This is the first issue of the year 2017 and it is also the last issue under my editorship of International Journal of Performability Engineering which was being published for last 12 years. Dr. Dianxiang Xu and myself have been the Co-Editors-in-Chief of the Journal during the year 2016. From January 01, 2017, the journal will have two new Co-Editors-in-Chief, namely, Professor S. K. Chaturvedi, Reliability Engineering Center at IIT Kharagpur, India (eic.ijpe@gmail.com / skc@hijli.iitkgp.ernet.in) and Dr. Suprasad V. Amari, BAE Systems, USA. (Suprasad.amari@gmail.com). Professor Xing (Email: liudong.xing@umassd.edu) will remain the Editor for Short Communications in 2017.
Formal introduction of the new Co-Editors-in-Chief and the Editor for Short Communications is presented on the next page of this issue (page 2). The Editorial Board remains unchanged. 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.
This issue consists of eight papers from different areas of performability engineering. In the first paper, the performance effect of fluid flow inside the centralized waste collection pipeline is numerically investigated with different configuration of inlet points which were opened at the same time of discharge.
The second paper aims to reduce process variation of Chopped Strand Mat (CSM) in a fiber industry in the state of Goa, India. Critical process parameters have been identified using brainstorming and multi-voting method. Taguchi method of experimental design has been used to identify key factors and their optimal levels. Reduction of variance coupled with an economic analysis has been carried out and reported in the paper.
The third paper discusses the issue of integrated planning of maintenance activities and production operations at the tactical level for multi-line systems with separate resources and introduces the breaking on demand constraint and that of setup time. The paper also presents a numerical example to illustrate the results and represent the economic gap between the separate and integrated planning.
In the fourth paper, the Bayesian and classical estimation of augmented strength reliability under Augmentation Strategy Plan (ASP) have been considered. A comparative study between Maximum Likelihood and Bayesian estimators have been carried out on the basis of mean square errors (MSE) and absolute biases. The Markov Chain Monte Carlo method of approximations has been applied to draw posterior expectations under both the loss functions. The MSE and absolute biases are calculated with 1000 replications.
The fifth paper presents a discrete state space and continuous time stochastic model for two unit hot standby database system. The primary unit is production unit synchronized with hot standby unit through online transfer of archive redo log files. Different modes of failure of primary database unit are considered. Expressions for various measures of system effectiveness have been obtained by making use of semi-Markov processes and regenerative point technique.
The focus of the sixth paper is related to application of Digimat-FE to generate a realistic three dimensional microstructure for the current carbon nanotube/ epoxy composite and carried FEA to estimate the effect of nanotube dimensions on the elastic properties. Analysis shows that nanocomposite elastic properties were found to be particularly sensitive to the nanotube diameter, since larger diameter nanotubes showed a lower effective modulus and occupied a greater volume fraction in the composite relative to smaller-diameter nanotubes.
In the seventh paper, additional fault frequency features in vibration spectrum have been proposed to detect the presence of single broken rotor bar (BRB) fault in VFD driven induction motors. The additional fault frequencies are identified in the vicinity of carrier frequency of the VFD drive for effective fault diagnosis. The proposed additional frequency features will be useful to correctly identify the BRB faults at low load and no load conditions, which was very difficult using the presently available fault frequencies in the literature.
The last paper proposes a two-step method for damage bar detection in tower structures. The damage units are identified from cross-correlation function and second generation wavelets of vibration signals collected from the structure. SVM is carried for pin pointing damage bar location.

Centralized collection system is strongly influenced by the flow of fluffs inside the pipeline and geometry parameters. Therefore, it has become necessary to find out the numerical investigation of flow inside the pipe line. In this study, the performance effect of fluid flow inside the centralized waste collection pipeline was numerically investigated with different configuration of inlet points which were opened at the same time of discharge. Centralized blower collects the fluffs from the collection box inlets which were delivered by an Industrial cleaner. Numerical investigations on five cases are done with the help of FLUENT software of computational fluid dynamics. CFD was used to determine the significance of output parameters with respect to the flow inside the pipe. This study helps to understand the flow behavior inside the pipeline and to compare the output parameters with experimental investigation. These investigation results are used to develop alternative solution to reduce the energy consumption of centralized collection system. Results indicates that the output parameters of inlet collection points 1,4,8 and 12 which were discharged at the same time gives the maximum power consumption. Thus it has been chosen for the experimental investigation of centralized waste collection system in order to get an optimized alternative solution for better energy saving.

Six Sigma is a structured, statistical and logical method for process improvement. It primarily focuses on increasing the process capability by reducing process variation. This paper aims to reduce process variation of Chopped Strand Mat (CSM) in a fiber industry in the state of Goa, India. The CSM is used in automobile, aerospace, marine and many other industrial applications as housing or cover shells where strength to weight ratio is important parameter in design. The major critical to quality characteristic of CSM is GSM of fiber, where any variation in GSM of fiber leads to variation in CSM. DMAIC methodology is implemented to optimize the fiber production process and reducing process variation. Critical process parameters have been identified using brainstorming and multi-voting method. Taguchi method of experimental design has been used to identify key factors and their optimal levels. Reduction of variance coupled with an economic analysis has been carried out and reported in the paper.

This article discusses the issue of integrated planning of maintenance activities and production operations at the tactical level for multi-line systems with separate resources and introducing the breaking on demand constraint and that of setup time. The maintenance policy offers preventive replacements in the beginning of each cycle and minimal repairs in case of random failure. The model defined an objective function that reduces the overall cost and can simultaneously determine the optimal production plan (producing, lunching, storing and breaking costs) and the moment of replacement. The resolution is made with the mixed integer linear solver CPLEX. Then we provide a numerical example to illustrate the results and represent the economic gap between the separate and integrated planning.

In this paper the Bayesian and classical estimation of augmented strength reliability under Augmentation Strategy Plan (ASP) have been considered. The Augmentation Strategy Plan (ASP) is suggested for enhancing the strength of failed equipment. The Bayes estimation is carried out by assuming the model parameters are random variable and having non-informative type of priors (uniform and Jeffery’s priors) under two different loss functions, viz. squared error loss function (SELF) and Linex loss function (LLF). We assume that the Inverse Gaussian stress (Y) is subjected to equipment having Inverse Gaussian strength (X) and are independent to each other. A comparative study between ML and Bayesian estimators have been carried out on the basis of mean square errors (MSE) and absolute biases. The Markov Chain Monte Carlo method of approximations has been applied to draw posterior expectations under both the loss functions. The MSE and absolute biases are calculated with 1000 replications.

A discrete state space and continuous time stochastic model for two unit hot standby database system has been developed. The system comprised of one primary unit and single hot standby unit. The primary unit is production unit synchronized with hot standby unit through online transfer of archive redo log files. Different modes of failure of primary database unit are considered. Failure of database unit either primary or standby is dealt by database administrator (DBA). Expressions for various measures of system effectiveness have been obtained by making use of semi-Markov processes and regenerative point technique. Numerical results have been drawn on the basis of data collected. Bounds pertaining the profitability of the system have also been obtained.

Discrepancy in reported elastic properties for nanocomposites is argued to be most likely a result of either variations in the size of reinforcement or lack of control of the composite microstructure. In general, there will be a size variation in nanotubes in a given composite, contribution from each nanotube diameter and the volume percentage that tubes of a definite diameter occupy within the composite toward the overall elastic modulus is modeled. In this work, Digimat-FE is used to generate a realistic three dimensional microstructure for the current carbon nanotube/ epoxy composite. A system of aligned carbon nanotubes embedded in epoxy matrix is modeled. In the system of aligned multi walled carbon nanotubes, the entire volume of the model has been divided into finite individual sub-composites, each one containing a specific nanotube diameter with a local volume fraction. A second model showed a single representative volume element for the current nano-composite, in which the carbon nanotubes were simulated as a randomly (fully) dispersed, where all particles have been separated from each other. Moreover, a micromechanical approach for modeling short fiber composites was developed to account for the structure of the multi-walled carbon nanotube reinforcement and predict the elastic modulus of the nanocomposite as a function of the constituent properties, reinforcement geometry and nanotube structure. Finite element results show increase in elastic modulus with increasing aspect ratio for composites with high filler loading (3 vol%). Micromechanical predictions highlight the structure or size influence of the nanotube reinforcement on the properties of the nanocomposite. The nanocomposite elastic properties were found to particularly be sensitive to the nanotube diameter, since larger diameter nanotubes showed a lower effective modulus and occupied a greater volume fraction in the composite relative to smaller-diameter nanotubes.

Motor current signature analysis (MCSA) is widely used condition monitoring technique for fault diagnosis of induction motor drives. Application of variable frequency drive (VFD) to operate induction motors is increasing day by day due to their high energy savings compared to conventional speed varying devices like belt drives, gear-boxes etc. One of the limitations of MCSA technique is its inability to detect the presence of incipient level of single BRB fault in VFD driven induction motors at light load conditions up to 15%. Detection of this type of fault using current signatures requires expertise in signal processing techniques. Early detection of BRB fault can avoid the risk of consequent failures in induction motor. In this paper, additional fault frequency features have been proposed to detect the presence of single BRB fault using vibration analysis. The results have been validated at various light load conditions by comparing the vibration signatures of healthy and single BRB state of the motor.

For a tower structure containing many bars, the possible number of damage patterns in a tower is numerous. To solve this problem, a new two-step method was proposed based on a cross-correlation function and second generation wavelets. First step, by comparing the peaks of cross-correlation function, damage basic units can be found. Second step, we select a suitable second generation wavelet for distinguishing damage patterns with vector angle similarity measure. SVM are used to pinpoint damage bar last. Test result indicates that this method has good locating accuracy.