Reliability Optimization Allocation Method for Multifunction Systems With Multistate Units Based on Goal-Oriented Methodology

2017 ◽  
Vol 3 (4) ◽  
Author(s):  
Xiao-jian Yi ◽  
B. S. Dhillon ◽  
Jian Shi ◽  
Hai-na Mu ◽  
Peng Hou
Keyword(s):  
Reliability Optimization ◽  
Allocation Model ◽  
New Approach ◽  
Reliability Indices ◽  
Analysis Process ◽  
Allocation Method ◽  
Power Shift ◽  
Go Model ◽  
Go Methodology ◽  
Optimization Allocation

This paper proposes a new reliability optimization allocation for multifunction systems with multistate units based on goal-oriented (GO) methodology. First, this optimization allocation method is expounded in terms of establishing GO model, establishing reliability optimization allocation model, and solving algorithm. Then its process is formulated. Finally, the new method is applied in reliability optimization allocation of power-shift steering transmission (PSST), whose goal is to minimize the system cost. The results analysis shows that the system costs for different operation times turn to a relatively stable value, and the allocated reliability indices of unit are satisfied with engineering requirements. All in all, this new optimization allocation method can not only obtain the reasonable allocation results quickly and effectively, but it also can overcome the disadvantages of existing reliability optimization allocation methods for complex multifunction systems efficiently. In addition, the analysis process shows that the reliability optimization allocation method based on GO method can provide a new approach for the reliability optimization allocation of multifunction systems with multistate units.

A New Reliability Optimization Allocation Method for Nuclear Power Systems Based on Goal Oriented Methodology

2017 ◽  
Author(s):  
Yi Xiao-jian ◽  
Xie Yong-cheng ◽  
Shi Jian ◽  
Mu Hui-na ◽  
Hou Peng
Keyword(s):  
Power Systems ◽  
System Reliability ◽  
Nuclear Power ◽  
System Analysis ◽  
Mathematic Model ◽  
Reliability Optimization ◽  
New Approach ◽  
Allocation Method ◽  
Go Model ◽  
Optimization Allocation

This paper presents a new reliability optimization allocation method for complex nuclear power systems based on Goal Oriented (GO) method, whose goal is to minimize the system cost. First, the new reliability optimization allocation method is expounded in detail. And its process is formulated. Then, the hoisting mechanism in nuclear power plant is taken as an example to allocate its system reliability index to design unit by the new method. The reliability optimization allocation processes are mainly as follows: (i) Conducting system analysis, (ii) Developing GO model, (iii) Establishing reliability optimization allocation mathematic model, (iv) Solving the reliability optimization allocation mathematic model, (v) Determining the allocation results. The results analysis shows that the system costs for different solving times turn to a relatively stable value, and the allocated reliability indexes of unit are satisfied with engineering requirements. All in all, this new reliability optimization allocation method can not only obtain the reasonable allocation results quickly and effectively, but it also can overcome the disadvantages of existing reliability optimization allocation methods for complex nuclear power systems efficiently. Moreover, this paper provides a new approach for the reliability optimization allocation of complex nuclear power systems.

A reliability optimization allocation method for the hydraulic system of CNC honing machine considering the operating condition information

2017 ◽  
Vol 232 (12) ◽  
pp. 2244-2264 ◽  
Author(s):  
Guanghui Zhou ◽  
Fengtian Chang ◽  
Changle Tian ◽  
Qi Lu
Keyword(s):  
Complex System ◽  
Complex Systems ◽  
Hydraulic System ◽  
Reliability Optimization ◽  
Hydraulic Systems ◽  
Allocation Model ◽  
Operating Condition ◽  
Allocation Method ◽  
Target Cascading ◽  
Optimization Allocation

In recent years, reliability optimization allocation has drawn a broad spectrum of attentions, especially for complex systems consisting of a large number of subsystems and components. Hydraulic system, deemed as a complex system, plays a great role in reliability increment of the CNC honing machine. In order to realize the CNC honing machine tool’s balanced operating performance, the crucial hydraulic system is designed to obtain the optimal and well-balanced allocation solution under the constrains of cost and reliability. Meanwhile, the quantified operating factor that influences the allocation solution is rarely considered adequately when operating samples are insufficient. So, if hydraulic systems are used in a new required longer operating mission duration or a new severer operating environment, the dissatisfied reliability could not be better reallocated to adapt to this environment with appropriate methods. Aimed at overcoming the abovementioned shortcomings and optimizing the dissatisfied reliability for existing hydraulic systems, this paper proposes a reliability optimization allocation method considering operating the condition information. From the standpoint of the complex system, this method firstly builds a three-level reliability optimization allocation model based on the analytic target cascading for the specific hydraulic system of CNC honing machine 2MK2263 × 200. It transforms the complex reliability allocation problem to a set of smaller and coordinated optimization sub-problems. Secondly, through studying the operating reliability problems of small samples in the new operating scene, the reliability prediction results based on the operating condition information are applied to build the initial reliability targets, which are regarded as the initial constrains for the optimization. With the help of analytic target cascading model and initial target reliability, the optimal reliability for the complex hydraulic system would be obtained. It is also shown to provide an innovative route for the reliability redesign of the related complex systems for this new required operating scene.

Reliability Analysis of Repairable System With Multiple-Input and Multi-Function Component Based on Goal-Oriented Methodology

2016 ◽  
Vol 3 (1) ◽  
Author(s):  
Xiao-Jian Yi ◽  
Jian Shi ◽  
Hui-Na Mu ◽  
Hai-Ping Dong ◽  
Zhong Zhang
Keyword(s):  
Reliability Analysis ◽  
Fault Tree Analysis ◽  
Repairable Systems ◽  
New Approach ◽  
Availability Analysis ◽  
Analysis Process ◽  
Power Shift ◽  
Comparison Results ◽  
Multiple Input ◽  
First Time

This paper proposes a new goal-oriented (GO) method for reliability analysis of repairable systems with multiple-input and multi-function component (MIMFC). First, a new GO operator combination, which is composed of a new function GO operator and a new auxiliary GO operator, is created to represent MIMFC. The new function GO operator named as Type 22 operator is created to represent MIMFC itself, and the auxiliary GO operator named as Type 15B operator is created to represent multi-condition control signals of MIMFC. Then, GO operation formulas of the new GO operator combination are deduced based on logical relationships among inputs, outputs, and the component itself. The reliability analysis process of the new GO method is formulated. Furthermore, this new GO method is applied for the first time in steady availability analysis and qualitative analysis of the fan drive system of a power-shift steering transmission. Finally, the results obtained by the new GO method are compared with the results of fault tree analysis (FTA) and Monte Carlo simulation (MCS), and the comparison results show that this new GO method is reasonable and advantageous in reliability analysis of repairable systems with MIMFC. Moreover, the analysis process shows that it is more advantageous in the aspect of building system models and conducting reliability analysis. Overall, this paper not only improves the basic theory of the GO method and expands the application of the GO method, but it also provides a new approach for reliability analysis of repairable systems with MIMFC.

Reliability Optimization Allocation Method for Multifunction Systems Based on Goal Oriented Methodology

2016 ◽  
Author(s):  
Xiaojian Yi ◽  
B. S. Dhillon ◽  
Jian Shi ◽  
Hui-na Mu ◽  
Peng Hou
Keyword(s):  
System Reliability ◽  
Reliability Index ◽  
Mathematic Model ◽  
Allocation Problem ◽  
Reliability Optimization ◽  
Constraint Function ◽  
System Cost ◽  
Allocation Method ◽  
Reliability Constraint ◽  
Optimization Allocation

This paper proposes a new reliability optimization allocation for multifunction systems based on GO methodology. First, two constraints functions are proposed, which are unit reliability constraint function and system reliability constraint function, respectively. The unit reliability constraint function consists of allocated reliability index of unit and the range of reliability index for unit. And the system reliability constraint function consists of the target reliability index of system, and the predicted reliability index of system obtained by using GO method and allocated reliability index of unit. Then, the objective function of optimization allocation problem is established to describe the system cost minimization taking into consideration costs of unit redesigned and unit selected versions. Based on above, the mathematic model of reliability optimization allocation problem for complex multifunction systems is established. In addition, an improved genetic algorithm is presented to solve this mathematic model. Furthermore, the process of the new reliability optimization allocation method for complex multifunction systems is formulated. Finally, the new method is applied in reliability optimization allocation of Power-shift Steering Transmission whose goal is to minimize the system cost. The results analysis shows that the system costs for different operation times turn to a relatively stable value, and the allocated reliability indexes of unit are satisfied with engineering requirements. All in all, this new optimization allocation method can not only obtain the reasonable allocation results quickly and effectively, but it also can overcome the disadvantages of existing reliability optimization allocation methods for complex multifunction systems efficiently. In addition, the analysis process shows that the reliability optimization allocation method based on GO method can provide a new approach for the reliability optimization allocation of multifunction systems.

A Reliability Optimization Allocation Method Considering Differentiation of Functions

2016 ◽  
Vol 13 (04) ◽  
pp. 1641020 ◽  
Author(s):  
X. J. Yi ◽  
Y. H. Lai ◽  
H. P. Dong ◽  
P. Hou
Keyword(s):  
Genetic Algorithm ◽  
Optimal Solution ◽  
Reliability Function ◽  
New Method ◽  
Reliability Optimization ◽  
Main Function ◽  
Actual Situation ◽  
Allocation Method ◽  
Importance Factor ◽  
Optimization Allocation

The reliability optimization has achieved great concern in recent years. Nowadays, many researchers obtain allocation results which can maximize the system reliability subject to the system budget. In these researches, the effect of system’s functions is always neglected or only considering the single main function of system. In addition, there are also no obvious evidences in results to distinguish the importance level of different units. However, complex systems tend to perform multiple functions. What’s more, the use frequency of each function and the combinations of units to realize different functions are not the same. In addition, the use demand of different functions is decided by different task environments, the demand differentiation of functions has led to the usage of frequency of various functions having different levels about reliability. Therefore, the reliability optimization allocation only considering cost constraint conditions is not accurate and will results in disaccord between the obtained results with actual situation. Focusing on the problem mentioned above, a reliability optimization allocation method that considers cost constraint and importance factor is proposed. In this paper, we consider systems consisting of units characterized by different reliability and importance factors. Such systems are multi-function because they must perform different tasks depending on the combination of units. Different functions may work simultaneously. Firstly, the concept of importance factor is defined to describe the importance of a unit and the required importance factor level of system functions in the task is also given. To deal with the differentiation of system functions, the corresponding bound about importance factor are executed when looking for the optimal solution. Similarly, the cost constraint is also forced. Finally, in order to reduce the randomness of intelligent algorithm, a number of optimization are conducted and a rule is proposed to select the most optimal solution from all the optimal solutions which are obtained in every iterative loop. Example of an integrated transmission device is presented. To begin with, we establish the reliability function of system as the objective optimization function. Then, the restraint of budget and different demands of importance factor of system functions are posed. Furthermore, using a genetic algorithm as the optimization tool, the optimization result can be obtained. Finally, the most optimal solution is selected. The results show that, the method, we proposed is more correct and more approximate than the reality. To verify the advantages and engineering applicability of the new method, the results obtained by the new method are compared with the results obtained under different conditions using basic genetic algorithm, without considering functions and the differentiation of functions, to solve the allocation problem of integrated transmission device, respectively. The reliability optimization allocation method presented in this paper can not only consider the constraint of cost but also can consider the diversities of functions, and thus the optimization results will be more approximate in actual situation. At the same time, this paper can also provide guidance for the similar reliability optimization problem.

scholarly journals Allocating Water Environmental Capacity to Meet Water Quality Control by Considering Both Point and Non-Point Source Pollution Using a Mathematical Model: Tidal River Network Case Study

Water ◽  
2019 ◽  
Vol 11 (5) ◽  
pp. 900 ◽  
Author(s):  
Lina Chen ◽  
Longxi Han ◽  
Hong Ling ◽  
Junfeng Wu ◽  
Junyi Tan ◽  
...  
Keyword(s):  
Water Quality ◽  
Nonlinear Optimization ◽  
Total Phosphorus ◽  
Compliance Rate ◽  
Ammonia Nitrogen ◽  
Tidal River ◽  
Allocation Model ◽  
Allocation Method ◽  
Control Section ◽  
Optimization Allocation

Based on the principles of fairness and feasibility, a nonlinear optimization allocation method for pollutants was developed based on controlled section water quality standards, considering the synergetic influence of point and surface sources. The maximum allowable emission of pollutants from point and surface sources were taken as the objective function. The water quality attainment rate of controlled sections, the control requirements of pollution sources, and technical parameters of pollution control engineering were taken as constraints. A nonlinear optimization allocation model was established, and a genetic algorithm was used to solve the problem. As an example, the model was applied to a certain area in the Taihu Lake basin, southern Jiangsu province, China. The analysis results showed that the annual number of days for ammonia-nitrogen and total phosphorus meeting the standard were 334 and 332 days, respectively, under maximum allowable emissions for each pollutant, and the water quality compliance rates of the control section were 91.5% and 91%, respectively. The ammonia-nitrogen and total phosphorus concentrations in the controlled section achieved related water quality compliance rate targets of 90%. These all met the water quality compliance rate requirements of the control section. The results indicate that this method reflects the feasibility of optimizing the total allocation results systematically and intuitively, overcomes the insufficiency in the feasibility of the optimized allocation method, and provides effective and reliable technical support for control and management of the total pollutant amount based on water quality improvement.

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