Application of neuro-fuzzy scheme to improve purchasing process in a hospital

Fatema, Nuzhat

doi:10.3233/jifs-169797

Cited by 6 publications

(2 citation statements)

References 13 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Bahrebar et al [50] proposed a general type-2 fuzzy inference approach to identify the hazardous conditions of a marine propulsion system. Fatema [51] designed a neurofuzzy scheme-based FMEA to improve the purchasing process in private hospitals. Sang et al [52] developed a genetic algorithm-based fuzzy FMEA model for the risk analysis and assessment of rainfed lowland rice production.…”

Section: Literature Reviewmentioning

confidence: 99%

A Novel Failure Mode and Effect Analysis Approach Integrating Probabilistic Linguistic Term Sets and Fuzzy Petri Nets

Wang

Xiong

et al. 2019

IEEE Access

View full text Add to dashboard Cite

Failure mode and effect analysis (FMEA) is an effective quality management technique widely used in various industries to improve the reliability and safety of systems, products, processes, and services. In traditional FMEA, the ranking of failure modes is carried out by the risk priority number (RPN), which is calculated by the product of severity (S), occurrence (O), and detection (D). Nevertheless, the normal FMEA has many inherent defects in assessing and ranking failure modes. Therefore, in this paper, we present a new FMEA model, which integrates probabilistic linguistic term sets (PLTSs) and fuzzy Petri nets (FPNs) for the risk assessment and prioritization of failure modes. Specifically, the PLTSs are used to capture the uncertainty of FMEA team members' subjective judgments, and the FPNs are established to acquire the risk priority of the identified failure modes. Besides, a technique for order preference by similarity to an ideal solution (TOPSIS)-based weighting method is proposed to determine the objective weight of each team member. Finally, a marine-ship system risk assessment example is provided to illustrate the suggested FMEA and a comparative analysis is conducted to assess its effectiveness and usefulness. The results show that the new FMEA approach can produce more reliable and reasonable risk ranking result of failure modes. INDEX TERMS Failure mode and effect analysis (FMEA), probabilistic linguistic term set (PLTS), TOPSIS method, fuzzy Petri net (FPN). The associate editor coordinating the review of this manuscript and approving it for publication was Zhiwu Li.

show abstract

Section: Literature Reviewmentioning

confidence: 99%

A Novel Failure Mode and Effect Analysis Approach Integrating Probabilistic Linguistic Term Sets and Fuzzy Petri Nets

Wang

Xiong

et al. 2019

IEEE Access

View full text Add to dashboard Cite

show abstract

“…In [23], a SVM based classifier is used for translating magneto-encephalography (MEG) signals to the corresponding wrist movement and the results obtained have been compared to various other techniques employed for the same. In [24], neuro-fuzzy techniques have been employed in conjunction with failure modes and effects analysis (FMEA) to calculate the risk priority numbers (RPN) with the goal of improving the quality of service at hospitals.…”

mentioning

confidence: 99%

Special issue on intelligent tools and techniques for signals, machines and automation

Srivastava

Malik

Sharma

2018

IFS

View full text Add to dashboard Cite

A reliability analysis method for electromagnet performance degradation based on FMEA and fuzzy inference system

Pang,

Dai,

Lian

et al. 2024

Quality & Reliability Eng

View full text Add to dashboard Cite

Electromagnets are often used in indirect control for industrial applications. The ability of an electromagnet to control objects should decrease with performance degradation. And electromagnets product poses a danger to people and objects in the working environment. So, it is very difficult to analyze the reliability of electromagnetic performance degradation because of the complicated working condition. Failure Mode and Effect Analysis (FMEA) is the most commonly used tool for product reliability analysis. The new version of FMEA uses integer as evaluation value, which cannot represent the hesitation psychology of the evaluator. The Action Priority (AP) table of the FMEA describes the relationship between the evaluation of influencing factors and the risk level of the failure mode, which provides rules for determining the risk level of the failure mode. However, the AP table may result in multiple failure modes having the same ranking, which does not align with the intention of FMEA to prevent failures. Therefore, this paper proposes a reliability analysis method for electromagnetic performance degradation based on FMEA and FIS. Firstly, the Double Hierarchy Hesitant Fuzzy Linguistic Term Set (DHHFLTS) is used as the evaluation language to describe the hesitation psychology of evaluators. Secondly, the AP table of FMEA is used as FIS fuzzy inference rule. In this way, the idea of FMEA to determine the risk level of failure mode is retained and the problem of FIS fuzzy rule making is overcome. Then, FIS defuzzification AP table inference results to determine the risk ranking of failure modes. This avoids situations where the order of failure modes is equal. Finally, a performance degradation model of the electromagnet is constructed based on the Wiener process, and the calculation results of the new method are verified.

show abstract

Application of neuro-fuzzy scheme to improve purchasing process in a hospital

Cited by 6 publications

References 13 publications

A Novel Failure Mode and Effect Analysis Approach Integrating Probabilistic Linguistic Term Sets and Fuzzy Petri Nets

A Novel Failure Mode and Effect Analysis Approach Integrating Probabilistic Linguistic Term Sets and Fuzzy Petri Nets

Special issue on intelligent tools and techniques for signals, machines and automation

A reliability analysis method for electromagnet performance degradation based on FMEA and fuzzy inference system

Contact Info

Product

Resources

About