PFDA-FMEA, an Integrated Method Improving FMEA Assessment in Product Design

Aguirre, Pedro Ángel García; Pérez-Domínguez, Luis; Luviano-Cruz, David; Noriega, Jesús Jaime Solano; Gómez, Erwin Martínez; Callejas-Cuervo, Mauro

doi:10.3390/app11041406

Cited by 17 publications

(6 citation statements)

References 64 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The basic concept of PFS, which are also used in the case study, is presented through the following definitions (Yager, 2013;Cao et al, 2013;García-Aguirre et al, 2021b).…”

Section: Methodsmentioning

confidence: 99%

Risk Assessment Using the PFDA-FMEA Integrated Method

Cicka

Turisová

Čičková³

2022

QIP Journal

View full text Add to dashboard Cite

Purpose: The paper aims to introduce risk assessment in new product development as an important activity for a successful new product launch. A practical example is presented to demonstrate the integration of tools Failure Mode and Effect Analysis (FMEA) and Pythagorean Fuzzy Dimensional Analysis (PFDA) at new product development process, which is a machined component. Methodology/Approach: Individual steps for creating a case study were carried out: create a Subject Matter Expert (SME) team, identify product failure modes, use linguistic values to assess the FMEA, compute and obtain the PFDA-FMEA and determine the product failure modes ranking. Findings: Minimized uncertainty in the final evaluation of the FMEA and improvement in the decision-making process based on the risks already identified in the new product development process. Research Limitation/Implication: The PFDA-FMEA method was based on the risk assessment of a machined part development process. Nevertheless, this method can be used for application in many other areas of industry that require high precision in risk analysis. Originality/Value of paper: The aim of this paper is to reveal a new integrated method in which FMEA, Pythagorean Fuzzy Sets (PFS) and Dimensional Analysis (DA) are coherent in one model.

show abstract

“…The basic concept of PFS, which are also used in the case study, is presented through the following definitions (Yager, 2013;Cao et al, 2013;García-Aguirre et al, 2021b).…”

Section: Methodsmentioning

confidence: 99%

Risk Assessment Using the PFDA-FMEA Integrated Method

Cicka

Turisová

Čičková³

2022

QIP Journal

View full text Add to dashboard Cite

show abstract

“…FMEA is a simple method that especially low-education employees can participate in and understand the process. It is a method widely used in various sectors such as automotive, manufacturing, food, chemistry, and product design [74,[76][77][78][79][80].…”

Section: Failure Mode and Effect Analysis (Fmea)mentioning

confidence: 99%

Risk Analysis in the Food Cold Chain Using Decomposed Fuzzy Set-Based FMEA Approach

Arslan,

Karakurt,

Cem

et al. 2023

Sustainability

View full text Add to dashboard Cite

Risk analysis is employed across various domains, including the increasingly vital food supply chain, particularly highlighted by the COVID-19 pandemic. This study focuses on applying decomposed fuzzy sets (DFS), a novel extension of intuitionistic fuzzy sets, within the context of the food cold chain. The objective is to develop “Decomposed Fuzzy Set-Based FMEA (DF FMEA)” by extending the well-known failure mode and effect analysis (FMEA) method to DFS, to assess risks in the food cold chain. The functional and dysfunctional questions related to the severity, occurrence, and detectability of the identified risks; they were addressed to three experts working on the food cold chain. The purpose is to prevent an inconsistent assignment considering the uncertainty and indecision of decision makers. Due to the implementation of the DF FMEA, the identified risks were prioritized as follows: “Financial Risks” held the highest priority, followed by “Delivery Risks”, “Technological Ability Risks”, “Environmental Risks”, “Quality Risks”, and “Social Risks” with the lowest priority. The study’s practical impact lies in the innovative risk assessment method. By considering decision makers’ preferences and uncertainties, the DF FMEA approach enhances informed decision making. This contributes to a robust framework for addressing risks in the food cold chain, aiding practitioners in more effective risk management.

show abstract

“…Although the methods of concept design evaluation have been continuously optimized, the evaluation criteria used in these studies are still mainly based on traditional survey methods such as expert opinion 34 , 36 , 44 , literature review 4 , 34 , 37 , 41 and questionnaires 18 , 35 , which are feasible but have obvious drawbacks such as time-consuming, slow feedback, low user involvement, and small research These methods are feasible but have obvious drawbacks, such as time-consuming, slow feedback, low user participation, and small scope. A prerequisite for effective methods to obtain accurate and objective product concept evaluation results is the establishment of comprehensive and objective evaluation criteria.…”

Section: Literature Reviewmentioning

confidence: 99%

Evaluation of product conceptual design based on Pythagorean fuzzy set under big data environment

Wang

Xie

et al. 2022

Sci Rep

View full text Add to dashboard Cite

The concept design evaluation phase of the new product launch is extremely important. However, current evaluation information relies mainly on the a priori knowledge of decision makers and is subjective and ambiguous. For this reason, a conceptual design solution decision model based on Pythagorean fuzzy sets in a big data environment is proposed. Firstly, we use the ability of big data to mine and analyze information to construct a new standard for product concept design evaluation in the big data environment. Secondly, the Pythagorean fuzzy set (PFS), Analytic Hierarchy Process (AHP), and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) are integrated into a decision model. AHP, extended by the Pythagorean fuzzy set, is used to determine the weights of new conceptual design criteria in a big data environment. The Pythagorean fuzzy TOPSIS is used to prioritize alternative conceptual design solutions. The feasibility of the approach is proven with a practical case, the generalizability of the method is confirmed with two descriptive digital cases, and the reliability, validity, and superiority of the process are demonstrated with sensitivity analysis, comparative analysis, and computational complexity analysis.

show abstract

PFDA-FMEA, an Integrated Method Improving FMEA Assessment in Product Design

Cited by 17 publications

References 64 publications

Risk Assessment Using the PFDA-FMEA Integrated Method

Risk Assessment Using the PFDA-FMEA Integrated Method

Risk Analysis in the Food Cold Chain Using Decomposed Fuzzy Set-Based FMEA Approach

Evaluation of product conceptual design based on Pythagorean fuzzy set under big data environment

Contact Info

Product

Resources

About