Abstract:Identification of failure modes is a vital work in the process of failure mode and effect analysis (FMEA). Since the traditional failure mode is defined as a specific function failure or a part failure, there are uncountable failure modes for mechanical products. Then, it is too hard to list or predict all of the potential failure modes when we do FMEA on a machine. Besides, the same failure can be defined as a failure mode or a failure cause casually, which makes the analysis work stuck. To solve these proble… Show more
“…It is more reasonable and effective for reliability analysis and reliability allocation of electromechanical products. 33,60 With regard to CNC machine tools, they are typical electromechanical products and integrate multiply techniques to accomplish the desired functions. Through implementing the FMA decomposition method to CNC machine tools, we could obtain substantial meta-action units.…”
“…However, failure modes in mechatronic systems are usually confused with failure causes, thanks to not strict demarcation between failure mode and failure cause. 33 Therefore, a function-motion-action (FMA) decomposition method extraordinarily suitable for mechatronic products or systems is proposed to identify failure modes from the perspective of motion, in which the fundamental and minimum motion is garnered and named as meta-action with two kinds that are translation and rotation meta-actions. Six basic failure modes are identified in light of the output properties of the meta-action whether meets its requirement or not, which encompass no action, speed insufficient, speed excessive, position insufficient, position excessive and fluctuation excessive.…”
Section: Introductionmentioning
confidence: 99%
“…The initial task in FMEA is to identify failure modes, but many studies do not include this step but implement only risk assessment. However, failure modes in mechatronic systems are usually confused with failure causes, thanks to not strict demarcation between failure mode and failure cause 33 . Therefore, a function–motion–action (FMA) decomposition method extraordinarily suitable for mechatronic products or systems is proposed to identify failure modes from the perspective of motion, in which the fundamental and minimum motion is garnered and named as meta‐action with two kinds that are translation and rotation meta‐actions.…”
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.
“…It is more reasonable and effective for reliability analysis and reliability allocation of electromechanical products. 33,60 With regard to CNC machine tools, they are typical electromechanical products and integrate multiply techniques to accomplish the desired functions. Through implementing the FMA decomposition method to CNC machine tools, we could obtain substantial meta-action units.…”
“…However, failure modes in mechatronic systems are usually confused with failure causes, thanks to not strict demarcation between failure mode and failure cause. 33 Therefore, a function-motion-action (FMA) decomposition method extraordinarily suitable for mechatronic products or systems is proposed to identify failure modes from the perspective of motion, in which the fundamental and minimum motion is garnered and named as meta-action with two kinds that are translation and rotation meta-actions. Six basic failure modes are identified in light of the output properties of the meta-action whether meets its requirement or not, which encompass no action, speed insufficient, speed excessive, position insufficient, position excessive and fluctuation excessive.…”
Section: Introductionmentioning
confidence: 99%
“…The initial task in FMEA is to identify failure modes, but many studies do not include this step but implement only risk assessment. However, failure modes in mechatronic systems are usually confused with failure causes, thanks to not strict demarcation between failure mode and failure cause 33 . Therefore, a function–motion–action (FMA) decomposition method extraordinarily suitable for mechatronic products or systems is proposed to identify failure modes from the perspective of motion, in which the fundamental and minimum motion is garnered and named as meta‐action with two kinds that are translation and rotation meta‐actions.…”
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.
“…Li et al [31] studied the error propagation mechanism of the meta-action assembly unit. Yu et al [32] proposed a novel definition of failure mode for mechanical systems based on meta-action. Li et al [33] studied the reliability and modal of the key meta-action in computerized numerical control (CNC) machine tool.…”
Fault analysis activity is very important for a flexible manufacturing cell (FMC) in the development phase. Fault tree analysis (FTA) and fault mode and effects analysis (FMEA) are widely used for fault analysis. However, they are time-consuming and expensive when fully implemented. In this paper, we propose an improving hybrid multilevel FTA-FMEA method that is the combination of the above two methods. The proposed method has a clear three-layer analysis structure. In the first layer, a system FTA of the FMC is performed to determine the functional fault modes. Then, FMEA is conducted to examine them and the key functional fault modes are selected by criticality analysis. In the second layer, we perform the FTA of the determined key functional fault modes to find out the meta-action/component fault modes. The bottom events of fault trees in this layer show differences due to the subsystems with different features. Same as the first layer, FMEA is conducted subsequently and criticality analysis is also used to determine the key meta-action/component fault modes. In the last layer, we perform the FTA of the determined key meta-action/component fault modes to find out fault causes. Then, the key fault causes are determined by criticality analysis. Risk priority number (RPN) is usually used to determine the priority ranking in criticality analysis, while its calculation way is slightly naïve. In this paper, we use the technique for order preference by similarity to ideal solution (TOPSIS) method to examine the priority ranking of fault modes/causes. Moreover, we consider the correction cost as the fourth indicator to assess the priority. The improving fault analysis method can not only help designers better understand the new FMC but also help decision makers make better decisions. At last, a real FMC as a case is presented to illustrate the proposed method. INDEX TERMS Flexible manufacturing cell, fault analysis, FTA-FMEA, TOPSIS, meta-action.
“…The force and motion relationship between all relevant parts is established by the MA. In this paper, a unit that is relatively independent in structure and achieves certain action goals that are controllable and need not (cannot) be subdivided is called an MA [25]. If a machine center is to achieve various part processing procedures, the B-axis worktable must be able to lift and rotate positively.…”
Section: A Structural Decomposition Model Based On Mamentioning
Cascading faults of computer numerical control machine tools will lead to frequent machine faults, but an effective fault analysis and control strategy can significantly reduce the frequency of such cascading faults. The numerous studies have focused on faulty parts using established fault diagnosis models centered on faulty parts and developed measures for controlling machine tool reliability from the parts' perspective. However, the internal parts of machine tools are strongly coupled, and when one part or assembly begins operating abnormally, it can easily initiate the abnormal operation of other parts or the entire assembly, which can lead to failures. Thus, a fault diagnosis method that considers only individual faulty parts ignores the problem of fault propagation between parts, which may lead to failure to locate the root cause. To address this problem, this paper proposes a cascading fault analysis and control strategy based on meta action. First, the functional components are decomposed into meta actions using the ''function-motion-action'' principle. Second, the directed edges and hierarchical digraph of meta action fault propagation are obtained. Third, the PageRank algorithm is used to calculate the fault propagation impact degree of each directed edge, and the key paths of meta action fault propagation are extracted based on the hierarchical digraph and the impact degree. Finally, the fault tree analysis method is applied to analyze the meta action on key paths, and feasible machine control measures are developed. The feasibility and effectiveness of the method are demonstrated using an example machining center.
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