Xiaochun Luo

Quantifying Hazard Exposure Using Real-Time Location Data of Construction Workforce and Equipment

AbstractTraditional risk-assessment methods typically evaluate accident probability, exposure frequency or duration, and consequence severity, respectively, and finally determine a quantitative risk score or a qualitative risk level. The assessment process is prospective and subjective. Changing and complex construction situations impede their practical and efficient application. To assess safety risk with regard to changing site conditions in an objective and efficient way, this study proposes a quantitative model for hazard exposure assessment based on real-time location data of construction workforce and equipment, collected by a location-based proximity warning system. In contrast with traditional risk-assessment methods, the model proposed in this study combines accident probability and hazard exposure duration into a single quantitative concept—hazard exposure amount. This concept takes into account the space factor as well as the time factor of construction activities. For ease of understanding, a ...

Comparative Study of Traditional and Group Decision Support-Supported Value Management Workshops

AbstractValue management (VM) participants often encounter problems of lack of active participation in addition to insufficient time and information in decision analysis. Group decision support systems (GDSS) have been proposed to overcome these problems by improving the efficiency and effectiveness of VM studies. To investigate the effect of using GDSS in VM workshops, three experimental studies together with questionnaire surveys have been conducted to compare the traditional VM and GDSS-supported workshops. The results have revealed that GDSS can help improve the performance of VM workshops in quantity of ideas, process efficiency, and participants’ satisfaction. These outcomes are valuable to the construction industry in Hong Kong, in which both the government and industry have called for wider use of VM, and yet users often encounter difficulties that are attributable to the large number of participants and short duration of the workshops.

Dynamics of Project-Based Collaborative Networks for BIM Implementation: Analysis Based on Stochastic Actor-Oriented Models

AbstractIn the project-based construction industry, organizations are coupled with each other largely through project-specific collaborative relationships, and the industry-level networks of these ...

Location-based measurement and visualization for interdependence network on construction sites

Abstract Appropriately assigning workers to tasks is vitally important in project management. To do this, project managers need to objectively and effectively measure and visualize the spatiotemporal orders of real construction process as well as coordination structure of the workforce. However, currently there is no method/tool available to project managers to represent spatiotemporal orders of construction processes. To address this issue, this paper presents a novel approach to measuring the real spatiotemporal order of onsite tasks as well as the task interdependence by an interdependence network. This approach extracts the distance of workspace distributions as a key interdependence indicator from historical location tracks across different construction stages according to the area-restricted nature of construction activities. It then integrates generated interdependence into a network over time, to imply the cooperation patterns in stages and a task delivery across stages with a holistic view. To validate the approach, location data were collected from 31 workers working in a high-rise housing construction project for one week to construct the interdependence network of this project, which was used to quantitatively evaluate the performance of construction schedule, assignments and cooperation. Results show that the interdependence network is able to provide insightful information on how workers perform individual tasks onsite and it is also an effective tool to identify and display the interactions among site workers.

Using Switching State-Space Model to Identify Work States Based on Movement Data

A key question in the construction industry is the productivity issue. With a variety of activities on sites from pip-installation to concrete placement, how to assess the working/non-working states in order to promote time allocation and productivity next time? This paper proposes to utilize switching state-space model integrated with first-difference random walk to recognize working and non-working behavioral modes through turning angles, step length, etc., containing four main steps: eliminate errors by forward/backward-averaging filter, establish the State-Space Model of a couple states with initial prior distributions that is called Switching State-Space Model (SSSM) enabling bidirectional transitions between states, estimate posterior distributions of parameters by Bayesian inference using Gibbs sampling, and analyze the objective work rate, time allocation, and productivity. A pilot study comprised of 24 workers from a housing project is finally conducted to test the proposed model and process.

Recognizing diverse construction activities in site images via relevance networks of construction-related objects detected by convolutional neural networks

AbstractTimely and overall knowledge of the states and resource allocation of diverse activities on construction sites is critical to resource leveling, progress tracking, and productivity analysis...

Hierarchical Bayesian Model of Worker Response to Proximity Warnings of Construction Safety Hazards: Toward Constant Review of Safety Risk Control Measures

AbstractQuickly changing and complicated workplace conditions, which are typical of construction projects, have always been contributing to the poor safety record of the construction industry. Howe...