Failure Mode Effects And Criticality Analysis Research Articles

A graph theory approach to predicting functional failure propagation during conceptual systems design

AbstractAn open area of research for complex, cyber‐physical systems is how to adequately support decision making using reliability and failure data early in the systems engineering process. Having meaningful reliability and failure data available early offers information to decision makers at a point in the design process where decisions have a high impact to cost ratio. When applied to conceptual system design, widely used methods such as probabilistic risk analysis (PRA) and failure modes effects and criticality analysis (FMECA) are limited by the availability of data and often rely on detailed representations of the system. Further, existing methods for system reliability and failure methods have not addressed failure propagation in conceptual system design prior to selecting candidate architectures. Consideration given to failure propagation primarily focuses on the basic representation where failures propagate forward. In order to address the shortcomings of existing reliability and failure methods, this paper presents the function failure propagation potential methodology (FFPPM) to formalize the types of failure propagation and quantify failure propagation potential for complex, cyber‐physical systems during the conceptual stage of system design. Graph theory is leveraged to model and quantify the connectedness of the functional block diagram (FBD) to develop the metrics used in FFPPM. The FFPPM metrics include (i) the summation of the reachability matrix, (ii) the summation of the number of paths between nodes (i.e., functions) i and j for all i and j, and (iii) the degree and degree distribution. In plain English, these metrics quantify the reachability between functions in the graph, the number of paths between functions, and the connectedness of each node. The FFPPM metrics can then be used to make candidate architecture selection decisions and be used as early indicators for risk. The unique contribution of this research is to quantify failure propagation potential during conceptual system design of complex, cyber‐physical systems prior to selecting candidate architectures. FFPPM has been demonstrated using the example of an emergency core cooling system (ECCS) system in a pressurized water reactor (PWR).

Comparative Analysis of RPN and Criticality Index for Assessment and Prioritization of Dumper Breakdowns

Dumper is a repairable equipment which is used to carry and dump the coal in open cast mining (OCM). Due to the enhanced demand for thermal power, the consumption of coal has increased to generate electricity. To meet the demand, coal must be produced and supplied at right time in right quantity. Dumpers, which act as load transport system, carry the coal from the mine to the power plant. Interruptions in the dumpers in the form of failures may result in improper and delayed delivery of coal to the power generating unit. In the interest of proper delivery and production of coal, failures are to be minimized and the reliability of the dumper should be maximized. In this paper, a well-known reliability enhancement metric, i.e., failure mode effect and criticality analysis (FMECA) is used to identify the risk and criticality level of dumper breakdowns. Initially, FMEA is carried out to find out all potential failure modes of functionally significant components of dumpers and thereafter, risk priority number (RPN) and criticality index is computed for each identified failure mode. Further, a comparative analysis of RPN and criticality index is performed to find out the convenient approach to conduct criticality analysis in FMECA.

Proposed maintenance policy using reliability centered maintenance (RCM) method with FMECA analysis: A case study of automotive industry

PT XYZ is one of the companies engaged in the automotive industry, especially in the motorcycle industry that produces spare parts on motorcycles. One component made by PT XYZ is Guide Comp Level K1AA. The problem in the company is one of the machines to produce the Guide Comp Level K1AA component, which is a Press machine that has a high frequency of failure. The Press machine itself consists of electrical and mechanical systems that each system consists of sequential subsystems as many as 6 subsystems and 10 subsystems. By using risk matrix, obtained two critical subsystems namely brake and trigger. Then the analysis of failure mode, effects and criticality analysis (FMECA) was carried out with output in the form of risk priority number (RPN), obtained that the selected critical subsystem is the brake. Using the reliability centered maintenance (RCM) method, then obtained the maintenance policy for the brake critical subsystem are 2 scheduled on condition task with interval time is 2.55 months and 2 scheduled restoration task with 5,394 months. The proposed maintenance policy also decreases the total maintenance cost for the critical subsystem brake up to 25% from existing maintenance costs.

Risks associated with the evolution in the compounding process of parenteral nutrition solutions: use of the “FMECA” method

Abstract Objectives An audit of the practices of our compounding unit was performed in 2016: areas of improvement were proposed, such as the automatization of our process. An automated compounder was acquired (MediMixmulti® MF4120R). The aim of the study was to anticipate the risks of the new process, in order to improve its security and to support the professionals during this evolution of our compounding process. Methods The Failure Modes, Effects and Criticality Analysis (FMECA) method was carried out in order to detect potential failures brought by the automatization of parenteral nutrition (PN) manufacturing in the new process. The FMECA method included four steps that were divided into five work sessions of one and a half hour each over a period of two months. A working group made up of professionals involved in the PN production process was set up (pharmacists, pharmacy resident, manager and pharmaceutical technician). Results Fifty failure modes were determined by this analysis, of which 96% could have an impact on the patient, 90% on the health staff and 74% on the product. The FMECA shows that 18 failure modes have a tolerable or unacceptable CI (CI≥100) for which it is necessary to implement preventive measures as a priority. This work also made it possible to review the barrier measures already in place for the current process. Conclusions The risk analysis allowed us to analyze the failures of both the actual and the future manufacturing processes. Once the most critical failure modes were identified, specific recommendations were proposed and an improvement plan was established. First, the compounder needs to be fully qualified. Then, the quality manual of the PN process will be reviewed and updated. Once these steps are completed, the pharmacy professionals (pharmacists, pharmacy technicians) will be trained and the PN production will be performed using the automated compounder on a daily basis.

Integration of FMECA and statistical snalysis for predictive maintenance

<p>The estimation of time-to-failure of machines is of utmost importance in the Manufacturing Industry. As the world is moving towards Industry 4.0, it is high time that we progress from the traditional methods, where we wait for a breakdown to occur, to the prognostics based methods. It is the need of the era to be aware of any incident before it occurs. This study provides application of Statistical-based Predictive maintenance. A BOPP Production line has been considered as a case study for this research. Since the inception of the line in 2013, it is evident that 60% of breakdowns are due to lack of maintenance and timely replacement of bearings. Therefore, the research is based on the application of FMECA (Failure Modes, Effects and Criticality Analysis) to determine which bearing in the production line is most prone to failure and determination of which statistical model best fits the failure data of the most critical bearing. The result provides the best distribution fit for the failure data and the fit can be utilized for further study on RUL (Remaining Useful Life) of the bearing through Bayesian Inference.</p>

Model-Based Safety Analysis and Design Enhancement of a Marine LNG Fuel Feeding System

Recent regulatory requirements for shipping emissions control have led to the adoption of Liquefied Natural Gas (LNG) as a marine fuel and the design of LNG-fuelled vessels. Considering the potential safety implications due to system failure/unavailability, this study aims at the safety analysis of a low-pressure LNG fuel feeding system using a novel model-based methodology. The proposed methodology is based on the functional system modelling, leading to the failure diagrams development, and combines the use of Failure Modes, Effects, and Criticality Analysis (FMECA) and Fault Tree Analysis (FTA), which are performed in MADe™ and PTC Windchill software environments. The FMECA results are employed to identify the investigated system critical components and failures as well as specifying the top events for the subsequently performed FTA, which evaluates the top events failure rates. The system critical components identification leads to the system design modification targeting reduced safety metrics. This study results demonstrate that the evaporator, pressure build-up unit, sensors, and cryogenic valve assemblies are the most critical components of the investigated system, whilst the enhanced system design exhibits a failure rate reduced by 69% in comparison to the baseline system. This study reveals the advantages of the developed methodology along with some limitations of the employed tools and contributes to the quantitative safety analysis and design of ship complex systems.

FMECA Assessment for Railway Safety-Critical Systems Investigating a New Risk Threshold Method

This paper develops a Failure Mode, Effects and Criticality Analysis (FMECA) for a heating, ventilation and air conditioning (HVAC) system in railway. HVAC is a safety critical system which must ensure emergency ventilation in case of fire and in case of loss of primary ventilation functions. A study of the HVAC's critical areas is mandatory to optimize its reliability and availability and consequently to guarantee a low operation and maintenance cost. The first part of the paper describes the FMECA which is performed and reported to highlight the main criticalities of the HVAC system under analysis. Secondly, the paper deals with the problem of the evaluation of a threshold risk value, which can distinguish negligible and critical failure modes. Literature barely considers the problem of an objective risk threshold estimation. Therefore, a new analytical method based on finite difference is introduced to find a univocal risk threshold value. The method is then tested on two Risk Priority Number datasets related to the same HVAC. The threshold obtained in both cases is a good tradeoff between the risk mitigation and the cost investment for the corrective actions required to mitigate the risk level. Finally, the threshold obtained with the proposed method is compared with the methods available in literature. The comparison shows that the proposed finite difference method is a well-structured technique, with a low computational cost. Furthermore, the proposed approach provides results in line with the literature, but it completely deletes the problem of subjectivity.

Fuzzy FMECA Process Analysis for Managing the Risks in the Lifecycle of a CBCT Scanner

The Failure Mode, Effects, and Criticality Analysis (FMECA) is one of the risk analysis techniques proposed by the ISO 14971 Standard. This analysis allows to identify and assess the consequences of faults that affect each component of a complex system. The FMECA is a forward-type technique used for highlighting critical points and classifying them by priority. It also makes it possible to evaluate the extent of failures by means of numerical indices. It can be applied to a product or to a work process. In the latter case we talk about Process-FMECA. The application of the Process-FMECA to bioengineering is of particular interest because this procedure provides an analysis related to risk management during all the different phases of the medical device life cycle. However, practical applications of this method have revealed some shortcomings that can lead to inaccuracies and inconsistencies regarding the risk analysis and consequent risk prioritization. This paper presents an example of application of a Fuzzy Process-FMECA, an improved Process-FMECA based on fuzzy logic, to a small computerized tomography (CT) device prototype designed for studying the extremities of the human body. This prototype is a CT device that uses the Cone Beam CT (CBCT) technology. The Fuzzy Process-FMECA analysis has made it possible to produce a table of risks, that are quantified according to the specifications of the method. The analysis has shown that each phase or activity is fundamental to guarantee a correct functioning of the device. The methodology applied to this specific device can be paradigmatic for analyzing the process risks for any other medical device.

System reliability analysis of forage crushing machine based on fuzzy FMECA

This paper aims to address the problems of high failure rate, poor reliability, and incomplete failure data associated with forage crushing machines. First, the failure mode effects and criticality analysis (FMECA) is combined with the fuzzy theory to transform the influencing factors on failure modes into fuzzy variables. Then, the analytic hierarchy process (AHP) is used to determine the weight of each influencing factor, and a comprehensive criticality degree is calculated for each failure mode to determine the key component posing the greatest criticality of disrupting the operation of the equipment. The results of the analysis show that fuzzy FMECA can be used to rank the comprehensive criticality degree of each failure mode. Furthermore, the results are consistent with the criticality ranking of failure modes obtained under actual operating conditions and can therefore be to determine the most critical failure mode and the key component. Fuzzy FMECA also provides valuable reference data for improving the design and system reliability and to effectively reduce the failure rate of forage crushing machines.

Composite Hybrid Framework for Through-Life Multi-Objective Failure Analysis and Optimisation

Complex engineering systems include several subsystems that interact in a stochastic and multifaceted manner with multiple failure modes (FMs). The dynamic nature of FMs introduces uncertainties that negatively impact the reliability, risk, and maintenance of complex systems. Traditional approaches of adopting standalone techniques for managing FMs independently at various stages of the asset life cycle pose challenges related to utilisation, costs, availability, and in some cases, accidents. Therefore, this paper proposes a composite hybrid framework comprising four independent hybrid models for comprehensive through-life failure management and optimisation. The first hybrid model entails failure mode, effects, and criticality analysis (FMECA) and fault tree analysis (FTA) to identify critical FMs and overall subsystem failure rates. The second hybrid model analyses FMs caused by multiple subsystems using hybrid dynamic Bayesian discretisation. The third hybrid model adopts a hybrid Gaussian process regression machine learning technique to evaluate wear loss. The fourth hybrid model evaluates the overall risk using a Bayesian factorisation and elimination method based on multiple failure causes. Finally, a decision-making step is used to evaluate the results of the previous four steps to decide an appropriate maintenance strategy. The proposed method is verified through a case study of a UK-based train operator’s pantograph system. The results show that the maintenance inspection intervals and strategy obtained using the proposed framework strike a good balance between safety and fleet availability.

An efficient global reliability analysis method for turbine disc’s multi-failure modes considering importance distribution technology

This paper presents an improved efficient global reliability analysis (EGRA) method for a turbine disc considering the importance distribution of multi-failure modes, such as low cycle fatigue (LCF) and creep-fatigue (CF). Failure mode effects and criticality analysis (FMECA) technology is firstly used to analyse the criticality and occurrence probability of each failure mode. Importance factor S is then proposed to quantify the importance of the corresponding failure mode. In order to improve the reliability analysis’s efficiency, expected feasibility function (EFF) criterion in sequential sampling method is selected through numerical experiments to generate the samples of random variables. Secondly, EGRA method is established by combining sampling method with Kriging model, in which the performance function is fitted using the key sampling points near both the failure boundaries and high uncertainty region. On the basis of EFF criterion, the composite EFF criterion applied to EGRA method is developed. This method avoids repeated analysis on non-significant failure modes, which further improves the reliability analysis’s efficiency for the multi-failure modes system. Through a binary nonlinear example, it is proved that the prediction accuracy is 99.8% compared with Monte Carlo method. Moreover, the computational time of reliability is reduced by half compared with EFF criterion, which proves the prediction efficiency of composite EFF criterion. Finally, the reliability analysis on a turbine disc is conducted using the improved EGRA method combining with the failure mode importance distribution technology. Results show that the fatigue life at 99.9% reliability is decreased by 7.4% after considering the importance of failure modes, indicating that the ignoration of failure modes’ importance would lead to a more dangerous prediction result.

Availability and Reliability Assessment for ITER Radial X-Ray Camera System in Final Design

ITER is an international experimental nuclear fusion device. In the project, the RAMI approach (reliability, availability, maintainability, and inspectability) has been adopted for technical risk control to mitigate all the possible failures of components in preparation for operation and maintenance. The availability and reliability assessment is required and is one of main design contents in the ITER radial X-ray camera diagnostic (RXC) system final design review phase. The availability and reliability assessment, based on the RAMI program, ensured the system with a very high performance to measure the X-ray emission and research the MHD of plasma with high accuracy on the ITER machine. A functional breakdown was prepared in a bottom-up approach, and the system was divided into three main functions, eight intermediate functions, and 31 basic functions which are described using the IDEFO method. Reliability block diagrams (RBDs) were prepared to calculate the reliability and availability of each function under assumption of operation conditions and failure data. Initial and expected scenarios were analyzed to define risk-mitigation actions. The initial availability of RXC system was 86.13%, while after optimizations were taken the expected availability was 92.57%. The initial reliability for all functions of ITER RXC system was 92.3% without spares and 94.7% with spares over 16 months. A failure modes, effects, and criticality analysis (FMECA) was performed to the system initial risk. Criticality charts highlight the risks of the different failure modes with regard to the probability of their occurrence and impact on operations. There are 29 risks for the initial state, including 16 major risks. No major risk remains after taking into account all the actions. It was assessed that the RAMI analysis results meet the project requirement in the final design phase and the results will be qualified further with the system manufacture going ahead.

A hybrid reliability-centered maintenance approach for mining transportation machines: a real case in Esfahan

PurposeThe purpose of this study is to propose a hybrid reliability-centered maintenance (RCM) approach for mining transportation machines of a limestone complex, a real case in Esfahan, Iran.Design/methodology/approachCriteria for selecting critical machines were collected within literature and selected by decision-makers (DCs), and critical machines have been identified using the preference ranking organization method for enrichment of evaluations (PROMETHEE). Also, multi-criteria decision-making (MCDM) methods were used in addition to failure mode, effects and criticality analysis (FMECA) for selecting and prioritizing high-risk failures as well as optimizing the RCM performance. More specifically, the criteria of severity, detectability and frequency of occurrence were selected for risk assessment based on the previous studies, and were weighted using the analytic hierarchy process (AHP) method. Also, the technique for order of preference by similarity to ideal solution (TOPSIS) has been applied to prioritize failures' risk. Finally, the critical failures were inserted in the RCM decision-making worksheet and the required actions were determined for them.FindingsAccording to the obtained values from PROMEHTEE method, the machine with code 739-7 was selected as the first priority and the most critical equipment. Further, based on results of TOPSIS method, the failure mode of “Lubrication hole clogging in crankpin bearing due poor quality oil,” “Deformation of main bearing due to overwork” and “The piston ring hotness due to unusual increase in the temperature of cylinder” have the highest risks among failure modes, respectively.Originality/valueRCM has been deployed in various studies. However, in the current study, a hybrid MCDM-FMECA has been proposed to cope with high-risk failures. Besides, transportation machineries are one of the most critical equipment in the mining industry. Due to noticeable costs of this equipment, effective and continuous usage of this fleet requires the implementation of proper maintenance strategy. To the best of our knowledge, there is no research which has used RCM for transportation systems in the mining sector, and therefore, the innovation of this research is employment of the proposed hybrid approach for transportation machineries in the mining industry.

Managing sewerage networks using both failure modes, effects and criticality analysis (FMECA) and analytic hierarchy process (AHP) methods

This paper proposes a methodology for managing complex sewerage networks based on the concomitant use of two performance evaluation methods, namely, the failure modes, effects, and criticality analysis (FMECA) and the analytical hierarchy process (AHP). The FMECA is used to determine the risks of structural failures making it possible to establish a methodology for managing these failures. The AHP is used to check the relationship consistency between the performance indicators allowing the determination of the overall performance (OP). This proposed methodology was utilized for the urban sewerage network of Oued-Kniss in the city of Algiers, Algeria, as part of the efforts engaged in for sustainable and efficient management.

Multilevel Simulation Methodology for FMECA Study Applied to a Complex Cyber-Physical System

Complex systems are composed of numerous interconnected subsystems, each designed to perform specific functions. The different subsystems use many technological items that work together, as for the case of cyber-physical systems. Typically, a cyber-physical system is composed of different mechanical actuators driven by electrical power devices and monitored by sensors. Several approaches are available for designing and validating complex systems, and among them, behavioral-level modeling is becoming one of the most popular. When such cyber-physical systems are employed in mission- or safety-critical applications, it is mandatory to understand the impacts of faults on them and how failures in subsystems can propagate through the overall system. In this paper, we propose a methodology for supporting the failure mode, effects, and criticality analysis (FMECA) aimed at identifying the critical faults and assessing their effects on the overall system. The end goal is to analyze how a fault affecting a single subsystem possibly propagates through the whole cyber-physical system, considering also the embedded software and the mechanical elements. In particular, our approach allows the analysis of the propagation through the whole system (working at high level) of a fault injected at low level. This paper provides a solution to automate the FMECA process (until now mainly performed manually) for complex cyber-physical systems. It improves the failure classification effectiveness: considering our test case, it reduced the number of critical faults from 10 to 6. The remaining four faults are mitigated by the cyber-physical system architecture. The proposed approach has been tested on a real cyber-physical system in charge of driving a three-phase motor for industrial compressors, showing its feasibility and effectiveness.

Risk Assessment of a Wind Turbine Using an AHP-MABAC Approach with Grey System Theory: A Case Study of Morocco

Clean energy has become a growing concern, and many organizations pay attention to environmental protection and energy production as well. In the last few decades, the wind turbine has become the core of clean energy production and has advanced in generating electricity from 40 kW to 5 mW. However, the new design of the wind turbine causes several potential failures which frequently lead to the inability to accomplish the operational requirements intended to meet the customers’ expectations. As a solution to this problem, the present paper proposes a novel systematic approach that combines Multicriteria Decision-Making (MCDM) techniques and Failure Mode Effects and Criticality Analysis (FMECA) tool to reveal the fatal failures and optimize the maintenance actions. To further develop the preceding framework, this work will not only rely on the three risk factors that are involved in the traditional Risk Priority Numbers (RPN) approach but also will consider the economic aspect of the system. In the proposed approach, the grey Analytic Hierarchy Process (AHP) method is applied in the first place to calculate the weights of the four risk factors criteria. Second, the grey Multiattribute Border Approximation area Comparison (MABAC) technique is applied to rank the failure modes and their criticality on the whole system. The proposed model is verified within an organization of renewable energy production in Morocco. Furthermore, the results of the comparative and the sensitivity analysis affirm that the proposed research framework is adequate for enhancing other complex systems design, especially in a developing world where funds and resources are scarce.

A study on irradiated welding joints in ITER materials and its effects on FMECA analysis of components

Abstract ITER (International Thermonuclear Experimental Reactor) is a huge engineering challenge. ITER Project is in construction phase, the machine is very complex and is an assembly of hundreds of different components. Due to its large assembly and huge welding of different materials, it needs to have certain kind of reliability for safe operation. The reliability of machine is achieved in various lifecycle stages from design to manufacturing through ITER RAMI programme. Reliability and failure rate of weld influence availability of machine [1]. In this paper a study is done for the effects of irradiation on weldments and its mechanical properties and understanding various parameters which can affect the reliability of weld due to irradiation. Various papers were studied to understand changes in mechanical properties in weldment due to irradiation. Thus, by understanding various irradiation scenarios of ITER along with FMECA(Failure mode effect and criticality analysis) as tool, this work tries to systematically recognize, evaluate and prioritize the risk and potential failures. FMECA is a part of ITER RAMI programme. Failure rate data is an important input for FMECA analysis. In this study two weld seams, seam 1 and seam 2 were selected respectively in cryostat and neutral beam duct to understand irradiation condition under ITER working scenario. Flux and DPA at their Cartesian coordinates were found out with the help of various softwares for ITER project. FMECA chart is drawn to understand the severity and criticality under different irradiation scenario for these welds. Thus correlating mechanical properties of irradiated material to reliability, with FMECA as a tool will help in assessing availability of machine and lifecycle management of components. This will help in better understanding on failure rate data of non-irradiated conditions to be used for irradiated condition and changing neutron load in fusion reactors.

A novel approach in probabilistic quantification of risks within the context of maritime supply chain: The case of extreme weather events in the Arctic

Extreme Weather Events (EWEs) are currently not well understood by the maritime community, even though the shipping industry is not immune to their potential disastrous consequences. This is critical for the Arctic supply chains, considering the serious lack of experience, data, communication facilities, and that rules and regulations governing the region are at the embryonic stage. Understanding such, the study develops an effective risk assessment model in the context of the maritime supply chain and quantifies the risks associated with EWEs in the Arctic. The model is developed based on a Bayesian Belief Network (BBN) that reflects a probabilistic risk priority index based on Failure Mode, Effects and Criticality Analysis (FMEA). Here, we introduce a new index, based on a weighted combination of the likelihood, visibility, and consequence of risk factors. The model is quantified by 51 respondents based on their sailing experience with cargo carriers along the Northwest Passage. Our findings suggest that dense fog and ice accretion are distinctly critical risk factors followed by thunderstorm, hail and/or waterspouts, extreme coldness, and blizzard. The study offers useful insight to all right- and stakeholders in the Arctic. Moreover, it presents an effective tool to develop high-resolution maps for maritime routes considering important shipping elements.

통합마스트-송수신 모듈의 열화인자 분석을 통한 결함진단 및 잔여수명 예측 연구

Frequently installed on latest destroyers, integrated mast (I-mast) conducts tasks including coast and air-space surveillances. I-mast is a complex multi-domain system with various mechanical and electrical subsystems and components. In the perspective of diagnosis and maintenance, it is important to technologically manage this system for long operating time periods and eventually increase its survivability. We explore the prognostics and health management (PHM) process of I-mast and transmitter receiver module (TRM) using the framework of Modelica-based system simulation. With Modelica, one can reuse components employed in a model, easily model a system expressed in mathematical language, and conduct a multi-dimensional, multi-physics analysis. First, failure mode effects and criticality analysis (FMECA) was conducted to extract the major failure and degradation factors of an I-mast structure and TRM under the vessel’s vibrating and operating conditions. To quantitatively assess the risk priority number (RPN), we propose the use of design of experiments (DoE) and analysis of variance (ANOVA). To preprocess the vibration acceleration signals, principal component analysis (PCA) was used to identify major features from statistical multi-components. Subsequently, based on the diagnosis of fault states, the prediction of remaining useful life (RUL) of I-mast and TRM has been discussed in the context of PHM.

Testing Mitigation in Safety Critical Systems: Trade-Off Analysis of Various Testing Criteria

This is the first paper of a set of papers dealing with cost of failures. In Safety Critical Systems (SCSs), trade -off the cost of failures (due to lack of testing) against the cost of testing is essential. Usually stronger test criteria are more costly to test, but also more effective at finding faults which if not exposed during testing could lead to operational failures incurring their cost. This paper presents a trade-off cost model that evaluates various criteria for testing mitigation of failures against the cost of defective mitigation. Failure Mode Effect and Criticality Analysis (FMECA) are used to quantify cost of failure, measure the return on investment (ROI) for mitigation test criteria.