Comparing the bullwhip effect under different inventory policies in engineering project supply chains

Measuring bullwhip effect is useful for making better controls on production planning and enhancing the supply chain operating efficiency.First,this article establishes the comparative analysis model of bullwhip effect between(s,S)and Periodic Review(PR)inventory policy based on the quantitative bullwhip effect model under different inventories.Then,the impacts of lead time,inventory review time,autocorrelation coefficient,and the number of samples on the gap of bullwhip effect under(s,S)and PR IP are analyzed.The results show that bullwhip effect in PR is more intense than(s,S)inventory policy.Contractors should pay more attention to control bullwhip effect when adopting PR inventory policy to enhance the total operating efficiency of the engineering project supply chains.     

Computer vision techniques for construction safety and health monitoring

For construction safety and health, continuous monitoring of unsafe conditions and action is essential in order to eliminate potential hazards in a timely manner. As a robust and automated means of field observation, computer vision techniques have been applied for the extraction of safety related information from site images and videos, and regarded as effective solutions complementary to current time-consuming and unreliable manual observational practices. Although some research efforts have been directed toward computer vision-based safety and health monitoring, its application in real practice remains premature due to a number of technical issues and research challenges in terms of reliability, accuracy, and applicability. This paper thus reviews previous attempts in construction applications from both technical and practical perspectives in order to understand the current status of computer vision techniques, which in turn suggests the direction of future research in the field of computer vision-based safety and health monitoring. Specifically, this paper categorizes previous studies into three groups—object detection, object tracking, and action recognition—based on types of information required to evaluate unsafe conditions and acts. The results demonstrate that major research challenges include comprehensive scene understanding, varying tracking accuracy by camera position, and action recognition of multiple equipment and workers. In addition, we identified several practical issues including a lack of task-specific and quantifiable metrics to evaluate the extracted information in safety context, technical obstacles due to dynamic conditions at construction sites and privacy issues. These challenges indicate a need for further research in these areas. Accordingly, this paper provides researchers insights into advancing knowledge and techniques for computer vision-based safety and health monitoring, and offers fresh opportunities and considerations to practitioners in understanding and adopting the techniques.     

EnvironalPlanning: Analytic Network Process Model for Environmentally Conscious Construction Planning

Although the construction pollution index has been put forward and proved to be an efficient approach to reducing or mitigating pollution level during the construction planning stage, the problem of how to select the best construction plan based on distinguishing the degree of its potential adverse environmental impacts is still a research task. This paper first reviews environmental issues and their characteristics in construction, which are critical factors in evaluating potential adverse impacts of a construction plan. These environmental characteristics are then used to structure two decision models for environmental-conscious construction planning by using an analytic network process (ANP), including a complicated model and a simplified model. The two ANP models are combined and called the EnvironalPlanning system, which is applied to evaluate potential adverse environmental impacts of alternative construction plans.     

Physiological condition monitoring of construction workers

Monitoring of workers' physiological conditions can potentially enhance construction workforce productivity, safety, and well-being. Recently, Physiological Status Monitors (PSMs) were validated as an accurate technology to assess physiological conditions during typical sport science and medicine testing procedures (e.g., treadmill and cycle ergometer protocols). However, sport science and medicine testing procedures cannot simulate routine construction worker movements in a comprehensive manner. Thus, this paper investigated the validity of two PSMs by comparing their measurements with gold standard laboratory instruments' measurements at rest and during dynamic activities resembling construction workforce's routine activities. Two physiological parameters such as heart rate and breathing rate were considered. Ten apparently healthy subjects participated in the study. One of the PSMs proved to be a viable technology in assessing construction workers' heart rate (correlation coefficient ≥ 0.74; percentage of differences within ± 11 bpm ≥ 84.8%).     

A deep learning-based method for detecting non-certified work on construction sites

The construction industry is a high hazard industry. Accidents frequently occur, and part of them are closely relate to workers who are not certified to carry out specific work. Although workers without a trade certificate are restricted entry to construction sites, few ad-hoc approaches have been commonly employed to check if a worker is carrying out the work for which they are certificated. This paper proposes a novel framework to check whether a site worker is working within the constraints of their certification. Our framework comprises key video clips extraction, trade recognition and worker competency evaluation. Trade recognition is a new proposed method through analyzing the dynamic spatiotemporal relevance between workers and non-worker objects. We also improved the identification results by analyzing, comparing, and matching multiple face images of each worker obtained from videos. The experimental results demonstrate the reliability and accuracy of our deep learning-based method to detect workers who are carrying out work for which they are not certified to facilitate safety inspection and supervision.     

Distributed and interoperable simulation for comprehensive disaster response management in facilities

Disaster-related simulations can be helpful for conducting various analysis on damage evaluations and response operations in damaged facilities. However, no single simulation can solve all the functional needs for complex disaster situations due to diverse disasters, damage types, and response efforts. To address these issues, the authors have developed a distributed simulation platform for a comprehensive analysis of facility damage and response operations, which can be flexibly applied to diverse disaster situations. The High Level Architecture is adopted to synchronize different federates such as simulation models and incoming data streams within an interoperable simulation environment. The developed simulation platform includes five different disaster-related federates such as the Fire Dynamics Simulator, USGS earthquake data feeds, OpenSees structure response simulation, evacuation simulation, and restoration simulation. The accuracy of interactions among different federates was confirmed with the case simulations of a facility fire evacuation and an earthquake restoration situation. The developed platform provides a flexible and interoperable distributed simulation environment for comprehensive disaster response management of unexpected disaster situations while promoting reusability and future extendibility of existing and newly-added disaster-related simulations.     

A feasibility study of using smartphone built-in accelerometers to detect fall portents

Fall accidents contribute to nearly half of all fatalities in the construction industry in Taiwan. Detecting fall portents using a smartphone, which many people carry daily, may help reduce fall accidents if the accuracy is acceptable. We designed two experiments with three algorithms to evaluate how well a smartphone can detect both falls and fall portents in a tiling operation scenario. The experiments show that work-related motions barely affected the detection of falls, and the result had a sensitivity and specificity of 100% and 96.1%, respectively. However, for detecting portents, the work-related motions had quite a large impact on the gyroscope-based algorithm, which demonstrated an accuracy rate of only 4.3%, but had only limited impact on the accelerometer-based algorithm, which still show acceptable accuracy rates of 73.5% and 88.5%. We conclude that using a smartphone to detect falls and portents in a construction site is feasible.     

Transportation interface facilities design using interactive high-level computer graphics

A prototype pedestrian facilities design system is described. The design system exploits the capabilities of an intelligent high-resolution vector graphics workstation which features a highly interactive computer graphics environment. A summary of historical developments in pedestrian facility design and graphics workstation architecture is presented, followed by a discussion of the stochastic model and interactive computer graphics features utilized by a prototype facilities design system. Potential applications of such a design system are discussed, and promising areas of future development are outlined.     

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.     

Strengths, Weaknesses, Opportunities, and Threats for Foreign-Invested Construction Enterprises: A China Study

China has been attracting overseas construction enterprises with its vast expanding business market. The country is further opening its construction market to overseas businesses as the result of its accession to the World Trade Organization in 2001. In line with this development, there are an increasing number of foreign-invested construction enterprises (FICEs) entering into the market. Using Porter’s competitiveness factor analysis method, this paper identifies the FICEs’ strengths, weaknesses, opportunities, and threats in the Chinese construction market. Data used in the analysis stem from multiple sources including statistical reports, literature review, regulations and policies, and interviews with construction professionals. These findings should provide a valuable reference for overseas construction enterprises who are interested in developing business in the Chinese construction market.