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Editorial

Volume 12, Number 1, January 2016 - Editorial - p 1

KRISHNA B MISRA



This is the first issue of the year 2016 and it is also the last issue under my editorship of International Journal of Performability Engineering which was being published for last 11 years under the ownership of RAMS Consultants. On request from Professor Wong, I agreed to edit this issue under the new ownership of IJPE. As you know by now that the ownership of IJPE has changed from RAMS Consultants, India to Totem Publisher, Inc., U.S.A. and IJPE will continue to be published from USA covering the areas of Quality, Reliability, Maintainability/Maintenance, Safety and Risk and Sustainability from January 01, 2016 under the ownership of Totem Publisher Inc., From January 01, 2016, this journal will have two Co-Editor-in-Chiefs, namely, Dr. Dianxiang Xu, Professor & Graduate Coordinator of the Department of Computer Science at Boise State University, USA (http://cs.boisestate.edu/~dxu/), and Dr. V.N.A. Naikan, - Professor and Head of the Reliability Engineering Center at IIT Kharagpur, India (naikan@hijli.iitkgp.ernet.in). The Editor for Short Communication shall also remain unchanged. I like to formally introduce the new Co-Editors-in-Chief and the Editor for Short Communications on the next page of this issue (page 2).The Editorial Board shall remain unchanged at least for next three years. I am sure the IJPE would continue to flourish under the leadership of these people and will be printed and published timely with excellence in the years to come.  I wish the new Editorial team of IJPE and the IJPE unprecedented success in fulfilling the tasks that are on the anvil and take great strides towards the success of unfinished tasks connected with the objectives for which the International Journal of Performability Engineering was launched in July 2005.

In this issue 7 papers included are from different areas of performability engineering. The first paper is on prognostics in which the authors indicate how to develop accurate and applicable data driven models for tool wear estimation and remaining useful life prediction of high speed Computer Numerical Control (CNC) milling machine cutters. The second paper from University of Maryland reviews how system multi-sensor data can be subjected to Bayesian inference to update the understanding of sub-system and component reliability parameters. It also reviews a methodology on how sensor placement can be optimized with multiple objectives, including the utility of inferred reliability information.  In the third paper, mathematical models of the various components of the boiler-turbine-generation system are developed and a comprehensive virtual model of a steam turbine power generation unit is presented, which can be used to evaluate parameter values at different stages of the plant, and to determine optimized plant parameters and to design controllers for thermal systems. In the fourth paper, the authors have proposed a novel storage location assignment policy for storing items in a warehouse that corresponds to print production environment. The fifth paper uses hierarchical models prioritized as per the users’ requirement to rank the various plans of Cloud Service Providers considering parameters like Agility, Finance, Performance, Security and Usability. These parameters provide a standardized method for measuring and comparing Infrastructure services of cloud providers. A unified trust evaluation framework described helps customers in selecting a most trustworthy cloud provider. The focus of sixth paper related to sustainability is on the evaluation of ATSWM technologies and their potential for enabling State of Florida USA to reach its recycling goal by 2020. This study can also be generalized to other geographical locations that are experiencing problems in, and seeking ways to achieve sustainable Solid waste management.  In the last paper, logistic and simple logistic functions are used as possible classifiers for detection of misfire in IC engines and their performance compared. It has been found that logistic function has better classification accuracy than simple logistic and thus can be used in misfire detection.

The first short communication presents a method of reliability modeling for a two-stage degraded system, using Cumulative damage model which helps in decision-making process on the system maintenance. The second short communication, state probabilities of source nodes and relay nodes in WSNs are evaluated based on a data flow. Results indicate that the energy consumed during operation affects the node reliability in WSNs, and the node state probabilities are related to the distribution of the number of the detecting events.

 


 
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