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SHERPA: A systematic human error reduction and prediction approach

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David Embrey at Human Reliability Associates
David Embrey
  • Human Reliability Associates
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Abstract

This paper describes a Systematic Human Error Reduction and Prediction Approach (SHERPA) which is intended to provide guidelines for human error reduction and quantification in a wide range of human-machine systems. The approach utilises as its basis current cognitive models of human performance.
SHERPA 19
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SHERPA 19
86.PDF
Content uploaded by David Embrey
Author content
All content in this area was uploaded by David Embrey on Apr 16, 2017
Content may be subject to copyright.
... Based on clinical experience, and data such as NAP4, we know that there may be some unpredictability and occasional catastrophic failures. Despite the inherent risks, there is a limited number of studies available on actions and decision-making as it relates to airway management in the clinical environment for a long-time engineer have had mechanisms and techniques [6] that enable them to analyse complex processes. These tools may allow systematic analysis of the airway management process if supported by robust, clinically credible data. ...
... Each goal, task and sub-task was represented by using a flow chart diagram ( Figure 1). The Systematic Human Error Reduction and Prediction Approach (SHERPA) [6] was then used to examine the task steps at the lowest level of the HTA in more detail. ...
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Should I Evaluate My Augmented Reality System in an Industrial Environment? Investigating the Effects of Classroom and Shop Floor Settings on Guided Assembly
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Numerous prior studies have investigated real-time assembly instructions using Augmented Reality (AR). However, most such experiments were conducted in laboratory settings with simplistic assembly tasks, failing to represent real-world industrial conditions. To ascertain to what extent results obtained in a laboratory environment may differ from studies in actual industrial environments, we carried out a user study with 32 manufacturing apprentices. We compared assembly task execution results in two settings, a classroom and an industrial workshop environment. To facilitate the experiments, we developed AR-guided manual assembly systems for simple and more complex assets. Our findings reveal a significantly improved task performance in the industrial workshop, reflected in faster task completion times, fewer errors, and subjectively perceived higher flow. This contradicted participants' subjective ratings, as they expected to perform better in the classroom environment. Our results suggest that the actual manufacturing environment is critical in evaluating AR systems for real-world industrial applications.
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Total Knee Arthroplasty With Robotic and Augmented Reality Guidance: A Hierarchical Task Analysis
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  • Jun 2024
Background Total knee arthroplasty (TKA) is a commonly performed procedure that has traditionally utilized reproducible steps using a set of mechanical instruments. The number of TKAs performed using robotic assistance is increasing, and augmented reality (AR) navigation systems are being developed. Hierarchical task analysis (HTA) aims to describe the steps of a specific task in detail to reduce errors and ensure reproducibility. The objective of this study was to develop and validate HTAs for conventional, robotic-assisted, and AR-navigated TKA. Methods The development of HTAs for conventional TKA involved an iterative review process that incorporated the input of 4 experienced arthroplasty surgeons. The HTAs were then adapted for robotic-assisted and AR-navigated TKA by incorporating specific steps associated with the use of these systems. The accuracy and completeness of the HTAs were validated by observing 10 conventional and 10 robotic-assisted TKA procedures. Results HTAs for conventional, robotic-assisted, and AR-navigated TKA were developed and validated. The resulting HTAs provide a comprehensive and standardized plan for each procedure and can aid in the identification of potential areas of inefficiency and risk. Robotic-assisted and AR-navigated approaches require additional steps, and there are an increased number of instances where complications may occur. Conclusions The HTAs developed in this study can provide valuable insights into the potential pitfalls of robotic-assisted and AR-navigated TKA procedures. As AR-navigation systems are developed, they should be optimized by critical analysis using the developed HTAs to ensure maximum efficiency, reliability, accessibility, reduction of human error, and costs.
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Hierarchical Task Analysis and Training Decisions
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The technique of hierarchical task analysis (HTA), proposed by Annett et al. (1971), which requires the analyst to describe a task in terms of a hierarchy of operations and plans, is reviewed and examined as a basis for making training decisions. The basic ideas as originally stated are in the main accepted, with some qualifications. The benefit of neutrally stated operations is emphasized as a means of establishing agreement between the analyst and the sponsor of the work, before more speculative human factor decisions are undertaken. The necessity of plans as statements of the conditions under which operations are carried out is stressed. The benefits of a hierarchical description in terms of economy of analysis and a means of accounting for complex performance are outlined. But the value of retaining the input‐action‐feedback classification as an integral part of HTA is questioned. HTA facilitates training design in a number of ways: by raising non‐training issues and thereby clarifying training content; by clarifying training objectives and requiring training hypotheses to be stated routinely; and by indicating how the training of even complex decision‐making tasks can be programmed. While emphasizing that the analyst must often bring to bear other techniques and knowledge of training to make full use of HTA, suggestions are made regarding research into training classification schemes which could simplify training decisions for non‐experts.
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