Coupling Digital Human Modeling with Early Design Stage Human Error Analysis to Assess Ergonomic Vulnerabilities

2018 ◽

Cited By ~ 2

Author(s):

Salman Ahmed ◽

Mihir Sunil Gawand ◽

Lukman Irshad ◽

H. Onan Demirel

Keyword(s):

Human Factors ◽

Surrogate Model ◽

Human Performance ◽

Design Method ◽

Human Subjects ◽

Design Stage ◽

Digital Human Modeling ◽

Design Variables ◽

Human Modeling ◽

Digital Human

Computational human factors tools are often not fully-integrated during the early phases of product design. Often, conventional ergonomic practices require physical prototypes and human subjects which are costly in terms of finances and time. Ergonomics evaluations executed on physical prototypes has the limitations of increasing the overall rework as more iterations are required to incorporate design changes related to human factors that are found later in the design stage, which affects the overall cost of product development. This paper proposes a design methodology based on Digital Human Modeling (DHM) approach to inform designers about the ergonomics adequacies of products during early stages of design process. This proactive ergonomics approach has the potential to allow designers to identify significant design variables that affect the human performance before full-scale prototypes are built. The design method utilizes a surrogate model that represents human product interaction. Optimizing the surrogate model provides design concepts to optimize human performance. The efficacy of the proposed design method is demonstrated by a cockpit design study.

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Identification of Human Errors During Early Design Stage Functional Failure Analysis

Volume 1B: 38th Computers and Information in Engineering Conference ◽

10.1115/detc2018-85979 ◽

2018 ◽

Cited By ~ 2

Author(s):

Lukman Irshad ◽

Salman Ahmed ◽

Onan Demirel ◽

Irem Y. Tumer

Keyword(s):

Failure Analysis ◽

Human Error ◽

System Level ◽

Design Stage ◽

Human Factors Engineering ◽

Human Errors ◽

Functional Failure ◽

Early Design ◽

Early Design Stage ◽

Early Design Stages

Detection of potential failures and human error and their propagation over time at an early design stage will help prevent system failures and adverse accidents. Hence, there is a need for a failure analysis technique that will assess potential functional/component failures, human errors, and how they propagate to affect the system overall. Prior work has introduced FFIP (Functional Failure Identification and Propagation), which considers both human error and mechanical failures and their propagation at a system level at early design stages. However, it fails to consider the specific human actions (expected or unexpected) that contributed towards the human error. In this paper, we propose a method to expand FFIP to include human action/error propagation during failure analysis so a designer can address the human errors using human factors engineering principals at early design stages. To explore the capabilities of the proposed method, it is applied to a hold-up tank example and the results are coupled with Digital Human Modeling to demonstrate how designers can use these tools to make better design decisions before any design commitments are made.

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Using Automated Use Case Generation for Early Design Stage Functional Failure and Human Error Analysis

Volume 1: 39th Computers and Information in Engineering Conference ◽

10.1115/detc2019-98466 ◽

2019 ◽

Cited By ~ 1

Author(s):

Lukman Irshad ◽

H. Onan Demirel ◽

Irem Y. Tumer

Keyword(s):

Human Error ◽

Large Scale ◽

Design Stage ◽

Test Case ◽

Use Case ◽

Human Errors ◽

Functional Failure ◽

Early Design ◽

Early Design Stage ◽

Complex Engineered Systems

Abstract Human errors and poor ergonomics are attributed to a majority of large-scale accidents and malfunctions in complex engineered systems. Human Error and Functional Failure Reasoning (HEFFR) is a framework developed to assess potential functional failures, human errors, and their propagation paths during early design stages so that more reliable systems with improved performance and safety can be designed. In order to perform a comprehensive analysis using this framework, a wide array of potential failure scenarios need to be tested. Coming up with such use cases that can cover a majority of faults can be challenging or even impossible for a single engineer or a team of engineers. In the field of software engineering, automated test case generation techniques have been widely used for software testing. This research explores these methods to create a use case generation technique that covers both component-related and human-related fault scenarios. The proposed technique is a time based simulation that employs a modified Depth First Search (DFS) algorithm to simulate events as the event propagation is analyzed using HEFFR at each timestep. This approach is applied to a hold-up tank design problem and the results are analyzed to explore the capabilities and limitations.

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Extending the Capabilities of Digital Human Modeling: A Design Framework to Assess Emergencies Early in Design

Volume 6: Design, Systems, and Complexity ◽

10.1115/imece2020-24457 ◽

2020 ◽

Author(s):

Mihir Sunil Gawand ◽

H. Onan Demirel

Keyword(s):

High Risk ◽

Data Collection ◽

Human Subject ◽

Work Conditions ◽

Design Framework ◽

Digital Human Modeling ◽

Early Design ◽

Human Modeling ◽

Digital Human ◽

Sample Set

Abstract Digital Human Modeling (DHM) brings in the advantages of reducing the time and cost spent on building physical prototypes and minimizing the risk of conducting human-subject data collection in hazardous settings. However, most of the DHM studies focus on evaluating standardized tasks executed in normal or nominal work conditions. There is a limited existing DHM research that focuses on the analysis of high-risk tasks performed during emergencies. This paper introduces a DHM based design framework that focuses on the ergonomics evaluation of high-risk tasks that are required to be performed during an emergency. The research aims to provide a methodology that can be used to measure the effect on the visibility of the controls due to a fire or smoke emergency in a civilian aircraft cockpit. The design framework described in this paper also automates the repetitive task simulations and ergonomic evaluations, which are typically performed manually by the designer. Thus, the automation module saves time and allows the consideration of a large sample set of anthropometries for assessing ergonomic adequacies. The automation framework also brings in the advantage of making the emergency assessments part of the early design ergonomics analysis digitally, which has not been the focus of traditional ergonomics studies.

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