Automation and Robotics for Construction

The potential for automated real‐time data acquisition, process control and robotics for remote, large‐scale field operations, such as those on construction engineering projects, is addressed. Classifications of technologies for automation and robotics in such operations include hard‐wired instrumentation, remote sensing, analog and digital telecommunications, optical (laser, infrared and fiber‐optic) data transmission, monitoring via microcomputer‐based instrument control and data recording, on‐site process control for fixed plants, partial or fully automatic control of mobile equipment, fixed‐based manipulators, mobile robots, communications between on‐site computers and automated machinery, electronic ranging and detection, and video‐image pattern recognition. Combining selected technologies with microcomputer‐based software could facilitate analysis, design and control decision‐making, and could provide a means of coordinating various discrete automated components or machines that must work together to perform field tasks. This paper also mentions categories of needs for such technologies on field operations, and potential barriers to implementation. Progress will depend on the interest and support of researchers qualified to advance this field.     

Cost-Benefit Analysis of Embedded Sensor System for Construction Materials Tracking

Tracking and monitoring the location of materials on a construction job site is an important, yet commonly overlooked aspect of field data acquisition because timely information about the status of materials, equipment, tools, and labor resources are directly related to the successful completion of a project. With the advanced technologies and innovations in the construction industry, it has become technically viable to implement automated tracking for construction materials. Through the development of an embedded sensor system, this paper illustrates the implementation of pilot experiments examining the accuracy of a system’s performance. A cost-benefit analysis is conducted to illustrate labor savings associated with construction materials handling by comparison between manual and sensor-based materials tracking. The presented embedded sensor system can be extended into diverse application areas in tracking and monitoring framework by providing improved method of field data acquisition and information management.     

Automated Recognition of 3D CAD Objects in Site Laser Scans for Project 3D Status Visualization and Performance Control

This paper presents a new approach that allows automated recognition of three-dimensional (3D) computer-aided design (CAD) objects from 3D site laser scans. This approach provides a robust and efficient means to recognize objects in a scene by integrating planning technologies, such as multidimensional CAD modeling, and field technologies, such as 3D laser scanning. Using such an approach, it would be possible to visualize the 3D status of a project and automate some tasks related to project control. These tasks include 3D progress tracking, productivity tracking, and construction dimensional quality assessment and quality control. This paper provides an overview of the developed approach and demonstrates its performance in object recognition and project 3D status visualization, with data collected from a construction job site.     

Embedded System for Construction Asset Tracking Combining Radio and Ultrasound Signals

Today’s sensor technology provides the increased opportunities for automation and improvement in data acquisition and construction processes. However, many current field practices at construction sites still rely on manual processes for asset tracking and information handling. Previous technologies, such as radio frequency identification and global positioning systems, do not provide a solution to automated asset tracking because of their limitations in terms of applicability and performance in a typical construction environment. This paper introduces a new development of an embedded sensor system for construction asset tracking by combining radio and ultrasound signals. We present the detailed hardware and software architecture and have implemented outdoor experiments to examine the accuracy and performance of the designed system. The results obtained showed the accurate distance and position estimation with enhanced networking flexibility. The findings and lessons learned from this research demonstrate the potential for future practical deployment of similar systems in many civil engineering applications.     

Mixed Reality-Based Visualization Interfaces for Architecture, Engineering, and Construction Industry

Varied computing devices and automated sensors will enable new human-computer interface paradigms for interacting with digitally managed project information. The writers therefore propose the development of Mixed Reality (MR)-based computer interfaces, and especially Augmented Reality systems, for the architecture, engineering, and construction industry and describe the technologies and principles for applying such computer interfaces to support all phases of the constructed facility project life cycle. An Augmented Reality computer-aided drawing prototype is described as an experimental platform to study the human factors issues in interacting with Augmented Reality three-dimensional digital design models. Two critical research needs are cited for realizing effective Augmented Reality systems: (1) human factors research for development of visualization tools to enhance design comprehension and support collaborative work, and (2) the development of a technology infrastructure for “augmented” control and inspection interfaces to directly access digital project plan and site information that may be spatially referenced and displayed in the field. Research should be geared to advance knowledge regarding spatial cognition, human–computer interfaces, and computer-mediated human-to-human interactions, and it should address application of MR to all phases of the project life cycle.     

Interpretation of Automatically Monitored Lifting Equipment Data for Project Control

Interpretation of the data that can be collected by automated monitoring systems on construction sites is the most significant challenge to providing useful management information. Distinct construction operations must be identified and associated with construction activities, so that they can be related to construction plans. Earlier research has indicated that construction equipment can be monitored conveniently and that individual equipment operations can be isolated and characterized. In this work, an approach has been developed for unique association of isolated equipment operations with planned construction activities. The approach is based on comparison of the values of various characteristics, calculated for each equipment operation, against preset filters of characteristic values for all expected basic construction activities. The composition of the set of characteristics is different for each data stream monitored and is dependent on the nature of the construction activities. The method has the distinct advantage of ensuring the uniqueness of each filter within the collection of filters when the system is calibrated at the start of any project, rather than during online data processing. In this way, rapid and accurate interpretation of monitored data can be guaranteed. The method was tested using data collected during construction of a high-rise office tower.     

Field Experiments in Automated Monitoring of Road Construction

The growing need for better monitoring and control of road construction projects, together with rapid technological progress, have led to a number of interesting developments, which are reviewed below. The present paper describes the development of a real-time monitoring model capable of measuring productivity and progress automatically. The model, which uses global positioning system for on-site automated data collection, was tested and validated on site. The results of the field experiments have indicated that the expected accuracy level of the model can be assessed as ±4–5% for unstructured activities and even higher for more structured ones, such as asphalt spreading. The paper concludes that it is possible to automatically measure the performance of earthmoving operations. Based on the results, it also highlights the needs for further research.     

Automated Collection of Mixer Truck Operations Data in Highly Dense Urban Areas

Our research has investigated the feasibility of directly sourcing autonomous operations data from a construction-vehicle positioning system, so as to enable productivity analysis and simulation modeling in the practical context of ready mixed concrete production and delivery. In this paper, we first review research efforts related to applying radio frequency identification tags and global positioning system for tracking construction resources and acquiring operations data in the field. We then describe the technical design and system components of an automated data collection (ADC) solution to accumulating concrete delivery operations data, which is extended from a construction-vehicle positioning system tailored for highly dense urban areas. We further elaborate on how our ADC system captures, transforms, and analyzes data of mixer truck operations. Truck-tracking experiment results based on field trials are presented to demonstrate the usefulness of data sourced from our ADC system with respect to: (1) analyzing truck-waiting time versus truck-unloading time on site; and (2) predicting truck’s plant-to-site travel time. In conclusion, the ADC solution resulting from this research not only allows sophisticated analysis of mixer truck resource utilization at concreting sites situated in highly dense urban areas, but also provides an accumulation of input data that will enable concrete plant operations simulation modeling.     

Distributed System for Coastal Infrastructure Modeling and Assessment

The client/server computer architecture of the Internet provides an efficient mechanism for implementing effective civil infrastructure monitoring and assessment applications. Systems functionality that is enabled by this important technology includes remote and real-time data acquisition, distributed model execution and control, multiuser access to and monitoring of decision support systems, and efficient systems expansion and maintenance. With the dramatic increase in available infrastructure data and the continued improvement in the reliability and robustness of these technologies, widespread design, implementation, and use of distributed infrastructure modeling systems will become common. This paper describes the design and development of a prototype infrastructure modeling system incorporating these technologies that has recently been implemented to help decision makers manage the coastal infrastructure of the Great Lakes.     

Model based optimisation of highly automated industrial batch annealing operation

Abstract

Modern batch annealing operations are highly automated facilities, equipped with online sensors, model based control and a production management system to archive material, process and quality parameters. In these operations, efficient models and algorithms are used to allocate the resources, schedule the operation and design process cycles of individual stacks. The present work endeavours to enhance the productivity of a highly automated batch annealing facility, operating well above its rated capacity. This was achieved by intelligent analysis of production data and a critical assessment of the prevalent thermal model used for designing the process cycle of the individual stack. Two major limitations, namely, the inability to capture non-isothermal kinetics and the stiff radial conductivity model, of the prevalent thermal model were identified. These limitations were eliminated by designing process cycles with an integrated process model, where phase transformation kinetics is incorporated. Implementation of these process cycles has enhanced the productivity of the batch annealing operation by 7–9%. These benefits have been validated through rigorous laboratory experiments and plant trials.     

Computer Vision-Based Video Interpretation Model for Automated Productivity Analysis of Construction Operations

Videotaping is an effective and inexpensive technique that has long been used in construction to conduct productivity analyzes. However, as schedules of modern construction projects become more and more compressed, the limitation of video-based analysis—intensive manual reviewing process—contrasts sharply with the need for effortless data analysis methods. This paper presents a study on developing a video interpretation model to interpret videos of construction operations automatically into productivity information. More specifically, this research formalizes key concepts and procedures of video interpretation within the construction domain. It focuses on designing a mechanism for furthering the crosstalk between the prior knowledge of construction operations and computer vision techniques. It uses this mechanism to guide the detection and tracking of project resources as well as work state classifications and abnormal production scenario identifications. The resulting approach has the potential to provide a common base for developing automated video interpretation procedures that can greatly improve current data collection and analyzes practices in construction. Experimental results from preliminary studies have shown the potential of the proposed video interpretation method as an improved productivity data analysis method.     

Technology Development Decision Economics for Real-Time Rolling Resistance Monitoring of Haul Roads

Proponents of advanced technologies for the delivery of constructed facilities assert that information and automation technologies can significantly reduce construction costs. However, technology transfer has been greatly limited as practitioners are reluctant to adopt new technologies for myriad reasons including concerns over expertise requirements, value versus traditional approaches, implementation practicality, and risk. All of these concerns ultimately relate to cost versus benefit. While considerable automation research has been documented, thorough economic justifications in the literature have been rare in comparison. In this paper, the writers present and illustrate a model to assess the economics of construction equipment automation using a case illustration focused on the allowable cost of sensor technologies for real-time, in-field rolling resistance monitoring. Rolling resistance is vital in determining power train requirements, fuel consumption, and travel time associated with hauling operations. The absence of a true understanding of field changes in rolling resistance may result in a lack of insight regarding the interaction of jobsite characteristics and the performance potential of hauling operations.     

Tracking Components and Maintenance History within a Facility Utilizing Radio Frequency Identification Technology

Limitations in data transfer between maintenance workers and a central facility management (FM) system result in lower data quality, longer service process times, and ineffective capturing of component maintenance history. Radio frequency identification (RFID) technology provides an opportunity to meet the current needs for uniquely identifying facility components, storing some maintenance history information on the component, and accessing this information on-demand within a facility. There have not been any research studies that tested the performance of active ultrahigh frequency RFID technology on facility components during operations and maintenance phase repetitively over an extended period of time. The objectives of this study were to identify how RFID technology can improve current FM processes and to determine technological feasibility of using RFID within a facility repetitively on a daily basis. The writers tagged fire valves in a facility with RFID tags and conducted a longevity test for sixty consecutive days by simulating tag identification, data access, and entry in real-life conditions. The results demonstrate that current commercially available active RFID technology performs well in a building environment where metallic objects and different obstructions are present. The observed reading distances were approximately half of the reading range expected in open air provided that there are not any massive obstructions between the reader and the tag.     

Simulation As a Tool to Assess the Vulnerability of the Operation of a Health Care Facility

Health care systems are classified as critical infrastructure systems when responding to disaster events. Physical damage to health care facilities or disruption of their operations or supply chains could prevent an effective response and aggravate the outcome of an emergency situation. Even if a hospital or public health facility were not directly affected by the disaster event, these facilities are required to operate efficiently during an emergency in order to manage a surge of capacity. When infrastructure systems are damaged as a result of man-made or natural disaster events, insufficient supply of resources through these systems affects their performance. In this paper, a system dynamics simulation model will be used as a tool to represent the operation of a health care facility, including the interaction between the different service areas (emergency room, intensive care unit, wards, operating room), the flow of patients inside the facility, and the condition of the infrastructure systems that supply resources (i.e., water, power, transportation of medical supplies) to maintain the operation of the facility. The results of this study may assist hospital administrators in their disaster preparedness plans, providing information regarding the level of occupancy and patients waiting to enter the service areas.     

Eye movement monitoring as a process tracing methodology in decision making research.

Over the past half century, research on human decision making has expanded from a purely behaviorist approach that focuses on decision outcomes, to include a more cognitive approach that focuses on the decision processes that occur prior to the response. This newer approach, known as process tracing, has employed various methods, such as verbal protocols, information search displays, and eye movement monitoring, to identify and track psychological events that occur prior to the response (such as cognitive states, stages, or processes). In the present article, we review empirical studies that have employed eye movement monitoring as a process tracing method in decision making research, and we examine the potential of eye movement monitoring as a process tracing methodology. We also present an experiment that further illustrates the experimental manipulations and analysis techniques that are possible with modern eye tracking technology. In this experiment, a gaze-contingent display was used to manipulate stimulus exposure during decision making, which allowed us to test a specific hypothesis about the role of eye movements in preference decisions (the Gaze Cascade model; Shimojo, Simion, Shimojo, & Scheier, 2003). The results of the experiment did not confirm the predictions of the Gaze Cascade model, but instead support the idea that eye movements in these decisions reflect the screening and evaluation of decision alternatives. In summary, we argue that eye movement monitoring is a valuable tool for capturing decision makers' information search behaviors, and that modern eye tracking technology is highly compatible with other process tracing methods such as retrospective verbal protocols and neuroimaging techniques, and hence it is poised to be an integral part of the next wave of decision research. (PsycINFO Database Record (c) 2011 APA, all rights reserved)     

服务采矿工程教学研究的自动化充填料浆环管试验系统设计及应用

为实现矿山充填环管输送工艺的自动化运行,研制了一套自动化充填料浆环管试验系统。该系统主要由给配料系统、泵送系统、监测系统、管路系统和以PLC编程控制器为核心的自动控制系统等子系统组成,可完成充填料配比、料浆浓度、料浆流速、料浆流量、料浆温度等料浆流变参数及特性的测试工作,并自动绘制出各项测试参数之间的关联变化曲线。结果表明:该系统流速控制范围宽,管道布置方式多样,操作键盘化,集成度高,使用方便可靠,是进行矿业工程领域矿山充填研究与分析的重要基础设备,为科研与教学工作提供了自动化的试验与教学环境。     

Graphical Control Interface for Construction and Maintenance Equipment

This paper discusses graphical interfaces to improve equipment control in construction and facility∕infrastructure maintenance environments. Most large construction and maintenance machines are difficult to control because of insufficient visual feedback to equipment operators. In many emerging applications such as hazardous waste cleaning, it is also necessary to control such equipment from a distance using teleoperation techniques. Initial evidence indicates that real-time updated graphical representation of equipment and work environments can enhance equipment control by providing better spatial perception to the equipment operator. Real-time simulation and task planning with graphical models can also ensure safe and reliable operation of equipment. However, graphical control interfaces require careful design for successful results as it is very difficult to generate exact graphical models of unstructured and dynamic environments such as construction and maintenance. Design of graphical control interfaces for construction equipment also requires knowledge in various technological areas. In this paper, design issues and principles for graphical control interfaces for construction and maintenance equipment are presented. The usefulness of graphical control interfaces is also presented through performance tests of a teleoperated clinker clearing robot for power plant maintenance.     

Requirements and Incentives for Reducing Construction Vehicle Emissions and Comparison of Nonroad Diesel Engine Emissions Data Sources

Nonroad construction vehicles and equipment powered by diesel engines contribute to mobile source air pollution. The engines of this equipment emit significant amounts of carbon monoxide, hydrocarbons, nitrogen oxides, and particulate matter. These pollutants pose serious problems for human health and the environment. Therefore, it is necessary to regulate and control the levels of these pollutants. Furthermore, there are emerging requirements and incentives for “greening” of construction vehicle fleets and operations. Currently, there are two types of standards that regulate air pollution for these types of vehicles: technological standards for engines and quality standards for air. It is also necessary to quantify the levels of emissions that nonroad construction vehicles and equipment produce. Quantification may be based on existing data sources (such as the EPA NONROAD model) or by collecting data directly from the vehicles as they work in the field. The purpose of this paper is to introduce the challenges to quantification of emissions from nonroad construction vehicles, describe associated governmental regulations and incentives for reducing emissions, identify and compare various sources of emissions data, establish the need to collect additional data, and propose a future research agenda that focuses on air pollution generated by construction vehicles.     

基于冗余容错技术的高炉鼓风机自动化特护系统

通过采用冗余容错、冷风保安拨风子系统、风机特殊仪表自适应性、动态实时监控和跟踪等技术对运行的风机机组自控系统进行优化改造,建立了高炉鼓风机自动化特护系统,提高了整个自控系统的稳定性和可靠性。