AI-driven FMEA: integration of large language models for faster and more accurate risk analysis

Design Science, Journal Year: 2025, Volume and Issue: 11

Published: Jan. 1, 2025

Abstract Failure mode and effects analysis (FMEA) is a critical but labor-intensive process in product development that aims to identify mitigate potential failure modes ensure quality reliability. In this paper, novel framework improve the FMEA by integrating generative artificial intelligence (AI), particular large language models (LLMs), presented. By using these advanced AI tools, we aim streamline collaborative work FMEA, reduce manual effort accuracy of risk assessments. The proposed includes LLMs support data collection, pre-processing, identification, decision-making FMEA. This integration enables more efficient reliable leverages strengths human expertise capabilities. To validate framework, conducted case study where first used GPT-3.5 as proof concept, followed comparison performance three well-known LLMs: GPT-4, GPT-4o Gemini. These comparisons show significant improvements terms speed, accuracy, reliability results compared traditional methods. Our emphasize transformative processes contribute robust design assurance practices. paper concludes with recommendations for future research focusing on security domain-specific LLM training protocols.

Language: Английский

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Addressing Uncertainty in Digital Risk Evaluation Using a Fuzzy-FMEA Methodology

Published: May 13, 2025

Alongside with the four past revolutions that crowned industrial field, and innovative technologies grows digitalization trend, manufacturing systems are becoming more complex especially in automotive industry. Even though this evolution plays an important role enhancing companies’ performance, they also present many risks to manage, which leads stakeholders need of implementing a strong strategy assess such as Failure Modes Effects Analysis (FMEA). Nowadays, flows confronts different types variables continuously dynamically interacting (social, environmental, financial, political, educational, cultural, etc.), leading uncertainty decision-making approach, specifically during ranking failure severity. Accordingly, article explores how latest version FMEA (AIAG/VDA) approach can be strengthened through Fuzzy-logic overcome judgments. It presents use case based on RFID system implemented within company.

Language: Английский

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Integrating large language models for improved failure mode and effects analysis (FMEA): a framework and case study

Proceedings of the Design Society, Journal Year: 2024, Volume and Issue: 4, P. 2019 - 2028

Published: May 1, 2024

Abstract The manual execution of failure mode and effects analysis (FMEA) is time-consuming error-prone. This article presents an approach in which large language models (LLMs) are integrated into FMEA. LLMs improve accelerate FMEA with human the loop. discussion looks at software tools for emphasizes that must be tailored to needs company. Our framework combines data collection, pre-processing reliability assessment automate A case study validates this demonstrates its efficiency accuracy compared

Language: Английский

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Data-driven machinery faults detection techniques using Artificial Intelligence in Industry 4.0 concept

Procedia Computer Science, Journal Year: 2025, Volume and Issue: 257, P. 404 - 411

Published: Jan. 1, 2025

Language: Английский

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Encouraging Safety 4.0 to enhance industrial culture: An extensive study of its technologies, roles, and challenges

Green Technologies and Sustainability, Journal Year: 2024, Volume and Issue: unknown, P. 100158 - 100158

Published: Dec. 1, 2024

Language: Английский

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Improving Analysis of Risk-Based Maintenance Management Strategies Through Reliability Centered Maintenance. Case Study : Coal Crushing Plant. Central Kalimantan. Indonesia

Advance Sustainable Science Engineering and Technology, Journal Year: 2023, Volume and Issue: 6(1), P. 0240109 - 0240109

Published: Dec. 21, 2023

PT XYZ as a company operating in the coal mining sector has 7 production lines on in-loading system its crushing plant. In-loading line no. is that lowest mechanical availability, therefore it necessary to search for systematic method obtain an appropriate maintenance mode and not only consider operational aspects but also pay attention occupational health & safety aspects. RCM qualitative analysis (which can be developed into quantitative analysis) which formulates task selection based safety, environmental considerations. From results of FMEA research, was found there were 28 failure modes with 6 components had unacceptable risk level critical "very critical" so LTA carried out these obtained tasks each component, namely scheduled condition (HPU pump, Drag Chain, Hydraulic Pipe) redesign (Flight bar, Flap Plate).

Language: Английский

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Assessing the impact of quality improvement on production defectiveness: a case study on an automotive manufacturing industry

Cogent Engineering, Journal Year: 2024, Volume and Issue: 11(1)

Published: Aug. 18, 2024

Overall Equipment Efficiency (OEE) is a crucial performance metric for manufacturing production efficiency. Since the automotive industry vital to economy, growing demand from customers and competition has further increased need optimised through an OEE. The study evaluates volume target affected by quality defects, encompassing calculations of First Time Capability (FTC), assesses relationship between implementation control tools contribution losses on OEE in paint shop plants. applies mixed method, evaluating various defects at paint-shop section automobile applying both qualitative quantitative identifying nonconformities. was assessed using visual inspection thickness measurement range 4–7 mils gauge data tools. A correlational research design adopted techniques determine correlation output knowledge focus group charge producing inspecting painting output. results indicated that does not meet targets due defects. also showed approximately 78% shop-floor workers were deficient significance productivity. In comparison, system current 88.7%. identified missing strategies non-compliance with relevant ISO-8504 standards.

Language: Английский

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A Two-Stage Risk Assessment Method in Aviation Sector

International Journal of Advances in Engineering and Pure Sciences, Journal Year: 2023, Volume and Issue: 35(4), P. 460 - 484

Published: Dec. 29, 2023

Globalleşen dünyada havacılık sektörü en önemli ulaştırma alanlarından biri olup, iyileştirilip geliştirilmesi için pek çok çalışma yapılmaktadır. Havaalanları yolcu trafiğinin ve yük taşımacılığının sıkı takip edildiği, ufak bir aksaklığın sektöre maliyetinin ciddi seviyede olacağı stratejik bölgelerdir. Bu çalışmada havaalanlarında meydana gelen hata risk türleri belirlenerek önleyici bakım planlama faaliyetlerinin amaçlanmaktadır. açıdan türü etkileri analizi (HTEA) yaklaşımı kullanarak havalimanı yetkilileri ile görüşülerek alınan bilgiler doğrultusunda öncelik sayısı (RÖS) ölçeği belirlenmiştir. Buna göre ilgili türlerinin önlenmesi faaliyetler sıralanmıştır. Ayrıca HTEA yönteminin eksikliğini gidermek objektif yöntem olan Entropi yaklaşımına dayanan karar verme yöntemi ağırlıklandırarak sınıflandırılmıştır. hava alanlarında ortaya çıkan tehlike durumları iki aşamalı analitik yaklaşımla boyutlu değerlendirilmektedir. Elde edilen sonuçların, alanı yöneticilerinin öncelikle yapması gereken iyileştirme yatırım kararları hakkında yol gösterici olması beklenmektedir.

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