Proposition of a modified FMEA to improve reliability of product

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29th 29th CIRP CIRP Design Design 2019 2019 (CIRP (CIRP Design Design 2019) 2019)

Proposition modified FMEA improve reliability 28tha Design Conference, 2018, Nantes, France of Proposition of of a CIRP modified FMEA to toMay improve reliability of product product

A new methodology to analyze the functional and physical architecture of aa bb existing products for an Ilyas assembly family identification Mzougui *, El Ilyas Mzouguioriented *, Zoubir Zoubirproduct El Felsoufi Felsoufi Paul Stief *, Jean-Yves Dantan, Alain Etienne, Ali Siadat

Faculty of Sciences and Technologies, Abdelmalek Essaadi University, Tangier, 90000, Morocco Faculty of Sciences and Technologies, Abdelmalek Essaadi University, Tangier, 90000, Morocco b École Nationale Supérieure d’Arts et Métiers, Arts et Métiers ParisTech, LCFC EA 4495, 4 Rue Augustin Fresnel, Metz 57078, France b Faculty of Sciences and Technologies, Abdelmalek Essaadi University, Tangier, 90000, Morocco Faculty of Sciences and Technologies, Abdelmalek Essaadi University, Tangier, 90000, Morocco a a

**Corresponding 3 87 37 54 30;E-mail E-mailaddress: address:[email protected] [email protected] Correspondingauthor. author.Tel.: Tel.:+33 +212660755864. * Corresponding author. Tel.: +212660755864. E-mail address: [email protected]

Abstract Abstract Abstract InFailure today’s business environment, is the trend towards more product variety and customization is unbroken. Due to this development, need of allows the identification identification of failures failures that could happen on on the system Failure mode mode and and effect effect analysis analysis is aa safety safety and and reliability reliability analysis analysis tool tool that that allows the of that could happen aa system agile and reconfigurable production systems emerged to cope with various products and product families. To design and optimize production and gives their effects and consequences. FMEA has many advantages, it is simple to use, time saving and highly effective. However. It has and gives their effects and consequences. FMEA has many advantages, it is simple to use, time saving and highly effective. However. It has systems well weaknesses. as to chooseAccording the optimal matches, product analysis methods areneeds needed. Indeed, most of the known methods aim to certainlyassome some to product specialists, to obtain obtain an effective effective result, FMEA certainly weaknesses. According to specialists, to an result, FMEA needs the the availability availability of of all all information information and and data. data. For For analyze a product or one product family on the physical level. Different product families, however, may differ largely in terms of the number and new systems, a correct risk analysis cannot be performed. The use of only 3 factors cannot describe and judge correctly failures in all activities. new systems, a correct risk analysis cannot be performed. The use of only 3 factors cannot describe and judge correctly failures in all activities. In this article, we will propose a modification to the conventional FMEA. We propose the use of the TRIZ Anticipatory Failure Determination nature of components. This fact impedes an efficient comparison and choice of appropriate product family combinations for the production In this article, we will propose a modification to the conventional FMEA. We propose the use of the TRIZ Anticipatory Failure Determination (AFD) identify all of the system. The Hierarchy is calculate the of system. A new methodology proposed products in viewProcess of their (AHP) functional andto architecture. aimfactor. is to cluster (AFD) to to identify all possible possibleisfailures failures of to theanalyze system.existing The Analytic Analytic Hierarchy Process (AHP) is used used tophysical calculate the weight weight The of each each factor. Those weight will be introduced on the Risk Priority Number (RPN) calculation. To prove its efficiency, this approach will be applied on these products in new assembly oriented product families for the optimization of existing assembly lines and the creation of future reconfigurable Those weight will be introduced on the Risk Priority Number (RPN) calculation. To prove its efficiency, this approach will be applied on aa product development assembly systems. Based phase. on Datum Flow Chain, the physical structure of the products is analyzed. Functional subassemblies are identified, and product on on development phase. 2019 The Authors. Published by Elsevier B.V. a© functional analysis performed. a hybrid functional and physical architecture graph (HyFPAG) is the output which depicts the © Authors.isPublished Published by Moreover, Elsevier B.V. © 2019 2019 The The Authors. by Elsevier B.V. committee of the CIRP Design Conference 2019 Peer-review under responsibility of the scientific similarity between product families by providing design support both, production system planners and product designers. An illustrative Peer-review under responsibility of the scientific committee of CIRP Design Conference 2019 Peer-review under responsibility of the scientific committee of the the to CIRP Design Conference 2019. example of a nail-clipper is used to explain the proposed methodology. An industrial case study on two product families of steering columns of Keywords: Type your keywords here, separated by semicolons ; FMEA, AFD, AHP, RPN, Maintainability, Cost thyssenkrupp Presta is then give a first industrial the proposed Cost approach. Keywords: Type yourFrance keywords here, carried separatedout by to semicolons ; FMEA, AFD,evaluation AHP, RPN,ofMaintainability, © 2017 The Authors. Published by Elsevier B.V. Peer-review under responsibility of the scientific committee of the 28th CIRP Design Conference 2018.

1. Introduction Keywords: Assembly; Design method; Family identification 1. Introduction According According to to the the automotive automotive Industry Industry Action Action Group Group (AIAG) (AIAG) [1], FMEA is an analytical methodology to ensure [1], FMEA is an analytical methodology to ensure that that potential potential 1.problems Introduction have problems have been been considered considered and and addressed addressed throughout throughout the the product and process development process. Its product and process development process. Its most most visible visible Due is fast development in the knowledge domain of result documentation of of result is tothe the the documentation of the the collective collective knowledge of communication and an ongoing trend of digitization and cross-functional teams. It includes a means of ranking the cross-functional teams. It includes a means of ranking the digitalization, manufacturing enterprises facing important severity failure to of severity of of the the failure modes modes to allow allowarepriorization priorization of the the countermeasures. This is done by producing the values challenges in today’s market environments: a continuing countermeasures. This is done by producing the values of of the the severity, occurrence and This value tendency reduction of product development times Risk and severity, towards occurrence and detection. detection. This value is is called called Risk Priority (RPN). MoreInthis this value is isthere highismore more the failure failure shortened product(RPN). lifecycles. addition, an increasing Priority number number More value high the is critical to the system. demand of customization, being at the same time in a global is critical to the system. FMEA introduced on by competition with competitors all over themilitary world. standards. This trend,It FMEA was was introduced on 1949 1949 by the the military standards. It was developed after that by Boeing on 56 and adapted to the which is inducing the development from macro to micro was developed after that by Boeing on 56 and adapted to the automotive industries as quality improvement tool. markets, results in diminished sizes due to augmenting automotive industries as aa lot quality improvement tool. product varieties (high-volume to low-volume production) [1]. To cope with this augmenting variety as well as to be able to identify possible optimization potentials in the existing 2212-8271 ©system, 2019 The Authors. Publishedtobyhave Elsevier B.V. knowledge production is important a precise 2212-8271 © 2019 The it Authors. Published by Elsevier B.V.

Nowadays, the core Nowadays, FMEA FMEA is is the core tool tool of of risk risk management management on on many many quality management standards such as the IATF 16949. quality management standards such as the IATF 16949. Koning Koning J, J, Jaspers Jaspers R, R, Doornink Doornink J, J, Ouwehand Ouwehand B, B, Klinkhamer Klinkhamer F, Snijders B, Sadakov S [2] considered that F, Snijders B, Sadakov S [2] considered that FMEA FMEA is is an an of the product range and characteristics manufactured and/or essential method for the development of risk analyses in essential method for the development of risk analyses in the the assembled in this system. Instrategies. this context, the main challenge in maintenance management maintenance management strategies. modelling and analysis is now only to cope single FMEA is a powerful tool, is systematic, wellwith organized FMEA is a powerful tool, it it not is systematic, well organized products, a limited product range or existing product families, and efficient. It allows to users the identification and and efficient. It allows to users the identification and the the classification of Moreover, it provide action but also to be able to analyze and to compare to define classification of failures. failures. Moreover, it can can products provide an an action plan to failures and improve the reliability of new families. It can be planproduct to the the critical critical failures andobserved improvethat the classical reliabilityexisting of the the system. However, as we told before, FMEA has product families are regrouped in function of clients or features. system. However, as we told before, FMEA has some some weaknesses. Many works have following However, assembly families are the hardly to find. weaknesses. Manyoriented works product have mentioned mentioned the following inconvenient: On the product family level, products differ mainly in two inconvenient: main characteristics: (i) the number of components and (ii) the •• Experts from disciplines the of type of components (e.g. mechanical, electrical, electronical). Experts from different different disciplines decide decide the rank rank of each each failure mode. It is hard for them to reach a consensus. Classical methodologies considering mainly single products failure mode. It is hard for them to reach a consensus. or solitary, already existing product families analyze the product structure on a physical level (components level) which causes difficulties regarding an efficient definition and comparison of different product families. Addressing this

Peer-review under responsibility of the scientific committee of the CIRP Design Conference 2019 Peer-review under responsibility of the scientific committee of the CIRP Design Conference 2019

2212-8271©©2017 2019The The Authors. Published by Elsevier 2212-8271 Authors. Published by Elsevier B.V. B.V. Peer-review under responsibility of scientific the scientific committee theCIRP CIRP Design Conference 2019. Peer-review under responsibility of the committee of the of 28th Design Conference 2018. 10.1016/j.procir.2019.04.315

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• The three factors are assumed to have the same importance without any distinction • The same RPN value can be the product of different group of O, S and D ranks. • Only three factors are involved in the failure priorization, some crucial factors such as time, maintainability or cost are not integrated on the failure judgement. • RPN are not continuous on many lobs such as 11, 43 and 901. Those values will never be the product of three factors. • Defining severity as the worst effect is overly pessimistic. The severity rank will thus be higher than the actual situation. According to Thurnes, Zeihsel, Visnepolschi and Hallfell [3], FMEA is limited to normal expectations of occurring failures, it uses the breakdown structure for products or processes to identify single failure causes and effects. Usually the FMEA provides no consideration for interconnected failures and failure scenarios. Many works tried to eliminate these weakness by proposing a more performed FMEA. The first study has been established by Kara-Zaitri [4]. He proposed the use of a fuzzy numbers modelization methodology under a simple matrix. This study allows the creation of data bases for the experts. However, this method is time consuming. MARTINS and Gilson [5] proposed the use of the Monte Carlo method to analyze and simulate risks. This method can identify all possible failures that emanate from a system with their probabilities but to perform the analysis, we need the availability of all information about the system. Facing this constraint, many studies proposed the use of fuzzy data that allows starting FMEA analysis despite lack of information. Kwai, Wang, Poon and Yang [6] proposed a new method for RPN calculation based on the developed methodology for multiple attribute decision. This method manages the failures priorization under uncertainties. Kutlu and Ekmekcioglu [8] used the fuzzy technique for order of preference by similarity to ideal solution (FTOPSIS) and the FAHP to obtain an improvement on the conventional FMEA. Kuo, T.-C. and Wua [9] used an approach by using the fuzzy AHP (FAHP) to rate the weight of each risk factor. This method was used to analyze the risk of green components in the European Union. The AHP method was developed by Saaty [7]. Zammori and Gabbrielli [10] performed the FMEA with using the analytic network process (ANP) method. This approach allowed the representation of the interaction between failures. Some of the research has proposed to improve FMEA by using additional factors. Carmignani [11] proposed the use of the profitability as a fourth criterion and used the AHP method to calculate the weight factors. Braglia, Bevilacqua and Gabbrielli [12] proposed a FMEA with 6 parameters instead of 3. These parameters are the association of Safety, Machine importance, Maintenance Costs, failure frequency, downtime length and operating condition. FMEA has limited the process of failures identification, it can only be used for the expected ones and for each failure it gives only single cause and effects. FMEA do not shows the

connections between failures. Many study proposed the use of the Anticipatory Failure detection (AFD) method to improve FMEA analysis. This method not only help in the identification of all possible failures but allows also the schematization and the understanding of failures and failures scenarios. Regazzoni and Russo [13] integrated the TRIZ tool on FMEA in a step by step approach. With this combination, they built an improved tool that can anticipate problems and give technical solutions to reduce failures criticality. The idea was to make a risk management tool more appealing for companies by trying to provide better results with involving few resources. Mendikoa, Sorli, Barbero, Carillo and Gorostiza [14] proposed an approach to improve collaboration between designers and manufacturers and to manage failures during the design phase of a product. Thurnes, Zeihsel, Visnepolschi and hallfell [3] proposed a method that combine the advantages of the FMEA and Anticipatory Failure prediction (AFP) to improve managing failures by creating failure scenarios and hypothesis. This method was called FMEAA. Russo, Birolini and Ceresoli [15] combined FMEA to TRIZ (Theory for inventive problem solving) methods to identify the elements that caused the failure of the cranes. In this article, we propose an improvement of the FMEA by using the AHP and the AFD methods. In the next paragraph, we will describe those two methods and the proposed approach. In the paragraph three, we will propose an application to a really case to summarize and conclude in the end. 2. The proposed approach The development stage is the most critical phases on a product life. Facing continuous changing and limitation on time and resources, each unidentified failure could have a terrible impact on the product development. As we already said, FMEA do not give good result for new system. An improvement is then needed to overcome this weakness. We propose a method that combine FMEA with AFD and AHP. Before describing the proposed approach, we will start first by a small presentation of these two methods. 2.1. The Anticipatory failure determination Anticipatory Failure Determinations (AFD) is a method of risk analysis that allows the identification of all possible and undesirable events that can impact the normal operation of a technical system. This method was proposed the first time by Altshuller and Al [16] and was declined on two tools. The first one is named AFD-1. The second one is called AFD-2 and was described by Kaplan, Zlotin and AL [17]. These methods presented a limitation on predicting failures due to human and organization factors. To Overpass this weakness, the AFD-3 was proposed. Aven and Krohn [18] combined the use of the brainstorming and the AFD. These methods were called integrated AFD. Suchkov [19] improved the process of failure identification by proposing a combination between function and resources. This method is called XTRIZ AFD and this is



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the version that we propose to use in our approach. The steps of this method are: • Select the system to analyze • Define the stage of system operation or stage of the life cycle • Build a function model of the system and the super system ○ Define subsystems and super system ○ Define functions between components of subsystems and the super system • Create the list of functions • Identify all resources that interacted with the system • Identify failures by interacting functions into resources • Estimate indirect and environmental impacts • Search for generic causes of failures • Rank potential failures and accidents The principle difference between AFD and conventional techniques of risk management such as FMEA and Hazard and Operability Analysis (HAZOP) results in the perspective from which potential failures are determined. In the conventional techniques, the process of failure prediction proceeds linearly from an articulation of the system function to what may occur if there is a failure in deliverance of these functions. According to the TRIZ journal, The AFD approach of determining potential failures is the reverse and the power of this technique comes from the process of inventing failures. The subversive method is used to invent, cause and create failures. According to Frenklach [20], the process of failures identifications requires not only asking the characteristically FMEA questions Why and What but furthermore asking the question How several times. Thurnes, Zeihsel, Visnepolschi and hallfell [3] said that the AFD method encourages these questions and it use improves the process of failure identification. According to Regazzoni and Russo [13], AFD has several parallels with the established methods such as FMEA, HAZOP or fault tree analysis. The main difference is that it forces users to take a much more proactive approach to finding causes of problems. Therefore, systems designed with this approach are less vulnerable to unpredicted failures. 2.2. The Analytical hierarchy processes Developed by Saaty [7], the AHP method is one of the multi criteria methods of hierarchical decision problems analysis. It is simple in his principle and on his application. This simplicity explains the considerable number of Scientifics that work with this method. It proceeds by two-by-two combinations of the elements of each hierarchical level by respecting the elements of the higher level. The method begins with the definition of the main objective to be achieved or the decision to be made, from which it breaks down this objective into a hierarchical structure of criteria and sub-criteria for evaluation. In the last hierarchical level, we find the candidates to evaluate the alternatives.

Figure 1AHP structure example

The AHP method makes it possible to structure a complex problem with several criteria. It also allows easy comparison of alternatives, criteria and sub criteria. The figure 1 shows an example hierarchical structure of a decision-making process for a problem of ordering five alternatives in terms of six different criteria. The steps to perform this method are: • Step1: This step consists to dress a matrix with the size equal to the number of criteria. Each criterion is compared to others according to its importance. To obtain the comparison values, we use the linguistic conversion scale of Saaty [7] represented in the table 1. Table 1 Linguistic conversion board of Saaty Numerical values

Verbal pairwise comparisons

1 Equal importance of two elements 3 Moderate importance of one element over another 5 Strong importance of one element over another 7 Very strong importance of one element over another 9 Extreme importance of one element over another 2, 4, 6, 8

Intermediate values

• Step 2: In this step, we proceed to the normalization of the comparison matrix by the use of the following equation.

• Step 3: The normalized matrix will be used to calculate the weight of each criterion using the following equation.

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2.3. The modified FMEA FMEA and AFD are both two valuable tools for risk management. FMEA is an organized and simplified tool that is well accepted and standardized. AFD is the most innovative and creative method ever developed on risk management. This method combines the benefit of these two methods. With the combination of these two methods, we will improve drastically the process of failure identification. However, the weaknesses due to the use of only 3 factors to judge failures continues to exist. Under product development, one of the most relevant factor is the cost and it should be integrated on the risk analysis. To describe well failures, another factor need to be included and it is related to the final customer. We choose the use of the maintainability as the fives factor. NF X 60-010 [21] define it as the ability of an appliance, machine or facility to be maintained or restored, over a given period, in a state in which it can perform a required function. A maintainability is higher on a product that need less hour and technicity for it reparation. The integration of this factor on the development phases allows the reduction of the product complexity and improves the customer satisfaction. To obtain failures values related to these two factors. We propose the use of the scales shown on the Table 2 and 3 Table 2 Maintainability Scale Effect

Criteria: Maintainability

Extreme Hight impact

Failure that cause an extreme reparation and or spare part changing. The reparation hours exceed 18 hours

Ranking

Table 3 Cost Scale Effect

Criteria: Cost

Extreme Hight cost

An important fail that requires a substantial change on the product to be fixed. The cost is higher than 10% of the budget. A risk that can impact the milestone of the product

Ranking

10

Very Hight Cost

An important fail that requires a change on the product to be fixed. The cost is estimated between 10% and 2,5%

9

Hight Cost

An important fail that requires a change on the product to be fixed. The cost is estimated between 2,5% and 0,5%

7-8

Moderate Cost

The risk leads a change on the product. It has a minor impact on cost and manhours

4-5-6

Low Cost

The change can be applied without additional cost No modification is needed

1-2-3

The RPN equation will support the use of a weight associated to each factor. The Table 4 shows these values obtained using the AHP method. Table 4 Factor weights Severity Occurrence Detection

10

Weights

29%

12%

22%

Maintenability

Cost

11% 26%

After presenting all parameters needed for our approach, the proposed approach steps will be proposed in the next.

Very Hight impact

Failure that cause a very Hight reparation and or spare part changing. The reparation hours are between 12 and 18

9

Hight impact

Failure that cause a Hight reparation and or spare part changing. The reparation hours are between 12 and 8

7-8

Moderate impact

Failure with a medium reparation and or spare part changing. The reparation hours are between 2 and 8

4-5-6

Low impact

Failure with a low reparation and or spare part changing. The reparation hours are less than 2.

1-2-3

• Step1: Schematization of information After identifying the principal function, the system is divided into components and subcomponents. We define after that functions to link them and a graph of cause and effect connections is built. This graph shows the useful and harmful functions and the principal function of the system. • Step2: Identifying focal point By using the system diagram, we identify the focal point as the part that have high number of incoming and outgoing links • Step 3: Failure identification The identification of the failures is done on two stages: ○ Development of the AFD direction using the Source Effect Object Result. With this model we build hypothesis after destructing the object by the harmful source. We will obtain in the final failure hypothesis. ○ To obtain more failure hypothesis, the question of how can I make this harm happened need to be asked. • Step4: Use the FMEA to assess risks After identifying all possible risks, we fill all failures in FMEA. Each one of them is judged according to the 5 factors: Severity, Occurrence, Detection, Cost and Maintainability.



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After obtaining the judgement values, the RPN is calculated using the following equation.

Temperature Wiring system Stator Case

RPN=( S X ∝S) + (O X ∝O) + (D X ∝D) + (C X ∝C) + (M X ∝M)

With S= The value of Severity obtained using AIAG FMEA scale O= The value of Occurrence obtained using AIAG FMEA scale D= The value of Detection obtained using AIAG FMEA scale C= The value of Cost obtained using the table 3 scale M= The value of Maintainability obtained using the table 2 scale ∝S= The weight of severity ∝O= The weight of Occurrence ∝D= The weight of Detection ∝C= The weight of the Cost ∝M= The weight of Maintainability • Step 5: The subversion method In this step, we will use a subversion method to identify the solutions to the critical failures. For each one, we create a diagram to find the solution to prevent failures. The diagram shows failure mechanism chains and contradictions and by analyzing them we will obtain a reliable solution.

• Step 6: The evaluation of solutions In this step we will evaluate if the solution can prevent the failure. In the end, we will update the values of factors and then the RPN values. In the next paragraph, we will test the applicability and the effectiveness of this method on a real case study. 3. Case study The approach described in the top will be applied to manage risks for an electrical Motor. This product is an electrical machine that converts electrical energy into mechanical energy. The product chosen is on the development phases and was designed to load big weights under elevated temperature and in a corrosive environment such us sea. The table 5 contains the elements of this system divided into resources class. After obtaining the element list, a graph is then built to present the cause and effect connections. The failure identification process start around the harmful source and the failure hypothesis are obtained. This graph is shown on figure 2. We set all failures on FMEA and we calculate the associated RPN. For the critical failure, we will use the step 5 and 6. The FMEA for this type of failures is shown on table 6.

1007 5

Coil of the stator Rotor Magnet Short circuit ring Rotor Shaft Bearing Fan system

Material

Table 6 FMEA developed from the failures diagram

Failure Mode

Terminal box

Cause of Failure

Effect of the failur e

RPN

Actions

Sealing problem

Fuse shut down

2,2

Control The operation of tithing Chose a better box

Improper connection

Fuse shut down

2

Provide a more explained schema

Wrong electrical connection

Fuse shut down

2,2

Train operators Improve the process

Short circuit between phases

Engin e shut down

2,9

Check the quality of the parts

2,7

Check the dimension of the power needed Make more tests Check the quality of the parts

Coil broken

Power needed is under estimated

Degradatio n in the insulator

The insular chosen is not appropriate

Loss of power 2,9

Check if the insular used is adapted to the conditions of work Check for a better insular

Misaligned coils

Short circuit between coils

Loss of power 2,1

Train operators Improve the process Improve the product

Weakness of the magnetic field

Short circuit between phases

Loss of power 2,7

Check the quality of parts make more tests

Overload

Loss of power 3,8

Check if the product is adapted to the needs Make more tests

Overheatin g

Loss of power 2,9

Check if the product is adapted to the needs Make more tests

Engin e shut down

Table 5 The element list Element list

Resource class

Electrical Energy Magnetic Field Mechanical Energy

Energy

Rotation

Information

Bar broken

The use of AFD gives to experts the opportunity to identifies all potential failures and FMEA attributes to them values and allows the RPN calculation and failures

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classification. The modification on the RPN equation with the integration of weight factors allows obtaining more realistic results. Integrating two additional factors gives a better accuracy for the risk analysis and improves the assessment and the priorization of failures. The use of the subversion method gives the possibility to obtain an efficient action plan. The use of a modified RPN equation reduced the obtained values. Engineers have agreed to fix 2 as the criticality threshold values.

and the threshold values needs to be adapted to be more appropriate for the criticality analysis. We rate that this method still under evolution and its application to complex systems will probably requires more refinements and adjustments to be adapted for engineer’s needs.

Figure 2 Diagram of components and failures causes and effects

4. Conclusion This paper proposes a method that combine the advantages of the AFD and FMEA methods. With this approach, the process of identification of failures is improved and the FMEA analysis could be performed despite lakes of information. The proposed approach integrates the concept of focal points, failure hypothesis and scenarios. Maintainability and cost are used as additional factors to improve failures priorization and classification. Considering the fact that the traditional RPN has been extensively criticized on many works, we proposed in this paper the use of weight factors and their introduction improves the accuracy and precision of the analysis. A case study has been presented to test the applicability and the effectiveness of this modified FMEA. The use of AFD allows the identifications of potential failures and helps engineers on assessing risks. The introduction of cost and maintainability as two additional factors improves failures judgement and the subversion analysis improves the effectiveness of action plans. However, the introduction of weight on RPN calculation has reduced the obtained values

References 1. 2.

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