An optimization method of aircraft periodic inspection and maintenance based on the zero-failure data analysis

Author(s):  
Jun Huang ◽  
Yanbo Song ◽  
Yongji Ren ◽  
Qingwei Gao
Author(s):  
Rommel Estores ◽  
Pascal Vercruysse ◽  
Karl Villareal ◽  
Eric Barbian ◽  
Ralph Sanchez ◽  
...  

Abstract The failure analysis community working on highly integrated mixed signal circuitry is entering an era where simultaneously System-On-Chip technologies, denser metallization schemes, on-chip dissipation techniques and intelligent packages are being introduced. These innovations bring a great deal of defect accessibility challenges to the failure analyst. To contend in this era while aiming for higher efficiency and effectiveness, the failure analysis environment must undergo a disruptive evolution. The success or failure of an analysis will be determined by the careful selection of tools, data and techniques in the applied analysis flow. A comprehensive approach is required where hardware, software, data analysis, traditional FA techniques and expertise are complementary combined [1]. This document demonstrates this through the incorporation of advanced scan diagnosis methods in the overall analysis flow for digital functionality failures and supporting the enhanced failure analysis methodology. For the testing and diagnosis of the presented cases, compact but powerful scan test FA Lab hardware with its diagnosis software was used [2]. It can therefore easily be combined with the traditional FA techniques to provide stimulus for dynamic fault localizations [3]. The system combines scan chain information, failure data and layout information into one viewing environment which provides real analysis power for the failure analyst. Comprehensive data analysis is performed to identify failing cells/nets, provide a better overview of the failure and the interactions to isolate the fault further to a smaller area, or to analyze subtle behavior patterns to find and rationalize possible faults that are otherwise not detected. Three sample cases will be discussed in this document to demonstrate specific strengths and advantages of this enhanced FA methodology.


2015 ◽  
Vol 14 (4) ◽  
pp. 109-120 ◽  
Author(s):  
Joseph Al Asmar ◽  
Raed Kouta ◽  
Salah Laghrouche ◽  
Joseph El Assad ◽  
Maxime Wack

Abstract The cogeneration systems in the industrial sector have become an essential part due to their global efficiency and reduced pollution. These systems may operate from conventional fuel sources, as well as from renewable energy sources (biomass, solar, fuel cell). Cogeneration systems could be installed as a distributed generation and on-site generation source in order to take advantage from the produced heat. The utility can motivate factories to install such systems by permitting them to link and sell their residual production capacity to the electrical grid. This work presents a new technique to find the best solution from multi-objective optimization results, using a sensitivity and data analysis method. Genetic Algorithm (GA) optimization method is used with the data analysis method: Multiple Linear Regression (MLR).


2014 ◽  
Vol 615 ◽  
pp. 165-168
Author(s):  
Xing Zheng He

The external anticorrosive coating is the shelter for preventing buried steel pipelines from corrosive damage. Many pipelines face severe corrosive problems because of the performance decrease of the coating, especially during long-term services. This situation usually causes safety accidents. Periodic inspection to the coating is an important way to ensure running safety. Aimed at the detecting technology, the methods for locating the pipelines and the means of on-line defects detecting with no excavation for the coating were studied and introduced. The ways for direction detecting, depth measuring and location coordinates detecting were pointed out. The basic principles of data analysis were also outlined. The various influences coming from external environment factors to the detecting results were analyzed.


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