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Proceeding Paper

Failure Modes and Effects Analysis for Automotive Trim Parts Processing †

by
Dorin-Ion Dumitrascu
1 and
Adela-Eliza Dumitrascu
2,*
1
Department of Automotive and Transport Engineering, Transilvania University of Brasov, 1 Politehnicii, 500036 Brasov, Romania
2
Department of Manufacturing Engineering, Transilvania University of Brasov, 5 Mihai Viteazul, 500036 Brasov, Romania
*
Author to whom correspondence should be addressed.
Presented at the 1st International Conference on Industrial, Manufacturing, and Process Engineering (ICIMP-2024), Regina, Canada, 27–29 June 2024.
Eng. Proc. 2024, 76(1), 22; https://doi.org/10.3390/engproc2024076022
Published: 18 October 2024

Abstract

:
The paper presents a study related to the implementation of failure modes and effects analysis (FMEA). The analysis consists of the identification, assessment, monitoring, and control of potential failure modes specific to the injection process applied to veneer trim parts. Based on the Ishikawa diagram, potential failure modes, effects, and causes of failure can be determined. The assessment results show that the potential risks are mostly located in the medium and high zones. By implementing corrective action, the process is significantly improved, and the potential risks are located in the low and medium zones. From a qualitative point of view, the Pareto chart allows prioritization of the defects that appear for the analyzed manufacturing process. It can be noted that the first two types of identified defects represent 27% of the total defects.

1. Introduction

Along with statistical methods and tools used to evaluate the quality of products and industrial processes, failure modes and effects analysis (FMEA) can be considered a non-probabilistic method that can increase reliability and operational safety in a very effective way [1].
Failure modes and effects analysis represents a method of product or process improvement in terms of quality and reliability [2,3,4].
  • FMEA is a simple method for systematically revealing the possible failures of a structure or process earlier in the design project stage. The purpose of FMEA is to reveal problems that can result in safety hazards, product malfunctions, or a shortened life. The goal is to avoid or mitigate the potential failure modes in order to prevent their occurrence [1].
  • FMEA is a system reliability analysis technique used in various industries to identify, mitigate, and eliminate failure risks [2,3,4,5,6]. Considering the need to minimize or eliminate risks and meet customer expectations, an integrated quality function deployment (QFD)–FMEA framework could be useful for product and process improvement [3].
  • The detailed FMEA process involves consideration of the main elements of a process, namely, people, materials, equipment, methods, measurements, and environment [1]. These key elements provide valuable information in order to identify and evaluate the failure modes as well as their potential causes and effects [4].
The FMEA method does not have a specific area of use, but it can be applied in the following situations [1,2,3,4,5,6,7]:
  • Analysis of potential failure modes in the case of important safety components;
  • Changes in legislation or technical conditions of the client;
  • Implementation of new technology;
  • Products or processes with problems related to quality and safety in their operation;
  • Launching a new type of product or process;
  • Changes to existing products or processes;
  • Adaptation of products to new conditions of use.
Industrial organizations must direct attention to enhance characteristics related to health, safety, and environment management systems to attain success in their activities. In order to accomplish safety and environment management, the overall goal should be the identification and assessment of potential risks so that they can be controlled. This may increase the protection level of employees and the efficiency of the work environment [4]. These conditions must completely fulfill the legal and other requirements that are imposed.
  • The objective of this study is to analyze the potential failure modes for the injection process of veneer trim parts. For each potential failure mode, the following are evaluated: the severity of potential effects (S), the frequency of the occurrence of potential causes (O), and the potential detection (D). These risk indices are ranked depending on action priority (AP). The purpose of implementing the failure modes and effects analysis is to control and reduce the potential causes of the potential effects and defects specific to the analyzed manufacturing process.

2. Materials and Methods

The analysis consists of FMEA method application in order to assess the potential failure modes of the injection process applied to veneer trim parts processing. The potential failure modes that can be caused by the processing process, technological equipment, devices, and production methods are first identified. The purpose of the evaluation is to determine the potential or existing failures of the process and to rank them. The purpose of the analysis is to implement corrective and preventive actions in order to reduce the risk level of each potential failure mode.
Potential failure modes are quantified and prioritized based on how severe their effects are (S), how frequently they occur (O), and how easily they can be detected (D). Risks are associated with the effects that potential failure modes can generate. The level of scoring is established by an organization according to the importance of the provided products and industrial processes, as well as the technical conditions and quality requirements imposed by the beneficiary.
The main steps of FMEA application for a manufacturing process are detailed in Figure 1 [8]:

3. Results and Discussion

Using the Ishikawa diagram, potential failure modes, potential effects, and potential causes of failure can be determined. Figure 2 shows the quantified potential risks for the analyzed initial stage.
Depending on the assigned risk indices (S, O, and D), the priority actions (AP) of the implementation of corrective actions are established. The prioritization process consists of classifying the risks according to three levels: high (H), medium (M), and low (L).
Considering the initial stage of the analysis of the potential failure modes of the analyzed process, the following risk hierarchy is obtained (Figure 2): three potential risks are located in the low area, eighteen values indicate risks in the medium area, and two risks are considered high. Particular attention should be paid to risks that exceed the acceptable level. In the case of R3 and R4 potential risks, it is necessary to reduce them by decreasing them to an admissible level.
As the majority of risks are situated at the medium level, a qualitative analysis of them is required. By applying the Pareto chart, a prioritization of specific defects can be achieved so that they are minimized/eliminated by corrective actions (Figure 3).
The identified defects refer to injection defects, bubbles, wrinkles on the veneer, cracked veneer, dirt, damaged parts, etc.
As can be observed, the first two types of defects represent a cumulative 27% of the total defects. These refer to parts with improper surfaces and incomplete injections. After applying the corrective actions, the situation is presented synthetically in Figure 4.
After applying the corrective actions, for the optimized stage, 13 risks are recorded in the medium range (M) and 10 risks in the low range (L). Analyzing the optimized stage of the process, a significant improvement of the process is found, with all risks being located in the zone of acceptable risks.
The non-probabilistic application of the FMEA method highlights the fact that failure modes and potential causes can be kept under control, and the analyzed process can be significantly improved.
Studies related to FMEA probabilistic evaluation were carried out by [2,3,7]. The studies elaborated by [2] propose a novel FMEA model for risk assessment that combines minimum cost conflict risk mitigation and probabilistic information. To define the risk assessments in response to uncertainty and fuzziness, probabilistic linguistic term sets were used. The integration of this model into FMEA resulted in difference minimization among individual risk assessments at the minimum adjustment cost [2]. Also, Yifan et al. built an integrated QFD–FMEA framework. To enhance the process performance, the QFD and FMEA methods were improved [3].
Failure modes and effect analysis (FMEA) is one of the most commonly used methods in manufacturing process risk assessment. However, disadvantages of conventional FMEA, such as the use of a risk priority number (RPN) to prioritize risks, make this method inefficient in industries [4,7]. For these reasons, the updated version of the FMEA manual proposes a qualitative assessment in seven steps, centered on the ranking of risks in terms of action priorities [8].

4. Conclusions

  • The implementation of the failure modes and effects analysis can lead to a reduction in non-quality costs, a significant reduction in scraps, customer satisfaction, improvement in product quality and reliability, and fulfillment of legal requirements related to operational safety.
  • The use of failure modes and effects analysis determines and ensures the efficiency and effectiveness of quality management implementation for the processing process.
  • Analyzing the process from a quantitative point of view, 8.7% of defects are high risk, 78.3% medium risk, and 13% low risk. After applying corrective actions, an improvement of the process can be observed: 43.7% are low risk and 56.3% are medium risk. These results of the evaluation analysis highlight a significant improvement in the process.
  • The application of the Pareto analysis allows the identification, evaluation, and ranking of the main potential failure modes, considering the cumulative relative frequency of the potential risks.
The effectiveness of the application of the FMEA method is influenced by the FMEA team. The limitation of the application of the FMEA method is the scoring subjectivity of the severity (S), probability of occurrence (O), and detection (D).

Author Contributions

Conceptualization, D.-I.D. and A.-E.D.; formal analysis, A.-E.D.; investigation, A.-E.D.; methodology, D.-I.D. and A.-E.D.; software, D.-I.D. and A.-E.D.; supervision, A.-E.D.; validation, D.-I.D. and A.-E.D.; writing—original draft, D.-I.D. and A.-E.D.; writing—review and editing, D.-I.D. and A.-E.D. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

Data are contained within the article.

Acknowledgments

The authors are grateful to the Transilvania University of Brasov for technical and financial support.

Conflicts of Interest

The authors declare no conflicts of interest.

References

  1. Menčík, J. Concise Reliability for Engineers, Chapter 12—Failure Modes and Effects Analysis; IntechOpen: London, UK, 2016. [Google Scholar] [CrossRef]
  2. Du, Z.; Yu, S.; Chen, Z. Enhanced minimum-cost conflict risk mitigation-based FMEA for risk assessment in a probabilistic linguistic context. Comput. Ind. Eng. 2022, 174, 108789. [Google Scholar] [CrossRef]
  3. Wu, Y.; Liu, P.; Li, Y. An integrated QFD and FMEA method under the co-opetitional relationship for product upgrading. Inf. Sci. 2024, 667, 120505. [Google Scholar] [CrossRef]
  4. Yousef, S.; Alizadeh, A.; Hayati, J.; Baghery, M. HSE risk prioritization using robust DEA-FMEA approach with undesirable outputs: A study of automotive parts industry in Iran. Saf. Sci. 2018, 102, 144–158. [Google Scholar] [CrossRef]
  5. Bashir, S.; Mohammed, A.; Mujahid, A. Risk prioritization using a modified FMEA analysis in industry 4.0. J. Eng. Res. 2023, 11, 460–468. [Google Scholar] [CrossRef]
  6. Ervural, B.; Ayaz, I.A. A fully data-driven FMEA framework for risk assessment on manufacturing processes using a hybrid approach. Eng. Fail. Anal. 2023, 152, 107525. [Google Scholar] [CrossRef]
  7. Hiluf, R.; Akshay, D. Decision-making on the selection of lean tools using fuzzy QFD and FMEA approach in the manufacturing industry. Expert Syst. Appl. 2022, 192, 116416. [Google Scholar] [CrossRef]
  8. Failure Mode and Effects Analysis. In FMEA Handbook, 1st ed.; AIAG & VDA: Southfield, MI, USA, 2019.
Figure 1. Risk assessment methodology by applying the FMEA process.
Figure 1. Risk assessment methodology by applying the FMEA process.
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Figure 2. Risk classification for the initial stage.
Figure 2. Risk classification for the initial stage.
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Figure 3. Defect analysis.
Figure 3. Defect analysis.
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Figure 4. Risk classification for an optimized process.
Figure 4. Risk classification for an optimized process.
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MDPI and ACS Style

Dumitrascu, D.-I.; Dumitrascu, A.-E. Failure Modes and Effects Analysis for Automotive Trim Parts Processing. Eng. Proc. 2024, 76, 22. https://doi.org/10.3390/engproc2024076022

AMA Style

Dumitrascu D-I, Dumitrascu A-E. Failure Modes and Effects Analysis for Automotive Trim Parts Processing. Engineering Proceedings. 2024; 76(1):22. https://doi.org/10.3390/engproc2024076022

Chicago/Turabian Style

Dumitrascu, Dorin-Ion, and Adela-Eliza Dumitrascu. 2024. "Failure Modes and Effects Analysis for Automotive Trim Parts Processing" Engineering Proceedings 76, no. 1: 22. https://doi.org/10.3390/engproc2024076022

APA Style

Dumitrascu, D. -I., & Dumitrascu, A. -E. (2024). Failure Modes and Effects Analysis for Automotive Trim Parts Processing. Engineering Proceedings, 76(1), 22. https://doi.org/10.3390/engproc2024076022

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