Identification of Human–System Interaction Errors During Early Design Stages Using a Functional Basis Framework

2019 ◽  
Vol 6 (1) ◽  
Author(s):  
Nicolás F. Soria Zurita ◽  
Robert B. Stone ◽  
H. Onan Demirel ◽  
Irem Y. Tumer
Keyword(s):  
Design Process ◽  
Human Error ◽  
Failure Modes ◽  
Composite Function ◽  
Human System ◽  
Early Design ◽  
Functional Basis ◽  
Potential Failure ◽  
Early Design Stages ◽  
Criticality Analysis

Abstract Engineers have developed different design methodologies capable of identifying failure modes of engineering systems. The most common methods used in industry are failure modes and effects analysis, and failure modes effects and criticality analysis. Nevertheless, such methodologies have a significant limitation regarding incorporating the final user in the analysis and are not suited to identifying potential failure modes caused by physical human–system interactions. Engineering methods usually have a lack of sufficient attention to human–system interactions during the early design stages, even though introducing human factors principles is recognized as an essential analysis during the design process. As a result, designers rely on developing detailed and expensive physical or virtual prototypes to evaluate physical human–system interactions and identify potential failure modes caused by such interactions incorporating design modifications after a prototype is developed can be time-consuming, costly, and if significant changes are needed, the entire prototype requires to be constructed again. Identifying system–user interactions and possible failure modes associated with such interactions before developing a prototype can significantly improve the design process. In previous work, the authors introduced the function–human error design method (FHEDM), a tool capable of distinguishing possible human–system interaction failure modes using a functional basis framework. In this work, we examined the implementation of FHEDM within 148 products extracted from the design repository. The results are grouped in the composite function–user interaction error (FUIE) matrix, which can be used as a preliminary design database presenting information regarding the possible human error present in function-flow combinations.

An Association Rule Approach for Identifying Physical System-User Interactions and Potential Human Errors Using a Design Repository

2019 ◽  
Author(s):  
Nicolás F. Soria Zurita ◽  
Melissa Anne Tensa ◽  
Vincenzo Ferrero ◽  
Robert B. Stone ◽  
Bryony DuPont ◽  
...  
Keyword(s):  
Data Mining ◽  
Design Process ◽  
Human Error ◽  
Failure Modes ◽  
Functional Model ◽  
Design Stage ◽  
User Interactions ◽  
Early Design ◽  
Design Information ◽  
Rule Approach

Abstract During the design process, designers must satisfy customer needs while adequately developing engineering objectives. Among these engineering objectives, human considerations such as user interactions, safety, and comfort are indispensable during the design process. Nevertheless, traditional design engineering methodologies have significant limitations incorporating and understanding physical user interactions during early design phases. For example, Human Factors methods use checklists and guidelines applied to virtual or physical prototypes at later design stages to evaluate the concept. As a result, designers struggle to identify design deficiencies and potential failure modes caused by user-system interactions without relying on the use of detailed and costly prototypes. The Function-Human Error Design Method (FHEDM) is a novel approach to assess physical interactions during the early design stage using a functional basis approach. By applying FHEDM, designers can identify user interactions required to complete the functions of the system and to distinguish failure modes associated with such interactions, by establishing user-system associations using the information of the functional model. In this paper, we explore the use of data mining techniques to develop relationships between component, functions, flows and user interactions. We extract design information about components, functions, flows, and user interactions from a set of distinct coffee makers found in the Design Repository to build associations rules. Later, using a functional model of an electric kettle, we compared the functions, flows, and user interactions associations generated from data mining against the associations created by the authors, using the FHEDM. The results show notable similarities between the associations built from data mining and the FHEDM. We are suggesting that design information from a rich dataset can be used to extract association rules between functions, flows, components, and user interactions. This work will contribute to the design community by automating the identification of user interactions from a functional model.

Identification of Human Errors During Early Design Stage Functional Failure Analysis

2018 ◽  
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.

Computational Functional Failure Analysis to Identify Human Errors During Early Design Stages

2019 ◽  
Vol 19 (3) ◽  
Author(s):  
Lukman Irshad ◽  
Salman Ahmed ◽  
H. Onan Demirel ◽  
Irem Y. Tumer
Keyword(s):  
Failure Analysis ◽  
Human Error ◽  
Human Action ◽  
System Level ◽  
Design Stage ◽  
Human Factors Engineering ◽  
Human Errors ◽  
Functional Failure ◽  
Early Design ◽  
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 functional failure identification and propagation (FFIP), 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 toward 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. The capabilities of the proposed method is presented via 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.

Improving reliability in critical healthcare sector using FAMECA methodology

BMJ Leader ◽  
2017 ◽  
Vol 1 (4) ◽  
pp. 50-56
Author(s):  
Polinpapilinho Freeman Katina ◽  
Nina C Magpili-Smith
Keyword(s):  
Failure Modes ◽  
Methodological Approach ◽  
Well Being ◽  
Healthcare Systems ◽  
Healthcare Sector ◽  
Critical Infrastructures ◽  
Goods And Services ◽  
Mode Effects ◽  
Potential Failure ◽  
Criticality Analysis

BackgroundHealthcare systems are critical to the well-being of the society. In such a setting, the ability of the system to perform its intended mission/function during the designed period of time (ie, reliability) is essential. However, there remains a scarcity of literature, suggesting how the concept of reliability can be addressed in the context of critical healthcare infrastructure systems.MethodsWe recognise the importance of healthcare in the context of critical infrastructures. These systems produce goods and services essential for maintaining and sustaining public well-being. We suggest the use of failure mode, effects and criticality analysis (FAMECA) approach to increase reliability in critical healthcare systems. Phases of FAMECA are described.ResultsAfter reviewing the application of FAMECA and describing its basics, authors describe critical healthcare sector in terms of components, organisations, management and non-healthcare interdependent systems. The resulting application indicates applicability of the approach and articulates failure modes, effects and development of possible solutions to such modes and effects to increase reliability. The presented application, however, is very general and specific case applications are needed.ConclusionsA decision to suggest the FAMECA as a methodological approach in critical healthcare systems is pivotal to improving systems reliability and enhances the ability of the system to meet its intended missions during the designed period of time. The utility of FAMECA is found in its ability to identify potential failure modes, their effects and suggesting remedial efforts, including tools and technologies to address failure modes and their effects.

scholarly journals A Case Study on Improving Intensive Care Unit (ICU) Services Reliability: By Using Process Failure Mode and Effects Analysis (PFMEA)

2016 ◽  
Vol 8 (9) ◽  
pp. 207 ◽  
Author(s):  
Taraneh Yousefinezhadi ◽  
Farnaz Attar Jannesar Nobari ◽  
Faranak Behzadi Goodari ◽  
Mohammad Arab
Keyword(s):  
Intensive Care ◽  
Human Error ◽  
Failure Modes ◽  
Classification Model ◽  
Group Discussions ◽  
Team Members ◽  
Acceptable Risks ◽  
Process Failure ◽  
Potential Failure ◽  
Fmea Method

<p><strong>INTRODUCTION:</strong> In any complex human system, human error is inevitable and shows that can’t be eliminated by blaming wrong doers. So with the aim of improving Intensive Care Units (ICU) reliability in hospitals, this research tries to identify and analyze ICU’s process failure modes at the point of systematic approach to errors.</p><p><strong>METHODS:</strong> In this descriptive research, data was gathered qualitatively by observations, document reviews, and Focus Group Discussions (FGDs) with the process owners in two selected ICUs in Tehran in 2014. But, data analysis was quantitative, based on failures’ Risk Priority Number (RPN) at the base of Failure Modes and Effects Analysis (FMEA) method used.<strong> </strong>Besides, some causes of failures were analyzed by qualitative Eindhoven Classification Model (ECM).</p><p><strong>RESULTS:</strong> Through<strong> </strong>FMEA methodology, 378 potential failure modes from 180 ICU activities in hospital A and 184 potential failures from 99 ICU activities in hospital B were identified and evaluated. Then with 90% reliability (RPN≥100), totally 18 failures in hospital A and 42<strong> </strong>ones in hospital B were identified as non-acceptable risks and then their causes were analyzed by ECM.</p><p><strong>CONCLUSIONS</strong>: Applying of modified PFMEA for improving two selected ICUs’ processes reliability in two different kinds of hospitals shows that this method empowers staff to identify, evaluate, prioritize and analyze all potential failure modes and also make them eager to identify their causes, recommend corrective actions and even participate in improving process without feeling blamed by top management. Moreover, by combining FMEA and ECM, team members can easily identify failure causes at the point of health care perspectives.</p>

An Assessment of RPN Prioritization in a Failure Modes Effects and Criticality Analysis

2004 ◽  
Vol 47 (1) ◽  
pp. 51-56 ◽  
Author(s):  
John Bowles
Keyword(s):  
Failure Modes ◽  
Measurement Scale ◽  
Risk Priority Number ◽  
Probability Of Occurrence ◽  
Ordinal Ranking ◽  
Potential Failure ◽  
Different Characteristics ◽  
Criticality Analysis

The Risk Priority Number methodology for prioritizing failure modes is an integral part of the Automobile Failure Modes and Effects Analysis (FMECA) technique. This technique consists of ranking potential failures from 1 to 10 with respect to their severity, probability of occurrence, and likelihood of detection in later tests, and multiplying the numbers. The result is a numerical ranking, called the RPN, on a scale from 1 to 1000. Potential failure modes having higher RPNs are assumed to have a higher design risk than those having lower values. Although this method is well documented and easy to apply, it is seriously flawed from a technical perspective, making the interpretation of the analysis results problematic. Problems with the methodology include: use of ordinal ranking numbers as numeric quantities; lack of continuity in the RPN measurement scale; duplicate RPN values with extremely different characteristics; and varying sensitivity to small changes. Recommendations for an improved methodology are provided.

Information generation during design: Information importance and design effort

2005 ◽  
Vol 19 (1) ◽  
pp. 19-32 ◽  
Author(s):  
A.J. DENTSORAS
Keyword(s):  
Theoretical Analysis ◽  
Design Process ◽  
Quantitative Relationship ◽  
Design Knowledge ◽  
Belt Conveyor ◽  
Early Design ◽  
Design Information ◽  
Early Design Stages ◽  
Information Generation ◽  
The Relationship

The present paper studies the process of information generation during design and focuses on the relationship between the information importance and the required effort for its generation. Multiple associative relationships among design entities (handled as design descriptors) are used to represent the design knowledge. The characteristics of the dependent and the primary descriptors are examined and their distinct roles in the design process are discussed. Term definitions concerning the information importance and the design effort are also introduced. The descriptors are used to form a matrix. A number of operations on this matrix results in its transformation, with the final matrix reflecting the quantitative relationship between the information importance and the design effort. From the aforementioned matrix, a unique sorted list for the primary design descriptors is produced. Following this list during descriptor instantiation ensures the production of design information of maximum importance with the least effort in the early design stages. The design of a belt conveyor is used as a basis for a better understanding of the theoretical analysis and for a demonstration of the use of the suggested descriptor list.

scholarly journals Automated Generation of Fault Scenarios to Assess Potential Human Errors and Functional Failures in Early Design Stages

2020 ◽  
Vol 20 (5) ◽  
Author(s):  
Lukman Irshad ◽  
H. Onan Demirel ◽  
Irem Y. Tumer
Keyword(s):  
Human Error ◽  
Human Action ◽  
Time Step ◽  
Critical Function ◽  
Human Errors ◽  
Early Design ◽  
Complex Engineered Systems ◽  
Early Design Stages ◽  
Engineered Systems ◽  
Improved Performance

Abstract Human errors are attributed to a majority of accidents and malfunctions in complex engineered systems. The human error and functional failure reasoning (HEFFR) framework was 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 for engineers. This research aims overcome this limitation by creating a use case generation technique that covers both component- and human-related fault scenarios. The proposed technique is a time-based simulation that employs a modified depth first search (DFS) to simulate events as the event propagation is analyzed using HEFFR at each time-step. The results show that the proposed approach is capable of generating a wide variety of fault scenarios involving humans and components. Out of the 15.4 million scenarios that were found to violate the critical function, two had purely human-induced faults, 163,204 had purely non-human-induced faults, and the rest had a combination of both. The results also show that the framework was able to uncover hard-to-detect scenarios such as scenarios with human errors that do not propagate to affect the system. In fact, 86% of all human action combinations with nominal human-induced component behaviors had underlying human errors.

scholarly journals OPTIMIZING BREAKWATER DESIGN CONSIDERING THE SYSTEM OF FAILURE MODES

2011 ◽  
Vol 1 (32) ◽  
pp. 37
Author(s):  
Alvaro Campos ◽  
Carmen Castillo ◽  
Rafael Molina
Keyword(s):  
Design Process ◽  
Failure Probability ◽  
Failure Modes ◽  
Optimization Techniques ◽  
Physical Interaction ◽  
Complete Knowledge ◽  
Potential Failure

Optimization techniques have been applied to breakwater design in order to automate the design process (Castillo et al. 2004, 2006). Since safety of structures is the fundamental criterion for design, a complete knowledge of the potential failure modes, as well as the possible interaction between them, is essential to provide a consistent design. Failure modes are correlated in two ways: through common parameters like HS or by physical interaction. The latter has not yet been precisely identified nor quantified. The aim of the present paper is to advance on the analysis of both types of correlations and to check how the combination of failure modes modifies the failure probability of the whole structure either increasing or decreasing it. An application to a special type of composite breakwater is proposed: the fuse parapet case, where part of the parapet fails under certain circumstances in order to ensure the whole stability of the caisson, despite increasing overtopping events.

Integration of Crashworthiness Aspects into Preliminary Aircraft Design

2014 ◽  
Vol 598 ◽  
pp. 146-150 ◽  
Author(s):  
Dominik B. Schwinn
Keyword(s):  
Design Process ◽  
Aircraft Design ◽  
Analysis Tool ◽  
Preliminary Design ◽  
Design Phase ◽  
Crash Analysis ◽  
Early Design ◽  
Preliminary Aircraft Design ◽  
Early Design Stages ◽  
Certification Requirement

Crashworthiness proof is a certification requirement by aviation authorities for new aircraft types. The objective of static design is a sufficiently stiff and strong structure to carry bending and torsion during flight and ground maneuvers. High stiffness, however, is critical for good crashworthiness behavior. Therefore, crashworthiness investigations should be included at early design stages of the overall aircraft design process. This paper introduces the crash analysis tool AC-CRASH and shows an approach of integrating it into the preliminary design phase.

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