Quality-Reliability-Risk-Safety Paradigm—Analyzing Fatigue Failure of Aeronautical Components in Light of System Safety Principles

Thomas, Johney; Davis, Antonio; Samuel, Mathews P.

doi:10.1007/978-981-15-4779-9_18

Cited by 5 publications

(6 citation statements)

References 25 publications

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“…The FRAMED-IN-FRAM ® diagram is an improved version of the functional resonance analysis method (FRAM) diagram [32], developed by the authors. Interested readers are referred to Thomas, et al [1,2] for further information on the FRAMED-IN-FRAM ® diagram. The FRAMED-IN-FRAM ® diagram for the SRK framework, presented in Figure 6, shows how the behaviour and control, based on the three levels of skill, rule and knowledge, works through signals, signs and symbols of perceptual, conceptual and explicit nature respectively.…”

Section: Skill-rule-knowledge Framework and Macro-meso-micro Perspective Levelsmentioning

confidence: 99%

“…The erroneous reading by the faulty AoA sensor threw up multiple and confusing signals to the aircrew in the cockpit, and the pilots were not trained to handle such an automation surprise. This vicious cycle of the automatic 'AND' by the MCAS and the manual 'ANU' by the pilot continued many times, and finally the pilot had to give up the control to the MCAS automation under duress, causing the aircraft to plunge downwards and crash in both the disaster cases, as shown in the "FRAMED-IN-FRAM ® diagram" (Thomas et al [1,2]), given in Figure 11.…”

Section: The Intent-execution-manifestation Continuum Of the Axis Of Perception In A Typical Case Studymentioning

confidence: 99%

“…This vicious cycle of the automatic 'AND' by the MCAS and the manual 'ANU' by the pilot continued many times, and finally the pilot had to give up the control to the MCAS automation under duress, causing the aircraft to plunge downwards and crash in both the disaster cases, as shown in the "FRAMED-IN-FRAM ® diagram" (Thomas et al [1,2]), given in Figure 11. The case study shows the disconnect between the 'intent' of the designers, the 'execution' by the MCAS and the pilot, and finally the 'manifestation' of the disasters due to the disconnect.…”

Section: The Intent-execution-manifestation Continuum Of the Axis Of Perception In A Typical Case Studymentioning

confidence: 99%

“…The concepts of quality, reliability, risk and safety are correlated, as shown in the FRAMED-IN-FRAM ® diagram of quality-reliability-risk-safety paradigm (Thomas et al [2]) in Figure 14.…”

Section: The Quality-reliability-risk-safety Paradigmmentioning

confidence: 99%

“…Strategic quality management and system safety principles represent the latest developments in the fields of quality and safety, respectively. Quality and safety are linked through the quality-reliability-risk-safety paradigm presented in an earlier section [2], and strategic quality management has risk-based thinking as one of the cornerstones [39]. Hence application of strategic quality management and integration-in-totality principle together in the systems thinking framework can help understand aerospace systems like aircraft, aero engines, etc.…”

Section: Integration-in-totality Principle and Strategic Quality Managementmentioning

confidence: 99%

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Integration-In-Totality: The 7th System Safety Principle Based on Systems Thinking in Aerospace Safety

2020

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Safety is of paramount concern in aerospace and aviation. Safety has evolved over the years, from the technical era to the human-factors era and organizational era, and finally to the present era of systems-thinking. Building upon three foundational concepts of systems-thinking, a new safety concept called “integration-in-totality principle” is propounded in this article as part of a “seven-principles-framework of system safety”, to act as an integrated framework to visualize and model system safety. The integration-in-totality principle concept addresses the need to have a holistic ‘vertical and horizontal integration’, which is a key tenet of systems thinking. The integration-in-totality principle is illustrated and elucidated with the help of a simple “Rubik’s cube model of integration-in-totality principle” with three orthogonal axes, the ‘axis of perspective’ of vertical integration, and the two ‘axes of perception and performance’ of horizontal integration. Safety analysis along the three axes with a ‘bidirectional synthesis’ and ‘continuum approach’ is further elaborated with relevant case studies, one among them related to the Boeing 737 MAX aircraft twin disasters. Safety is directly linked to quality, reliability and risk, through a self-reinforcing reflexive paradigm, and airworthiness assurance is the process through which safety concepts are embedded in a multidisciplinary aviation environment where the system of systems is seamlessly operating. The article explains how the system safety principle of integration-in-totality is related to reliability and airworthiness of an aerospace system with the help of the ‘V-model of systems engineering’. The article also establishes the linkage between integration-in-totality principle and strategic quality management, thus bridging the gap between two parallel fields of knowledge.

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Section: Skill-rule-knowledge Framework and Macro-meso-micro Perspective Levelsmentioning

confidence: 99%

Section: The Intent-execution-manifestation Continuum Of the Axis Of Perception In A Typical Case Studymentioning

confidence: 99%

Section: The Intent-execution-manifestation Continuum Of the Axis Of Perception In A Typical Case Studymentioning

confidence: 99%

Section: The Quality-reliability-risk-safety Paradigmmentioning

confidence: 99%

Section: Integration-in-totality Principle and Strategic Quality Managementmentioning

confidence: 99%

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Integration-In-Totality: The 7th System Safety Principle Based on Systems Thinking in Aerospace Safety

2020

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Semantic Representation of Low‐Cycle‐Fatigue Testing Data Using a Fatigue Test Ontology and ckan.kupferdigital Data Management System

Nasrabadi,

Hanke,

Skrotzki

2024

Adv Eng Mater

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Addressing a strategy for publishing open and digital research data, this article presents the approach for streamlining and automating the process of storage and conversion of research data to those of semantically queryable data on the web. As the use case for demonstrating and evaluating the digitalization process, the primary datasets from low‐cycle‐fatigue testing of several copper alloys are prepared. The fatigue test ontology (FTO) and ckan.kupferdigital data management system are developed as two main prerequisites of the data digitalization process. FTO has been modeled according to the content of the fatigue testing standard and by reusing the basic formal ontology, industrial ontology foundry core ontology, and material science and engineering ontology. The ckan.kupferdigital data management system is also constructed in such a way that enables the users to prepare the protocols for mapping the datasets into the knowledge graph and automatically convert all the primary datasets to those machine‐readable data which are represented by the web ontology language. The retrievability of the converted digital data is also evaluated by querying the example competency questions, confirming that ckan.kupferdigital enables publishing open data that can be highly reused in the semantic web.

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Exploring the Role of Explainable AI in the Development and Qualification of Aircraft Quality Assurance Processes: A Case Study

Milcke,

Dinglinger,

Holtmann

2024

Communications in Computer and Information Science

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Quality-Reliability-Risk-Safety Paradigm—Analyzing Fatigue Failure of Aeronautical Components in Light of System Safety Principles

Cited by 5 publications

References 25 publications

Integration-In-Totality: The 7th System Safety Principle Based on Systems Thinking in Aerospace Safety

Integration-In-Totality: The 7th System Safety Principle Based on Systems Thinking in Aerospace Safety

Semantic Representation of Low‐Cycle‐Fatigue Testing Data Using a Fatigue Test Ontology and ckan.kupferdigital Data Management System

Exploring the Role of Explainable AI in the Development and Qualification of Aircraft Quality Assurance Processes: A Case Study

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