Aggregation of Risk Management and Non-Parametric Models to Rank Failure Modes of Radio Frequency Identification Systems
The failure mode causes and effects analysis (FMCEA) is a commonly used reliability approach. It identifies, predicts, and analyzes potential failure modes affecting the proper function of equipment or the process under study, along with their roots and consequences. FMCEA aims to evaluate and asses...
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| Format: | Article |
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MDPI AG
2024-01-01
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| Series: | Applied Sciences |
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| Online Access: | https://www.mdpi.com/2076-3417/14/2/584 |
| _version_ | 1797340173999013888 |
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| author | Khaoula Chnina Sahand Daneshvar |
| author_facet | Khaoula Chnina Sahand Daneshvar |
| author_sort | Khaoula Chnina |
| collection | DOAJ |
| description | The failure mode causes and effects analysis (FMCEA) is a commonly used reliability approach. It identifies, predicts, and analyzes potential failure modes affecting the proper function of equipment or the process under study, along with their roots and consequences. FMCEA aims to evaluate and assess the risks resulting from their occurrence, intending to suggest corresponding repair, adjustment, and precautionary measures to be planned during the conception, instruction, or implementation stages. However, the FMCEA has been criticized in the literature for its many inherent shortcomings related to risk assessment and prioritization. Therefore, this study presents an enhanced FMCEA method to address the deficiencies of the traditional risk priority number (RPN) and improve the reliability of risk assessments and corrective actions. A data envelopment analysis (DEA), as a non-parametric method, is used to evaluate the efficiency of these failures by considering their fixing time and cost and deciding on their final priority ranks. Sub-failure modes and their interrelationships are also taken into account. The radio frequency identification (RFID) system was chosen as an example due to its core role in Industry 4.0 and the Internet of Things (IoT) to demonstrate the effectiveness and usefulness of the proposed method. A total of 67 failures related to both hardware and software parts, including the environmental impacts of this technology, have been disclosed. The results of the conventional and the suggested FMCEA methods are found to be considerably different, with ten failure modes classified as being the most efficient. |
| first_indexed | 2024-03-08T09:59:13Z |
| format | Article |
| id | doaj.art-cf05a23237f84e27bdd27a76b6de283f |
| institution | Directory Open Access Journal |
| issn | 2076-3417 |
| language | English |
| last_indexed | 2024-03-08T09:59:13Z |
| publishDate | 2024-01-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj.art-cf05a23237f84e27bdd27a76b6de283f2024-01-29T13:42:55ZengMDPI AGApplied Sciences2076-34172024-01-0114258410.3390/app14020584Aggregation of Risk Management and Non-Parametric Models to Rank Failure Modes of Radio Frequency Identification SystemsKhaoula Chnina0Sahand Daneshvar1Department of Industrial Engineering, Eastern Mediterranean University, Turkish Republic of Northern Cyprus (TRNC), Via Mersin 10, Gazimagusa 99628, TurkeyDepartment of Industrial Engineering, Eastern Mediterranean University, Turkish Republic of Northern Cyprus (TRNC), Via Mersin 10, Gazimagusa 99628, TurkeyThe failure mode causes and effects analysis (FMCEA) is a commonly used reliability approach. It identifies, predicts, and analyzes potential failure modes affecting the proper function of equipment or the process under study, along with their roots and consequences. FMCEA aims to evaluate and assess the risks resulting from their occurrence, intending to suggest corresponding repair, adjustment, and precautionary measures to be planned during the conception, instruction, or implementation stages. However, the FMCEA has been criticized in the literature for its many inherent shortcomings related to risk assessment and prioritization. Therefore, this study presents an enhanced FMCEA method to address the deficiencies of the traditional risk priority number (RPN) and improve the reliability of risk assessments and corrective actions. A data envelopment analysis (DEA), as a non-parametric method, is used to evaluate the efficiency of these failures by considering their fixing time and cost and deciding on their final priority ranks. Sub-failure modes and their interrelationships are also taken into account. The radio frequency identification (RFID) system was chosen as an example due to its core role in Industry 4.0 and the Internet of Things (IoT) to demonstrate the effectiveness and usefulness of the proposed method. A total of 67 failures related to both hardware and software parts, including the environmental impacts of this technology, have been disclosed. The results of the conventional and the suggested FMCEA methods are found to be considerably different, with ten failure modes classified as being the most efficient.https://www.mdpi.com/2076-3417/14/2/584risk managementdata envelopment analysis (DEA)RFID systemFMEA enhancementfailure mode and effects analysis (FMEA)risk priority number (RPN) |
| spellingShingle | Khaoula Chnina Sahand Daneshvar Aggregation of Risk Management and Non-Parametric Models to Rank Failure Modes of Radio Frequency Identification Systems Applied Sciences risk management data envelopment analysis (DEA) RFID system FMEA enhancement failure mode and effects analysis (FMEA) risk priority number (RPN) |
| title | Aggregation of Risk Management and Non-Parametric Models to Rank Failure Modes of Radio Frequency Identification Systems |
| title_full | Aggregation of Risk Management and Non-Parametric Models to Rank Failure Modes of Radio Frequency Identification Systems |
| title_fullStr | Aggregation of Risk Management and Non-Parametric Models to Rank Failure Modes of Radio Frequency Identification Systems |
| title_full_unstemmed | Aggregation of Risk Management and Non-Parametric Models to Rank Failure Modes of Radio Frequency Identification Systems |
| title_short | Aggregation of Risk Management and Non-Parametric Models to Rank Failure Modes of Radio Frequency Identification Systems |
| title_sort | aggregation of risk management and non parametric models to rank failure modes of radio frequency identification systems |
| topic | risk management data envelopment analysis (DEA) RFID system FMEA enhancement failure mode and effects analysis (FMEA) risk priority number (RPN) |
| url | https://www.mdpi.com/2076-3417/14/2/584 |
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