Definition and Analysis of a New Risk Priority Number Concept

Braband, Jens

doi:10.1007/978-0-85729-410-4_322

Cited by 9 publications

(12 citation statements)

References 2 publications

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“…As discussed in Section 1, several disadvantages of the RPN approach are present [7,8]. Within this study, we presented a methodology to avoid all of the described pitfalls.…”

Section: Comparing Rpn Vs Ipm Approachmentioning

confidence: 99%

“…of consequence and probability of occurrence [3]. Due to its systematic approach for risk management, this guideline additionally lays the basis for the quality by design approach [4][5][6], which has been implemented in the biopharmaceutical industry for years.As a RA method, a failure mode and effects analysis (FMEA) tool aims to determine how a process can fail and evaluate the effect of this failure on the product [7,8]. This is determined via the risk priority number (RPN) approach which ranks the assessed risk of potential failure mode.…”

mentioning

confidence: 99%

“…As a RA method, a failure mode and effects analysis (FMEA) tool aims to determine how a process can fail and evaluate the effect of this failure on the product [7,8]. This is determined via the risk priority number (RPN) approach which ranks the assessed risk of potential failure mode.…”

mentioning

confidence: 99%

“…The numbers generally cover a range from 1 to 1000 or from 1 to 125. However, 88% of the RPN scale is empty [7,8]. An equal RPN number can be generated by an assessment of S = 7, O = 4, and D = 2.…”

mentioning

confidence: 99%

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Quantitative CPP Evaluation from Risk Assessment Using Integrated Process Modeling

Borchert¹,

Zahel²,

Thomassen

et al. 2019

Bioengineering

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Risk assessments (RAs) are frequently conducted to assess the potential effect of process parameters (PPs) on product quality attributes (e.g., a critical quality attribute (CQA)). To evaluate the PPs criticality the risk priority number (RPN) for each PP is often calculated. This number is generated by the multiplication of three factors: severity, occurrence, and detectability. This mathematical operation may result in some potential errors due to the multiplication of ordinal scaled values and the assumption that the factors contribute equally to the PPs criticality. To avoid these misinterpretations and to assess the out of specification (OOS) probability of the drug substance, we present a novel and straightforward mathematical algorithm. This algorithm quantitatively describes the PPs effect on each CQA assessed within the RA. The transcription of severity and occurrence to model effect sizes and parameters distribution are the key elements of the herein developed approach. This approach can be applied to any conventional RA within the biopharmaceutical industry. We demonstrate that severity and occurrence contribute differently to the PP criticality and compare these results with the RPN number. Detectability is used in a final step to precisely sort the contribution of each factor. To illustrate, we show the misinterpretation risk of the PP critically by using the conventional RPN approach. of consequence and probability of occurrence [3]. Due to its systematic approach for risk management, this guideline additionally lays the basis for the quality by design approach [4][5][6], which has been implemented in the biopharmaceutical industry for years.As a RA method, a failure mode and effects analysis (FMEA) tool aims to determine how a process can fail and evaluate the effect of this failure on the product [7,8]. This is determined via the risk priority number (RPN) approach which ranks the assessed risk of potential failure mode. The RPN is calculated by multiplying three factors: severity (S), occurrence (O), and detectability (D). Where S represents the severity of failure mode, O the probability of the failure, and D the likelihood of detecting the failure [6]. Resulting from its extensive use for many different applications, the RPN approach has been the most used assessment approach for years [9,10].Although widespread in the industry, it is often reported that the RPN approach is not the best assessment tool for such an evaluation [10,11]. This statement is supported by the following reasons:Bioengineering 2019, 6, 114 3 of 16 the biopharmaceutical process. Such a simulation strategy is called an integrated process model (IPM) and enables the simulation of the process outputs from a holistic point of view across the unit operation.

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“…As discussed in Section 1, several disadvantages of the RPN approach are present [7,8]. Within this study, we presented a methodology to avoid all of the described pitfalls.…”

Section: Comparing Rpn Vs Ipm Approachmentioning

confidence: 99%

mentioning

confidence: 99%

mentioning

confidence: 99%

mentioning

confidence: 99%

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Quantitative CPP Evaluation from Risk Assessment Using Integrated Process Modeling

Borchert¹,

Zahel²,

Thomassen

et al. 2019

Bioengineering

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“…Failure Mode and Effect Analysis (FMEA) is now a sustained tool which allows to analyze the risk of possible impact on any process, since the proposal of this tool it was rapidly adapted to different industries like automotive and electronics, and it is continuously being improved since that time. One of the main improvement on the FMEA, which is used until nowadays, is the Risk Priority Number (RPN) first introduced by Braband, [5]. Usually the FMEA is ranked by experts on the process under analysis, the RPN is the product ranked of three values, from 1 to 10, the three values are the Severity (S), Occurrence (O), and Detection (D), the final value of the RPN rank the critical potential failure modes (PFMs) on the process analyzed, helping to take the decision if the possible failure mode is a risk or no then, based on the previous range stablished of the RPN value, contingency plans have to be apply to avoid the risk of the possible failure.…”

Section: Introductionmentioning

confidence: 99%

PFDA- FMEA. An Integrated Method Improving FMEA Assessment in Product Design

Garcia¹,

Pérez-Domínguez²,

Luviano-Cruz³

et al. 2020

Preprint

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Product Design is getting nowadays new challenges on developing new products, since the industry is in a rush to introduce products into the marketplace, where customers demand products faster, cheaper, and free of failures. In the meantime, global companies are always trying to improve their Product Design process to get advantages over their competitors using proven tools like FEMA and mixing methodologies like Fuzzy theories with FMEA. Even today using all this tools and combination of methodologies there is a gap to address and it is required a robust risk analysis solving current issues in the electronic industry. This document aims to reveal a novel integrated method, where Failure Mode and Effect Analysis, Pythagorean Fuzzy Sets and Dimensional Analysis are cohesive into a model that minimize the uncertainty of the ranking and prioritization over the Failure Mode and Effect Analysis execution, helping to identify risks within an accurate grade over possible failures in the Product Design process. A real practical example is used to show the proposed method, where it is identified a robust methodology integration and solid and results using a sensitivity analysis.

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Failure mode and effects analysis using function–motion–action decomposition method and integrated risk priority number for mechatronic products

Wang

Ran

et al. 2021

Quality & Reliability Eng

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Failure mode and effects analysis is a widely applied risk assessment method in various engineering and management domains. However, the identification of failure modes is difficult and uncountable. Therefore, a function-motion-action (FMA) decomposition method is developed to identify failure modes from the perspective of motion and extraordinarily suitable for mechatronic products. In the typical risk assessment, the ranking orders of failure modes are determined by risk priority number (RPN), which has been criticized for several drawbacks and improved by some alternative RPNs, but some drawbacks still exist, such as duplicate values, narrow admissible value range, and missing failure modes' and risk factors' weights. This study formulates several alternative weighted RPNs to overcome the above drawbacks, and the final ranking orders of failure modes are garnered through the integrated RPN (IRPN). First, failure modes are identified via the proposed FMA decomposition method and evaluated with crisp values, whose weights are aggregated from the basic failure modes' weights. Second, the weights of the basic failure modes, risk factors and different RPN methods are derived from analytic hierarchy process. Third, the conditional weights of risk factors are determined by incorporating risk factors' weights and failure modes' conditional weights deduced from Shannon entropy. Next, several alternative weighted RPNs and IRPN are formulated to rank failure modes' risk levels. Finally, an illustrative example about computer numerical control machine center is presented to demonstrate the application and effectiveness of the proposed method.

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Definition and Analysis of a New Risk Priority Number Concept

Cited by 9 publications

References 2 publications

Quantitative CPP Evaluation from Risk Assessment Using Integrated Process Modeling

Quantitative CPP Evaluation from Risk Assessment Using Integrated Process Modeling

PFDA- FMEA. An Integrated Method Improving FMEA Assessment in Product Design

Failure mode and effects analysis using function–motion–action decomposition method and integrated risk priority number for mechatronic products

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