Intuitionistic fuzzy-based model for failure detection.
Daniel O Aikhuele1, Faiz B M Turan1
1Faculty of Manufacturing Engineering, Universiti Malaysia Pahang, 26600 Pekan, Malaysia.
Springerplus
|December 10, 2016
Summary
Customer requirements often miss product reliability needs. This study introduces an intuitionistic fuzzy multi-criteria decision-making method to improve product design by analyzing failure data for better reliability and quality.
Area of Science:
- Engineering
- Decision Sciences
Background:
- Customer requirements, often gathered via Quality Function Deployment (QFD), may not adequately address product reliability.
- Misinterpretations and gaps in customer feedback can lead to suboptimal product redesigns.
- Analyzing existing product failure data is crucial for enhancing reliability and quality in new designs.
Purpose of the Study:
- To propose a novel intuitionistic fuzzy multi-criteria decision-making method for product redesign.
- To enhance product reliability and quality by integrating failure analysis into the design process.
- To provide a robust framework for converting failure information into actionable design knowledge.
Main Methods:
- Development of a new intuitionistic fuzzy multi-criteria decision-making approach.
- Application of an intuitionistic fuzzy TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) model.
- Utilizing an exponential-related function to compute separation measures from intuitionistic fuzzy positive and negative ideal solutions (IFPIS and IFNIS).
Main Results:
- The proposed method was successfully applied to two practical case studies.
- The results demonstrated the effectiveness of the new approach in product redesign scenarios.
- Performance was compared favorably against existing computational methods in the literature.
Conclusions:
- The proposed intuitionistic fuzzy multi-criteria decision-making method offers a valuable tool for improving product reliability and quality.
- Integrating failure data analysis through this method enhances the design knowledge available to engineers.
- The approach provides a systematic way to address limitations of traditional customer requirement gathering for reliability.
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