Reliability Optimization Models for Embedded Systems With Multiple Applications

2004 ◽  
Vol 53 (3) ◽  
pp. 406-416 ◽  
Author(s):  
N. Wattanapongsakorn ◽  
S.P. Levitan
Author(s):  
Chengwei Fei ◽  
Wenzhong Tang ◽  
Guangchen Bai

To improve the performance and reliability of gas turbine like an aeroengine, the multi-object multi-discipline (MOMD) reliability optimization design of high press turbine (HPT) blade-tip radial running clearance (BTRRC) was first accomplished based on the mechanical dynamic assembly reliability (MDAR) theory and distributed collaborative response surface method (DCRSM). Four optimization models of MDAR were developed based on the features of assembly machinery and the thought of DCRSM, which are, respectively, called as the direct reliability optimization model (denoted by M1), the multilayer reliability optimization models (denoted by M2), the direct reliability optimization model-based probabilistic analysis (denoted by M3), and the multilayer reliability optimization model-based probabilistic analysis (denoted by M4). Through the MDAR optimization design of BTRRC by the four standard optimization models, some conclusions are drawn as follows: (1) the DCRSM is proved to be effective and feasible for MOMD MDAR optimization design with high computational efficiency and precision; (2) all the reliability optimization results of BTRRC and assembly objects satisfy the requirements of optimization design, and the optimized BTTRC variations are reduced by about 10% and obey the normal distribution, which are quite promising in improving the design and control of HPT BTRRC; (3) in computational efficiency, the computing time of M1 and M3 is far less than those of M2 and M4, meanwhile M3 and M4 are superior to M1 and M2; (4) in computational accuracy, M1 and M2 are better than M3 and M4, as well as M2 and M4 are higher than M1 and M3 theoretically. The presented study does not only fulfill the HPT BTRRC dynamic assembly design from a probabilistic optimization perspective and improve the performance and reliability of gas turbine engine, but also provides a promising approach and four valuable optimization models for MDAR optimization design. Besides, the present efforts are of great significance in enriching the theory and method of mechanical reliability design.


In the article, the author considers the problems of complex algorithmization and systematization of approaches to optimizing the work plans of construction organizations (calendar plans) using various modern tools, including, for example, evolutionary algorithms for "conscious" enumeration of options for solving a target function from an array of possible constraints for a given nomenclature. Various typical schemes for modeling the processes of distribution of labor resources between objects of the production program are given, taking into account the array of source data. This data includes the possibility of using the material and technical supply base (delivery, storage, packaging) as a temporary container for placing the labor resource in case of released capacity, quantitative and qualification composition of the initial labor resource, the properties of the construction organization as a counterparty in the contract system with the customer of construction and installation works etc. A conceptual algorithm is formed that is the basis of the software package for operational harmonization of the production program ( work plans) in accordance with the loading of production units, the released capacities of labor resources and other conditions stipulated by the model. The application of the proposed algorithm is most convenient for a set of objects, which determines the relevance of its implementation in optimization models when planning production programs of building organizations that contain several objects distributed over a time scale.


2012 ◽  
Vol 1 (5) ◽  
pp. 115-117
Author(s):  
Jahnavi KRM Jahnavi KRM ◽  
◽  
Raghavendra Rao K ◽  
Padma Suvarna R

2019 ◽  
Vol 139 (7) ◽  
pp. 802-811
Author(s):  
Kenta Fujimoto ◽  
Shingo Oidate ◽  
Yuhei Yabuta ◽  
Atsuyuki Takahashi ◽  
Takuya Yamasaki ◽  
...  

2013 ◽  
Vol 133 (2) ◽  
pp. 111-115 ◽  
Author(s):  
Takashi Anezaki ◽  
Suriyon Tansuriyavong ◽  
Chikatoshi Yamada
Keyword(s):  

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