe and hear construction operations. This paper discusses two applications of internet-based, audio and video technologies currently being piloted at Iowa State University (ISU) and at the University of Calgary (UC) for the purpose of bringing live construction projects into the university classroom. Virtual Project Tours have been piloted at Iowa State University in which real-time video and audio are delivered from active construction projects to a remote classroom through the internet. The second application discussed in this paper, Virtual Supervision, is being piloted at the University of Calgary and consists of the monitoring and analysis of construction projects by using imagery gathered by web-enabled, digital cameras of fixed location transmitting video through the internet. This paper also presents a vision of a globally networked organization of engineering and construction education institutions each sharing the unique engineering and building techniques of their respective part of the globe with design and construction students located around the world. This exchange of construction project observations among the institutions will be enabled by the internet-based applications of virtual project tours and virtual supervision systems described in this paper.     

Feasibility of Automated Monitoring of Lifting Equipment in Support of Project Control

One of the differences between industrial manufacturing or processing plants and construction sites is the temporary nature of the construction site, which has traditionally precluded installation of sophisticated production monitoring systems. Monitoring of production progress, cost, and quality is performed almost exclusively manually, with the result that it is expensive and approximate, and is commonly delivered with a time lag that does not allow for an effectively closed control loop. Automated monitoring of construction lifting equipment to provide useful feedback information for project management is a strong potential candidate; almost all components and materials must be transported by machines, and monitoring of machines is relatively straightforward. A system concept, employing a “black box” monitor and an electronic building information model, was developed. A field study was conducted to test the feasibility of the concept. The results indicate that the system is technically feasible, and offers the potential to deliver real-time, accurate project control information at very low cost.     

Detecting Semantic Anomalies in Truck Weigh-in-Motion Traffic Data Using Data Mining

Monitoring data from event-based monitoring systems are becoming more and more prevalent in civil engineering. An example is truck weigh-in-motion (WIM) data. These data are used in the transportation domain for various analyses, such as analyzing the effects of commercial truck traffic on pavement materials and designs. It is important that such analyses use good quality data or at least account appropriately for any deficiencies in the quality of data they are using. Low quality data may exist due to problems in the sensing hardware, in its calibration, or in the software processing the raw sensor data. The vast quantities of data collected make it infeasible for a human to examine all the data. The writers propose a data mining approach for automatically detecting semantic anomalies i.e., unexpected behavior in monitoring data. The writers’ method provides automated assistance to domain experts in setting up constraints for data behavior. The effectiveness of this method is shown by reporting its successful application to data from an actual WIM system, the experimental data the Minnesota department of transportation collected by its Minnesota road research project (Mn/ROAD) facilities. The constraints the expert set up by applying this method were useful for automatic anomaly detection over the Mn/ROAD data, i.e., they detected anomalies the expert cared about, e.g., unlikely vehicles and erroneously classified vehicles, and the misclassification rate was reasonable for a human to handle (usually less than 3%). Moreover, the expert gained insights about system behavior, such as realizing that a system-wide change had occurred. The constraints detected, for example, periods in which the WIM system reported that roughly 20% of the vehicles classified as three-axle single-unit trucks had only one axle.     

Building Project Model Support for Automated Labor Monitoring

In current project control practice, deviations from planned performance can only be reported after significant time has elapsed. Manual monitoring on construction sites is costly and error prone. Consequently, an automated model for monitoring labor inputs, based on automated data collection (ADC), offers a solution to the problem. Integration with a computerized building project model (BPM), including the physical geometry of the building, the resources active in its execution, and the planned construction activity schedule, is essential for the operation of such a model. Integration with an existing BPM requires that the BPM be expanded to support interpretation and accumulation of the monitoring results. To this end, appropriate project model classes and relationships have been implemented and tested. Experimental data were collected, using an ADC system, from the job site of a reinforced concrete building. The data were processed, within the BPM, with the aid of a prototypical location interpretation module.     

设备状态监测及故障诊断专家系统

介绍了设备运行监测及故障诊断专家系统的系统功能特点及系统的构成。系统采用工控计算机,数据采集卡,组态软件组成;故障诊断专家系统具有知识获取存储能力,诊断过程解释功能。系统实现了设备的实时监测,提高了故障分析能力。