Incident Causation Model for Improving Feedback of Safety Knowledge

In order for the construction industry to improve its poor safety performance it needs to learn from its mistakes and put the lessons learned to good use. This need calls for effective feedback mechanisms that can transmit information derived from incident investigation to be utilized in safety planning. The feedback should be at two levels; first, feedback to the Safety Management System that had failed, and second, feedback to the safety planning of future projects. The first level of feedback can be achieved by basing the investigation on an incident investigation model that explicitly identifies system failure. The second level of feedback can be achieved if both incident investigation and safety planning share the same incident causation model, such that the information from each process can be retrieved and utilized in the other process smoothly. One prerequisite to fulfill the two levels of feedback is the development of an incident causation model. In this paper, the modified loss causation model (MLCM), which is able to meet the above-mentioned purposes, will be presented. The MLCM is developed based on an extensive literature review and application on 140 actual accident cases obtained from Singapore’s Ministry of Manpower, Occupational Safety Department. In this paper, the model’s application will be demonstrated through a case study, which involves codification of investigation information based on an actual incident report, and a safety planning process based on a hypothetical case.     

Case-Based Reasoning for Construction Hazard Identification: Case Representation and Retrieval

This paper proposes a case-based reasoning (CBR) approach to construction hazard identification that facilitates systematic feedback of past knowledge in the form of incident cases and hazard identification. This paper focuses on two of the key components of the CBR approach: (1) a detailed knowledge representation scheme, developed based on the modified loss causation model, to codify incident cases and past hazard identification and (2) an intelligent retrieval mechanism that can automatically retrieve relevant past cases. The detailed knowledge representation scheme presented herein is designed to model both incident cases and hazard identification so that both types of knowledge repository can be retrieved simultaneously and adapted for use. The scheme also includes a linguistic structure used to facilitate indexing of cases. The retrieval mechanism is based on the concept of similarity scoring. In this paper, a novel scoring technique based on semantic networks is presented. A case study is presented to demonstrate and validate the proposed approach.     

Alternatives to seclusion in psychiatric care

The use of seclusion in psychiatry is declining. Its punitive nature has been acknowledged and alternative, more therapeutic approaches are needed to deal with disturbed patients. What alternatives are available? This article reports a study that sought to examine the response to incidents that formerly would have led to seclusion in one psychiatric intensive care unit. The sample consisted of 50 incidents. Information on the incident and subsequent action was recorded on standard incident forms and specially designed data collection sheets. The most frequent type of incident was damage to property, followed by direct or threatened physical assault on staff. The most common response was one-to-one nursing support, followed by the use of medication. In just over half the incidents, both responses were used together. This therapeutic strategy demonstrates that aggressive incidents can be dealt with safely without recourse to seclusion.     

Competency-Based Model for Predicting Construction Project Managers’ Performance

Using behavioral competencies to influence human resource management decisions is gaining popularity in business organizations. This study identifies the core competencies associated with the construction management role and, further, develops a predictive model to inform human resource selection and development decisions within large construction organizations. A range of construction managers took part in behavioral event interviews where staff were asked to recount critical management incidents, decisions, and actions from which their key competencies could be identified. By delineating the sample according to their levels of performance measured against a range of role-specific performance criteria, the competencies defining superior management performance could be determined. These were then used to construct a logistic regression model from which a project manager’s performance can be predicated. The validated results reveal that “self-control” and “team leadership” are the most predictive behaviors of effective project management performance within the framework of the model. The paper explores the potential role and application of the framework to underpin human resource management decision making with regards to recruitment, performance management, succession planning, and resource allocation.     

ISO13528与NATA能力验证尧敦图的统计模型比较

对ISO13528和澳大利亚国家检测机构协会(NATA)所用的能力验证尧敦图的统计模型进行了讨论,分别利用霍特林T²检验和二维正态分布推导出尧敦椭圆方程的公式,使用Excel软件绘制出尧敦椭圆,参与能力验证的各个实验室的分析数据也在同一个图中显示出来。利用坐标变换,还得到了其他不同坐标下的尧敦图。在一个尧敦图中同时绘制出置信水平分别为95%和99%的尧敦椭圆,直观显示出合格数据、存疑数据和不合格数据。ISO 13528中,Z_A,B是系统误差和随机误差的组合,利用主成分分析,可以将他们区分和表示出来。由于原始数据不总是正态分析,且采用了不同的数学模型,NATA方法得到的尧敦椭圆和ISO 13528得到的尧敦椭圆有时是不同的。     

Incident reporting in acute pain management

Incident reporting is an effective tool for continuous quality improvement in clinical practice. A prospective study on voluntary incident reporting in pain management was conducted at a major teaching hospital in Hong Kong. Over a 12-month period, 53 incidents were reported in 1275 patients who received pain relief treatments which were supervised by the acute pain service. The majority of the incidents were first detected by the pain team. The most common incidents involved delivery circuits, delivery pump and drug administration. A large proportion (81.4%) of the incidents were thought to be preventable. Human factors were involved in 41.9% of the patients reported, most commonly associated with unfamiliar technique/inexperience, inattention and inadequate communication. Four patients developed major morbidity of which two were attributed to inadequate analgesia, while three others had major physiological changes without morbidity. Strategies have been formulated to prevent further occurrence of these incidents. We propose that incident reporting is a potentially useful tool in identifying and preventing adverse events in postoperative pain management.     

Downgrading Construction Incidents

The financial losses resulting from various incidents on typical building construction sites are reported. Field data was collected on three sites over a period of nine months. Incidents were recorded by three observers on a daily basis including data on the cause of the event, the direct losses incurred and the contractors involved. The 658 incidents reported were analyzed to determine the general characteristics of incidents, the level of field control possible and the incident costs. Overall losses on the individual sites are compared while combined results for all three projects are examined. Particular attention is paid to safety‐related incidents. Limitations of the monitoring program are discussed. The results indicate that downgrading incidents are responsible for a substantial loss on construction projects, however, the observations show that most losses could be eliminated through up‐graded on‐site management. Recommendations are made for reducing the losses by improving such management functions as planning, scheduling, follow‐up, equipment maintenance and problem documentation.     

岩体质量分类的PCA-RF模型及应用

为了更合理地确定岩体质量类别,将主成分分析（PCA）与随机森林（RF）算法相结合,提出一种岩体质量分类的PCA-RF模型。选取能够充分反映岩体质量类别的5项指标进行分析,运用主成分分析法对各指标进行相关性处理,依据方差累计贡献率得出3个主成分,从而消除指标间的相关性,减少模型输入。然后采用随机森林模型对岩体质量进行分类,选用现场20组数据作为训练样本、10组数据作为测试样本,利用交叉验证的方法估计泛化误差。结果表明,该方法分类结果与实际结果较吻合,平均准确率达96.7%,同时得出岩体质量所处类别的概率分布,进一步反映岩体质量的复杂度,为工程建设提供更详细的参考依据。     

多火孔无焰陶瓷燃烧器顶燃式热风炉的数值模拟

采用CFD软件的FLUENT对多火孔无焰陶瓷燃烧器顶燃式热风炉进行了数值模拟。计算中采用了基于概率密度函数的PDF燃烧模型、P1辐射模型、标准κ-ε湍流模型,建立了三维计算模型,划分了四面体和六面体混合网格。主要对温度场、速度场、可燃物浓度场进行了计算与分析,计算结果与资料介绍的热风炉运行结果基本一致。     

Modelling age-specific risk: application to dementia

We give up-to-date methods for estimating the age-specific incidence of a disease and for estimating the effect of risk factors. We recommend taking age as the basic time scale of the analysis; then, the hazard function can be interpreted as the age-specific incidence of the disease. This choice raises a delayed entry problem. We present three methods: the person-years method; the smoothed Nelson-Aalen estimator, and the penalized likelihood approach. When explanatory variables are available, the Poisson model and the Cox model with delayed entry may be used for estimating relative risks; the penalized likelihood approach can also be used. We apply these methods to estimate the age-specific incidence of dementia using data from a large cohort study, Paquid. This 5-year study followed a random initial sample of 3675 subjects with 190 incident cases of dementia. We compare the estimates based on the three possible methods. The estimated incidences computed separately for men and women cross and it is verified that a non-proportional hazards model for gender holds; women below 75 have a lower risk than men while women above 75 have a higher risk.     

Describing a Beta Probability Distribution Function for Construction Simulation

A typical proposed application for a construction simulation model is to assess the productivity of a future operation. This type of application inherently presents the modeler with a situation where there is only a limited amount of data available for choosing an underlying probability distribution function (PDF). This paper presents a formulation for developing a Beta PDF for use in construction simulation modeling. The hypothesis of this paper is that there is a ratio that relates the 75th percentile to the mode of the activity duration. The research demonstrates that using such ratios, along with the minimum, mode, and maximum activity durations, results in estimates of a beta PDF that accurately describes the underlying duration distribution of construction activities. In the methodology proposed here the minimum and maximum activity durations are predicted using deterministic methods based on the physical characteristics of the job and equipment employed. The beta-shaped parameters a and b are estimated using a procedure for fitting beta distributions to activity times when sample data are not available.     

Driver fatigue in the city

The current survey investigates the features of driver fatigue incidents (accidents, near accidents and unintentional drifting-out-of-lane events) which occurred in cities. The results show similar patterns to previous surveys, with incident trips tending to be short, and prior sleep loss and late night driving featuring as factors. Work trips feature very strongly among city fatigue incident trips and work is also a common reason for sleep loss before a fatigue incident. Consistent with the high representation of work trips, there are peaks in incident occurrence at commuter travel times. Shiftworkers are prominent amongst fatigue incident-involved drivers. Social trips also feature amongst fatigue incident trips but are likely to be more difficult to address with countermeasures.     

Human Factors Analysis Classification System Relating to Human Error Awareness Taxonomy in Construction Safety

In several studies it is widely accepted that human error is the main reason for up to 80% of all incidents and accidents in complex high-risk systems that exist in the aviation, petrochemical, healthcare, construction, mining, and nuclear power industries. The construction industry, greatly impacted by accidents, is accountable for more than 1,000 fatalities in each of the past 14 years. The human factors analysis classification system (HFACS) is a general human error framework originally developed and tested as a tool for investigating and analyzing the human causes of accidents with applications to rail, air, and offshore environments. This paper introduces the concept of HFACS along with the framework of human error awareness training (HEAT) and their potential contribution to the construction industry. Based on the HEAT approach, this paper proposes a new error analysis educational and classification tool for safety within the construction industry. The primary difference between HFACS and HEAT is found in the structure, content, and presentation of the information allowing for higher effectiveness in incident investigation and safety education and training in construction.     

Probabilistic Model for Polycrystalline Microstructures with Application to Intergranular Fracture

A two part probabilistic model for polycrystalline microstructures is described. The model utilizes a Poisson–Voronoi tessellation for the grain geometry and a vector random field model for the crystallographic orientation. The grain geometry model is calibrated to experimental data through the intensity of the Poisson point field underlying the Poisson–Voronoi tessellation and the orientation random field is calibrated to experimental data through its marginal distributions and second moment properties. Realizations of the random microstructure are generated by use of translation methods and are used, with simplified mechanical models, to investigate the problem of intergranular fracture. It is found that intergranular cracks exhibit some statistical properties of a scaled Brownian motion process.     

Case-Based Reasoning Approach to Construction Safety Hazard Identification: Adaptation and Utilization

Risk assessment, consisting of hazard identification and risk analysis, is an important process that can prevent costly incidents. However, due to operational pressures and lack of construction experience, risk assessments are frequently poorly conducted. In order to improve the quality of risk assessments in the construction industry, it is important to explore the use of artificial intelligence methods to ensure that the process is efficient and at the same time thorough. This paper describes the adaptation process of a case-based reasoning (CBR) approach for construction safety hazard identification. The CBR approach aims to utilize past knowledge in the form of past hazard identification and incident cases to improve the efficiency and quality of new hazard identification. The overall approach and retrieval mechanism are described in earlier papers. This paper is focused on the adaptation process for hazard identification. Using the proposed CBR approach, for a new work scenario (the input case), a most relevant hazard identification tree and a set of incident cases will be retrieved to facilitate hazard identification. However, not all information contained in these cases are relevant. Thus, less relevant information has to be pruned off and all the retrieved information has to be integrated into a hazard identification tree. The proposed adaptation is conducted in three steps: (1) pruning of the retrieved hazard identification tree; (2) pruning of the incident cases; and (3) insertion of incident cases into the hazard identification tree. The adaptation process is based on the calculation of similarity scores of indexes. A case study based on actual hazard identifications and incident cases is used to validate the feasibility of the proposed adaptation techniques.     

Bayesian Modal Updating using Complete Input and Incomplete Response Noisy Measurements

The problem of identification of the modal parameters of a structural model using complete input and incomplete response time histories is addressed. It is assumed that there exist both input error (due to input measurement noise) and output error (due to output measurement noise and modeling error). These errors are modeled by independent white noise processes, and contribute towards uncertainty in the identification of the modal parameters of the model. To explicitly treat these uncertainties, a Bayesian framework is adopted and a Bayesian time-domain methodology for modal updating based on an approximate conditional probability expansion is presented. The methodology allows one to obtain not only the optimal (most probable) values of the updated modal parameters but also their uncertainties, calculated from their joint probability distribution. Calculation of the uncertainties of the identified modal parameters is very important if one plans to proceed with the updating of a theoretical finite-element model based on these modal estimates. The proposed approach requires only one set of excitation and corresponding response data. It is found that the updated probability density function (PDF) can be well approximated by a Gaussian distribution centered at the optimal parameters at which the posterior PDF is maximized. Numerical examples using noisy simulated data are presented to illustrate the proposed method.     

Violence and aggression in psychiatric units

OBJECTIVE: To help predict aggressive and violent behaviors, the frequency and types of these behaviors in acute psychiatric inpatient settings were examined, and potential interactions between staffing and patient mix and rates of the behaviors were explored. METHODS: Data on violent incidents were gathered prospectively in three adult acute psychiatric units in a general hospital and two units in a primary psychiatric hospital in Sydney, Australia. Staff recorded violent and aggressive incidents, which were ranked on an 8-level scale. They also completed weekly reports of staffing levels and patient mix. Poisson regression analysis was used to calculate relative rates, 95 percent confidence intervals, and p values. RESULTS: A total of 1,289 violent incidents were recorded over a seven-month period. Based on the scale, 58 percent of the incidents were serious. Seventy-eight percent were directed toward nursing staff. Complex relationships between staffing, patient mix, and violence were found. Relative risk increased with more nursing staff (of either sex), more nonnursing staff on planned leave, more patients known to instigate violence, a greater number of disoriented patients, more patients detained compulsorily, and more use of seclusion. The relative risk decreased with more young staff (under 30 years old), more nursing staff with unplanned absenteeism, more admissions, and more patients with substance abuse or physical illness. In total these factors accounted for 62 percent of the variance in violence. CONCLUSIONS: Violent incidents in psychiatric settings are a frequent and serious problem. Incidents appear to be underreported, and the seriousness of an incident does not guarantee it will be reported.     

Development of Causal Model of Construction Accident Causation

Accidents occur in all types of construction activities. The accident causation process is complex. Accident prevention requires a comprehensive understanding of this complex process. This paper proposes a conceptual, but practical, model of accident causation for the construction industry, highlighting the underlying and complex interaction of factors in the causation process. The model describes the constraints and responses experienced by the parties involved in project conception, design, and construction, which may affect accident causation. This paper details theoretical findings of research currently being conducted at UMIST. Both proximal and distal factors are considered (for example, operative factors, site environment and systems of work, and project management and organizational issues). A study of 500 accident records provided by the U.K. Health and Safety Executive shows that accidents in construction projects involve inappropriate construction planning (28.8%), inappropriate construction control (16.6%), inappropriate construction operation (88.0%), inappropriate site condition (6.0%), and inappropriate operative action (29.9%). Data currently available are, in some respects, inadequate and will need to be supplemented, in the future, by extended accident investigations.