In view of the fact that there is no comprehensive evaluation parameter of support equipment allocation efficiency, in this paper, we had a comprehensive consideration of the mean logistic delay time and the annual consumption cost of support equipment, and analyzed and constructed the optimization model of allocation efficiency from the perspective of cost-effectiveness with the constraint of satisfaction and utilization rate of support equipment. An improved genetic algorithm was used to solve this model, finally, a set of optimal allocation concept of equipment was obtained.
There is a growing concern about correlation analysis of natural environment test and laboratory accelerated test, especially test about corrosion of metal, nonmetal and coatings. This paper will concentrate on correlation analysis from simulation ability, accelerating ability and reproducibility. As an illustration, exposure test in marine atmospheric environment and salt spray test in laboratory of Parylene C coating were performed. And conclusions were reached that there was satisfactory correlation between these two tests and accelerated ratio was also gained.
Cable layout is an important part in the design of aviation equipment. Most of the cables are set within the narrow space of fuselage, the electrical environment and the spatial structure are complex, however, the traditional design process mainly focus on the physical properties of the cable itself without taking the maintainability especially the accessibility into consideration. In order to solve this problem, we first put forwards a cable layout design optimization model by converting basic constraints to weights of points in space through taking pretreatment (layering, rasterizing, digitalizing) in wiring space and confirming quantitative constraint conditions of accessibility based on visual cone volume of maintenance point and collisionless space volume. Then in the solving of the model, an improved A * algorithm is adopted and an optimized path of the cable is figured out. We use DELMIA to carry out 3D modeling to achieve the cable layout design and optimized the layout result based on its accessibility analysis module. In the end, we make a case study on cable layout optimization of an equipment compartment and verify the feasibility of the method, at the same time, propose a new and practicable optimization method for the design work of cable layout for aviation equipment.
The problem which is paid attention in this paper is that existing physics-of-failure model cannot input and calculate complex multi-level stress environmental profile when making simulating calculation of microelectronic devices' using reliability. A physical model for electro-migration failure is analyzed as an example. We make cumulative calculation and improvement using theory of accelerated factor, and the general function of physics-of-failure model for electro-migration damage accumulation under multi-level stress profile is set up. This model can achieve simulation and prediction of cycle time before failure under multi-level stress profile. At the end of this paper, an instance of multi-level stress profile's calculation is provided.
The article presents a new method for predicting the reliability of the automobile starter using the AgenaRisk program and experimental research. The program allows to forecast the health status of the starter and provide service intervals of its technical condition. Simulation studies for selected faults in the electrical and mechanical circuits of the starter allowed to carry out an analysis of the parameters defining the technical condition of the starter. The scientific aim of the article was to develop and validate a diagnostic method designed for the operational monitoring of the startup circuit of a car. The aim of the experiment was to forecast the state of reliability of elements of the starter system, with the possibility of using the OBD (On-Board Diagnosis).
Condition based maintenance (CBM) is a practical and effective way to guarantee the product availability. Recent years the optimization strategy of CBM is widely studied by researchers. For product with measurable degradation performance, degradation modeling plays an important role in CBM. Inverse Gaussian process has many superb properties in dealing with covariates and random effect. In this paper, a new CBM optimization model is developed basing on the nonlinear inverse Gaussian degradation model. With the constraint of cost, the optimal CBM strategy is obtained by maximizing availability of product. Specifically, we consider imperfect preventive maintenance and proposed a way to describe its influence. Finally, the proposed model is demonstrated by a numerical example.
Different kinds of maintenance events in practical maintenance have different effects on equipment operation and task success. Based on the characteristics of multiple events and uncertainties of maintenance events, this paper analyzes the influence of various maintenance events on maintenance cost decision under different maintenance times, and determines the influencing factors of maintenance cost decision and constructs the influence of various maintenance events model. According to the correlation effect model of multi - event combination, the decision-making model of multi-maintenance event is constructed.
Virtual maintenance based on virtual reality has been developed recent years, yet the relation between qualitative analysis and quantitative analysis has not been built. In this paper, a calculation method of operational domain of virtual maintenance based on convex hull algorithm is proposed. First, a hierarchical skeleton mathematical model based on the physiological characteristics of human skeletal structure is given to digitalize the virtual human body. Second, the motion equation of human posture is built based on the model of skeleton joint chain and the offset matrix of default skeleton posture. Finally, convex hull algorithm is used to calculate the operational domain of virtual maintenance. The proposed method is validated using realtime data collected by the Noitom's motion-capturing device. The experiment result has testified the method can provide an effectively quantitative analysis for operational domain of virtual maintenance.
Considering that the physical demonstration is difficult to implement in the real test experiment, and the complete simulation verification is difficult to satisfy the requirement. This paper designs a semi-physical demonstration system based on LabVIEW and MATLAB, and realizes the synchronous diagnosis of the state graph simulation model and hardware. The design principle of the slave computer and the host computer is introduced in detail. The embedded diagnosis semi-physical system of typical avionics is taken as an example to partly implement the demonstration system, and the result proves the applicability and effectiveness.
Industrial robots are being widely used attributed to their flexibility, repeatability, and accuracy. The reliability of industrial robots are becoming more highlighted. Over-year evidence clearly indicates that the reliability of industrial robots has had a big improvement, not only by the more reliable hardware design, but also by collecting and analyzing the failure data in fields over a long period of time. The database for the assessment of RAMS (Reliability, Availability, Maintainability and Safety) has been, therefore, paramount to industrial robot designers and manufactures. A common database for industrial robots is not a new idea. Normally, the industrial robot manufacturers retain the detailed data about faults and other incidents retained by through after-service. However, the current databases are far from satisfactory as they are not clear regarding how they will address the RAMS requirements. In this paper, the needs and expectations of the RAMS database for the industrial robots are stated. The potential technical challenges to be faced during the realization of this database are carefully discussed. It is expected that the realization of the RAMS database could bring a further improvement ranging from design, to operation and maintenance.
The assembling process is the final production step, its quality is the decisive factor of the reliability of the finished product. Along with the release of ISO 9001: 2015, the risk of thinking is firstly cited, and the risk oriented quality analysis should be extended to the assembling process. Therefore, in order to improve the reliability of the final product, the risk thinking is needed to be introduced into the management and analysis of the assembling quality. Therefore, based on the proposed RQR chain, a reliability oriented quality risk analysis method is presented for the product assembling process. Firstly, the RQR assembling chain is introduced in this paper, and its three basic management objects of system reliability (R), assembling process quality (Q) and product reliability (R) are expounded. Secondly, based on the co-effect in the RQR chain, a quality framework of risk control is put forward. Thirdly, the impact of noncritical quality characteristic variations on key quality characteristics (KQC) is analyzed, and then the decline degree of the assembling product reliability caused by the KQCs variation is quantified. Then, according to the impact of the proportion, the risk factor K is determined, and then the quantitative relationship between assembling variation and product quality accident risk is established. Finally, a quality risk analysis case of a lifting equipment assembling process is given to verify the availability of the approach.
To make better use of resources and achieve the highest benefits, the reliability and inspection strategy of the subsea gas boosting system are proposed in this paper. First, the operation modes and phases of the system were analyzed to establish the state transition chart accurately. On this base, the Markov model of the system with five state was established to depict the imperfect test effect and to get the steady-state reliability indexes of the system and the expression of steady-state probability of each state. Then, the failure rate was calculated using reliability predict method and the repairing rate was determined from experience and statistic data. Finally, system cost was calculated to determine the optimal inspection strategy and comparison was made to show the improvement of the system economic effectiveness.
This paper introduces a modified methodology on basis of the RULA (Rapid Upper Limb Assessment) to assess the astronaut ergonomics for space flight in microgravity environment. The proposed methodology under the combination of the neutral configuration in microgravity with the joint movement ranges to establish the assessment criterion for the modified RULA methodology to assess the ergonomics in the microgravity environment.
Products arranged in the same zone usually have some spatial correlation, function relation and the impact of environmental stress, which usually causes coupling effect with other products in the same zone. This kind of coupling effect affects products' quality, and may influence the veracity and comprehensiveness of the quality analysis. To solve this issue, starting from changing the traditional characteristics-based analysis method, proceeding with the different type of zonal events, this paper proposes a logical decision method based on the active event to analyze the association effect between regional products, and obtains bad coupling on several important quality characteristics such as product function, reliability, maintainability, guarantee ability and testing. Also discover the impacts of the bad coupling on the specific quality characteristics. Through the most critical impact of the coupling events and the highest correlated products found by the logical decision-making process, it could use as a reference for improving the products design.
The Tactical Missile is a complex system with a large number of components, with characteristics of high reliability, long storage life. Due to the limitation of the samples of the missile, the traditional method of modeling and evaluating based on mathematical statistics has a lot of shortcomings. Therefore, according to the Bayesian network method, we use the principle of physics of failure analysis to establish the assessment model from the components to the system. The work of the paper mainly includes the following contents. First, the failure modes and the sensitive environmental stress are qualitatively and quantitatively analyzed to determine the main influencing factors of the system failure at work. Second, according to the system function to establish the system function flow chart, the data is divided into different styles based on the physics of failure. According to the test results, the likelihood function is established. Third, based on the Bayesian network and combined with the system function, the paper establishes the qualitative and quantitative Bayesian network model from the component to the system, from the bottom node to the high node. According to the test data, the evaluation and verification of the system life parameters are carried out.
Based on the study of advantages and disadvantages of the traditional AR model (autoregressive model) and the characteristics of failure rate prediction, an AR model based on neural network residual correction is proposed in this paper. The basic idea is to establish the AR model first to obtain the residual sequence, and next construct the neural network residual prediction model using the residual sequence, and then correct the predicted value of the original AR model using the residual value predicted by the model. The combined model is used to predict the failure rate of a kind of Boeing aircraft. It is proved that this model is suitable for short-term failure rate prediction, and the accuracy of the prediction results is better than that of the single AR model.
Resilience test and evaluation is an important technology to evaluate system resilience and verify whether the value of system resilience meets the designated requirements before the system is used. In this study, a resilience test and evaluation process is proposed for given disturbances. The system resilience is defined by the ratio of the integral of the normalized system performance within its maximum allowed recovery time after the disturbance to the integral of the performance in the normal state, and an approximate method is developed to assess the system resilience based on the discrete monitoring data. To illustrate the effectiveness of our proposed method, the resilience of a DC servo motor is evaluated based on the performance simulation on Simulink/TrueTime.
The traditional reliability assessment method only considers the product under the condition of constant environmental stress. However, the products are often actually exposed to the real world environmental stress. Aiming to solve this problem, the real world environmental stress of the typical geographical location is introduced, and the five-parameter polynomial fitting method is used to deal with its historical climate data and get the variation tendency of temperature and humidity. Based on the Nelson cumulative damage model and generalized Eyring model, the product reliability assessment method under real world environmental stress is studied. Compared with the traditional reliability assessment method under constant environmental stress, the reliability assessment method under real world environmental stress is more accurate.
Determining the failure propagation paths is always an important content of safety analysis. The traditional safety analysis methods are hard to deal with large complex systems. Therefore, model-based safety analysis (MBSA) becomes increasingly popular. However, the existing modeling methodologies are mainly modeled from one of the following three aspects, function, structure and state. This lacking of unified modeling results in low degree of information integration between models and it is prone to lose information between the conversions of different types of models. D-higraph is a new modeling formalism to capture structure as well as functionality of a system. This paper proposes a failure propagation analysis method based on D-higraph.
Mission failure evolution is a unique aspect of complex human-machine system (CHMS), which contains failure regularity and directs emergent reconfiguration measures. Oriented to all varieties of system components, an analysis of how the parts are connected and contribute to CHMS failure is necessary. Prior work paid more attention to system design with the law of system normal operation, where a single function failure was identified positively and its consequence was analyzed to guarantee reliability and safety. In this paper, a normally operational CHMS process is divided into three layers which contains task, element and capacity as well as the conceptions of Basic Task Space (BTS) and Repair Task Space (RTS). The measurement method of these three aspects was defined. Furthermore, CHMS failure measurement will be presented with the parameters of capacity deviation. Taking multiple elements coordination and self-organization into consideration, a multi-agent based simulation approach of system failure evolution path is proposed. This method is demonstrated with the nuclear power system intending to interpret how the system fails to deal with all possible disturbance. Obvious results show that the multiple failure paths can be obtained, from which the writer provides some constructive comments for system design.
