Energy-based safety risk assessment: does magnitude and intensity of energy predict injury severity?

Hallowell, Matthew R.; Alexander, Dillon; Gambatese, John

doi:10.1080/01446193.2016.1274418

Cited by 34 publications

(5 citation statements)

References 35 publications

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“…7), the most predictive attributes of the medical case category are high-energy attributes (e.g., 'powered tool', 'machinery', 'electricity'), while for the first aid level, the top attributes are associated with low energy tasks (e.g., 'repetitive motion', 'nail', 'small particles'). This observation is in accordance with the assumption that the amount of energy in the environment is ultimately what governs injury severity [37].…”

Section: Qualitative Results: Attribute Importance Scoressupporting

confidence: 89%

AI-based Prediction of Independent Construction Safety Outcomes from Universal Attributes

Baker¹,

Hallowell²,

Tixier³

2019

Preprint

Self Cite

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Highlights• This paper significantly improves on and validates "Application of Machine Learning to Construction Injury Prediction" (Tixier et al. 2016 [1]).• NLP is used to extract attributes from a large dataset of injury reports and machine learning models are trained to predict independent safety outcomes (human annotations).• Four safety outcomes are predicted: injury severity, injury type, bodypart impacted, and incident type.• Random Forest, XGBoost and linear SVM are compared and combined through model stacking.• Results show that attributes are still highly predictive, even for the injury severity outcome. An analysis of per-category attribute importance scores is performed.

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Section: Qualitative Results: Attribute Importance Scoressupporting

confidence: 89%

AI-based Prediction of Independent Construction Safety Outcomes from Universal Attributes

Baker¹,

Hallowell²,

Tixier³

2019

Preprint

Self Cite

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“…Viner 51 defined hazard as “a source of potentially damaging energy”, with damage involving release and transfer of energy over time (p. 42). More recently, Hallowell et al 52 . showed that the energy transfer concept applies to, and has predictive validity in, construction.…”

Section: Model‐based Risk Theorymentioning

confidence: 99%

Model‐based risk analysis for system design

Mendes

2023

Systems Engineering

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Despite being the dominant risk analysis paradigm, event guessing is useless for systems design. In management, no event guessing has ever preempted the launch of policies that are decided, not designed. In engineering, events are not guessed; rather, they are created for testing purposes. Events provide inputs to which systems respond according to their structure, as described by state‐space or equivalent System Dynamics models. A new risk analysis framework draws design support information from model attributes. Risk‐informed dynamic models help design physical architectures or organizational policies that capably respond to arbitrary events. The approach builds on the notion that all inputs carry energy. Physical or policy systems change states by trading energy with the surroundings, through expected transactions and unexpected disturbances. A non‐probabilistic risk framework supports the design by showing that the system exhibits intended functionality when responding to arbitrary inputs. Instead of guessing countless hypothetical events, the framework systematically and comprehensively analyzes weaknesses in the system model using a programmed algorithm. It applies to any state‐space dynamic model by defining risk as a function of the energy needed to move the system from an acceptable to a faulty state. Robust systems dissipate excess energy, whereas vulnerable systems lose functionality. Fuses and cushions are generic classes of protections. Placing them into system models at identified weak points helps improve design. Two published simple models of business policies illustrate the framework, which is extended to define measures for consequence and uncertainty as functions of acceptable and faulty states.

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“…accidents data) to new situations and projects [39,40]. Despite these significant advancements, there is still a dearth of research that investigates the scientific extension and practical application of hazard energy within occupational safety [41].…”

Section: Energy Source Recognitionmentioning

confidence: 99%

Industrial Safety Management Using Innovative and Proactive Strategies

Song¹,

Awolusi²

2021

Concepts, Applications and Emerging Opportunities in Industrial Engineering

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Safety is considered a top priority due to its significance in safeguarding human lives and properties, especially in high-risk industrial sectors such as aviation, oil and gas, construction, transportation, steel manufacturing, and mining industries. These industries are plagued by workplace injuries, illnesses, and fatalities because of the dangerous work environments. As such, it is very vital to integrate safety into every work process in any industrial environment just like quality is built into products and services. It is important to establish and execute an effective safety management system to prevent the risks of irreversible accidents. This chapter begins with a background to safety management in industrial engineering and a discussion of the various issues of industrial safety management. It follows with an extensive description of existing and commonly used safety performance measurement methods. Several case studies are used to explain the methods and explore the important application areas relevant to most industrial sectors. The techniques and tools for safety data collection, analysis, and sharing are introduced together with their applications for safety management. The last section explains how emerging technologies can be implemented in most industrial sectors to enhance safety management.

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Energy-based safety risk assessment: does magnitude and intensity of energy predict injury severity?

Cited by 34 publications

References 35 publications

AI-based Prediction of Independent Construction Safety Outcomes from Universal Attributes

AI-based Prediction of Independent Construction Safety Outcomes from Universal Attributes

Model‐based risk analysis for system design

Industrial Safety Management Using Innovative and Proactive Strategies

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