Reliability allocation of mechanical transmission system considering motion accuracy stability and G-RCF model

Defect detection and signal processing for cast stainless steel: Shankar, R., Selby, G. and Jeong, P. Int. J. Pressure Vessels Piping 1988 35, (1–4), 57–72

Stressing and service life of highly pre-stressed bolted joints: Kloos, K.H. and Schneider, W. Mater. wiss. Werkst. tech. Nov. 1988 19, (11), 349–355 (in German)

Increasing speed of warships

Integrated allocation of warship reliability and maintainability based on top-level parameters

Steel castings — a solution to frabrication problems: Marston, G.J. Steel Technol. Int. 1988 253–256

Chapter 4 - Review on mechanical system reliability models

Reliability allocation method based on minimizing implementation risk

The traditional mechanical transmission system motion accuracy allocation process has the following problems: the error modeling process can not reflect the error formation mechanism of the system, and the influence of maintenance costs and the motion accuracy robustness of the system are ignored in the process of establishing the optimal allocation model of motion accuracy. In this paper, firstly, meta-action theory is introduced and the meta-action unit is taken as the basic analysis unit, the error modeling of mechanical transmission systems is studied, and the formation mechanism of the motion error is correctly analyzed. Secondly, the comprehensive cost of a mechanical transmission system, considering the part manufacturing cost, assembly cost and maintenance cost per unit, is accurately evaluated using the multi-criteria decision-making (MCDM) method. Thirdly, based on the motion error model, a robust model for system motion accuracy is obtained by analyzing the sensitivity of each motion pair. Then, a multi-objective optimal allocation model of motion accuracy is established. The model is solved by an intelligent algorithm to obtain the Pareto non-dominated solution set, and the optimal solution is selected by the fuzzy set method. Finally, the method described in this paper is illustrated by an engineering example.

Modern mechanical systems are required to have high reliability characteristics. To attain them, it is necessary to take particular care (aside from laboratory and in service reliability examinations) of reliability design from the early development stages of a mechanical system. Reliability design for a new system includes an allocation of reliability to system elements which should meet specified requirements. In order to meet certain technical and economic system requirements, a method has been developed using Lagrange multipliers to determine "the best" reliability allocation from the basis of achieving minimum system cost (CSmin) for a specified system reliability (RS). In addition, this method offers the possibility of achieving maximum system reliability (Rmax) for a specified system cost (CS). This paper presents a reliability allocation method allowing the techno-economic requirements imposed on the system to be satisfied in an appropriate way. The method was developed considering some specific factors in the construction of mechanical systems and the relationship between system cost and reliability. In addition, a procedure was developed which permits the determination of "the best" reliability allocation using the multi-criteria ranking method and compromise programming, where system cost and reliability represent the criteria for choosing "the best" solution. The described allocation model was employed in the reliability allocation for an automotive gearbox.

It is generally believed that the reliability of a mechanical system is determined by its composition. The system operates properly when all of its components do not fail. Based on this assumption, the reliability of the system can be represented by the reliability of its components. A problem arises when applying this hypothesis to a system containing motion mechanisms. There is a phenomenon in motion mechanism that the components do not happen structural failure (we call it “Type I failure”) and joint failure (we call it “Type II failure”), but the function of the mechanism cannot meet the requirements (we call it “Type III failure”). A reliability allocation method, which synthetically considers the composition and Type III failure modes of the motion mechanism, is proposed to solve this problem. A relative dispersion factor is introduced to describe the failure dependence of components and is proposed to calculate the complexity and criticality. A series system reliability allocation model considering three types of failure modes is established. Finally, using an airplane gear door lock mechanism as an example, a comparative analysis of the system reliability allocation results with and without considering Type III failure modes is made. The allocation results show the component reliability value without considering Type III failure modes is less than that when considering them, which will increase the system hazards. The result considering Type III failure modes is more reasonable than that from the traditional method.

Mechanical systems is vulnerable to be influenced of its structure and human factors for its subsystems, components and the complex relationship between each unit, causing the mechanical systems to be failed, which severely affects the reliability of the mechanical systems. based on Petri nets models of mechanical systems analysis, from safety, intermediate and failure three aspects, 3-level working model of “safety-intermediate-failure” is introduced to reflect the reliability (functioning fully) of mechanical systems, intermediary transition between reliable and failure, failure (can not work). Through using the union and intersection operation of stochastic event, and considering the different values of the related failure parameters among basic events which impacts on the reliability of mechanical system, eventually the calculation of mechanical system reliability vector with the intermediate state is established.

One of the important reliability activities in Design for Reliability (DFR) is system reliability allocation at the early product design stage. Usually system reliability is given as a product performance requirement under the normal use condition (e.g., the probability of failure for a 2-year operation should be less than 0.05 with a confidence level of 90%). Complex systems consist of many subsystems, which are developed concurrently and sometimes independently. It would be too late to validate the system reliability until the final system prototype is ready after months or years of development. From a project management point of view, the reliability for each subsystem or sub-function should be examined as early as possible. Therefore, allocating a reasonable reliability requirement to each subsystem and sub-function based on the system reliability requirement is very important. Many reliability allocation approaches can be used, such as the AGREE, weighted, equal reliability, and cost-based methods. Traditional system reliability allocation is conducted on the reliability requirement alone. None of the above existing methods considers allocating the reliability requirement together with a confidence level. In this paper, we will propose a new approach for allocating system reliability together with confidence level to the subsystems. The proposed method can be used for complex systems with serial, parallel, and k-out-of-n configurations.

Purpose This paper focuses on studying the reliability allocation for the railway system, aiming to improve the overall reliability of the railway system and ensure safety operation. Design/methodology/approach In view of the complex structure of the railway system, involving many subsystems, this paper analyzes the close dynamic coupling effect between railway subsystems. Based on this, taking the railway system failure as the top event, a fault tree is constructed in this paper. Then, a reliability allocation method based on the fault tree is employed to allocate the reliability index. Finally, a numerical experiment is implemented to show the performance of the reliability allocation method. Findings The results showed that each subsystem needs to improve its reliability to meet the specified railway system reliability requirements, and the traction power supply system is the most important subsystem, which is the most efficient in improving the reliability of the railway system. Originality/value For the first time, starting from a holistic perspective of the system, reliability allocation is carried out based on the importance of each railway subsystem.

Reliability allocation is a very important problem during early design and development phases of a system. There are several reliability allocation techniques which are used to achieve the target reliability. The feasibility of objectives (FOO) technique is one of them that is widely used to perform system reliability allocation. But this technique has two fundamental shortcomings. The first is the measurement scale and the second is that it does not consider the order weight of the reliability allocation factors. The prioritization of the factors is also an important topic in decision making. Practically, all factors in multi-criteria decision making (MCDM) are not in the same priority level. Hence, in decision making situation, it is usual for decision makers to consider different priority factors. So, considering the prioritization of the factors, a reliability allocation method is proposed here to overcome the shortcomings of the FOO technique. Also, a case study on reliability allocation in airborne radar system is considered here to verify the efficiency of the proposed approach. Finally, the results are calculated in different optimistic and pessimistic view point and compared with the FOO technique. This comparison exhibits the advantages and supremacy of the proposed approach.

Reliability allocation is a very important problem during early design and development phases of a system. There are several reliability allocation techniques which are used to achieve the target reliability. The feasibility of objectives (FOO) technique is one of them that is widely used to perform system reliability allocation. But this technique has two fundamental shortcomings. The first is the measurement scale and the second is that it does not consider the order weight of the reliability allocation factors. The prioritization of the factors is also an important topic in decision making. Practically, all factors in multi-criteria decision making (MCDM) are not in the same priority level. Hence, in decision making situation, it is usual for decision makers to consider different priority factors. So, considering the prioritization of the factors, a reliability allocation method is proposed here to overcome the shortcomings of the FOO technique. Also, a case study on reliability allocation in airborne radar system is considered here to verify the efficiency of the proposed approach. Finally, the results are calculated in different optimistic and pessimistic view point and compared with the FOO technique. This comparison exhibits the advantages and supremacy of the proposed approach.