Resilience Engineering for Sustainable Prevention in the Manufacturing Sector: A Comparative Study of Two Methods of Risk Analysis

Melanson, Annick; Nadeau, Sylvie

doi:10.4236/ajibm.2019.91017

Cited by 7 publications

(1 citation statement)

References 25 publications

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“…The need to adopt a Resilience Engineering perspective in system's analysis and look at failure and success as complex emergent events has been addressed and advocated in a wide array of studies [1,4]. Such applications are promising and can provide interesting and helpful results that can complement established methods to better keep up with technological developments and the continuously increasing complexity of sociotechnical systems [54]. However, as is the case with new and innovative methods, the application of such methods from a technology readiness point of view is not without challenges and issues to overcome.…”

Section: Discussionmentioning

confidence: 99%

A Mixed Rough Sets/Fuzzy Logic Approach for Modelling Systemic Performance Variability with FRAM

Slim

Nadeau

2020

Sustainability

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The task to understand systemic functioning and predict the behavior of today’s sociotechnical systems is a major challenge facing researchers due to the nonlinearity, dynamicity, and uncertainty of such systems. Many variables can only be evaluated in terms of qualitative terms due to their vague nature and uncertainty. In the first stage of our project, we proposed the application of the Functional Resonance Analysis Method (FRAM), a recently emerging technique, to evaluate aircraft deicing operations from a systemic perspective. In the second stage, we proposed the integration of fuzzy logic into FRAM to construct a predictive assessment model capable of providing quantified outcomes to present more intersubjective and comprehensible results. The integration process of fuzzy logic was thorough and required significant effort due to the high number of input variables and the consequent large number of rules. In this paper, we aim to further improve the proposed prototype in the second stage by integrating rough sets as a data-mining tool to generate and reduce the size of the rule base and classify outcomes. Rough sets provide a mathematical framework suitable for deriving rules and decisions from uncertain and incomplete data. The mixed rough sets/fuzzy logic model was applied again here to the context of aircraft deicing operations, keeping the same settings as in the second stage to better compare both results. The obtained results were identical to the results of the second stage despite the significant reduction in size of the rule base. However, the presented model here is a simulated one constructed with ideal data sets accounting for all possible combinations of input variables, which resulted in maximum accuracy. The same should be further optimized and examined using real-world data to validate the results.

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Section: Discussionmentioning

confidence: 99%

A Mixed Rough Sets/Fuzzy Logic Approach for Modelling Systemic Performance Variability with FRAM

Slim

Nadeau

2020

Sustainability

Self Cite

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Development and Validation of a Stability‐Indicating High‐Performance Liquid Chromatography Method Coupled With a Diode Array Detector for Quantifying Haloperidol in Oral Solution Using the Analytical Quality‐by‐Design Approach

Junkert,

Mieres,

Domingues

et al. 2024

J of Separation Science

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This study developed a stability‐indicating HPLC‐DAD method for quantifying haloperidol in oral solution using analytical quality‐by‐design principles. Haloperidol stability was tested under acidic, alkaline, oxidative, and photolytic stress conditions. The analytical quality‐by‐design approach began by defining the analytical target profile and identifying critical material attributes and critical method parameters via risk analysis. Factorial and Box–Behnken designs, conducted in Design Expert 13, were used to select critical method parameters and determine the method operable design region. The oral solution degraded significantly under acidic and alkaline conditions. Continuous critical method parameters such as mobile phase flow rate, gradient slope, column temperature, and pH were optimized. A quadratic Box–Behnken design with critical method attributes was applied and validated, resulting in robust regression models with significant p‐values (> 0.05), absence of lack‐of‐fit (p‐values < 0.05), and R2‐adjusted > 0.85. The method proved selective, accurate, and precise within the method operable design range. Normal operating conditions (NOCs) were established using a Waters Symmetry C18 column with a 100‐mM formate buffer (pH 3.8) and acetonitrile, with a gradient profile and detection at 246 nm. The operational region included flow rates between 1.2 and 1.35 mL/min (NOC = 1.3 mL/min), temperatures of 8°C–20°C (NOC = 15°C), and mobile phase pH variations from 3.3 to 4.3 (NOC = 3.8). The analytical quality‐by‐design–based method was robust and effective for stability monitoring, reducing subjectivity while maximizing reliability.

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Qualities of the Alternative Approach of the Functional Resonance Analysis Method and the Analytic Hierarchy Process. Review

Tierra-Arévalo,

del Carmen Pardo-Ferreira,

Herrera-Pérez

et al. 2023

Studies in Systems, Decision and Control

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Resilience Engineering for Sustainable Prevention in the Manufacturing Sector: A Comparative Study of Two Methods of Risk Analysis

Cited by 7 publications

References 25 publications

A Mixed Rough Sets/Fuzzy Logic Approach for Modelling Systemic Performance Variability with FRAM

A Mixed Rough Sets/Fuzzy Logic Approach for Modelling Systemic Performance Variability with FRAM

Development and Validation of a Stability‐Indicating High‐Performance Liquid Chromatography Method Coupled With a Diode Array Detector for Quantifying Haloperidol in Oral Solution Using the Analytical Quality‐by‐Design Approach

Qualities of the Alternative Approach of the Functional Resonance Analysis Method and the Analytic Hierarchy Process. Review

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