This study deals with the performance modeling and reliability analysis of a redundant machining system composed of several functional machines. To analyze the more realistic scenarios, the concepts of switching failure and geometric reneging are included. The time-to-breakdown and repair time of operating and standby machines are assumed to follow the exponential distribution. For the quantitative assessment of the machine interference problem, various performance measures such as mean-time-to-failure, reliability, reneging rate, etc. have been formulated. To show the practicability of the developed model, a numerical illustration has been presented. For the practical justification and validity of the results established, the sensitivity analysis of reliability indices has been presented by varying different system descriptors.

The present paper emphasizes on the development of a hierarchical model using Fuzzy Multiple Attribute Decision Making (FMADM) method for the selection of E-learning websites. The working of the model developed in this research mainly consists of three steps: (i) Summarization and identification of selection indexes, (ii) Selection indexes weights calculations using Fuzzy Analytical Hierarchy Process (FAHP) and (iii) Ranking of alternatives by implementing three MADM analytical methods as Complex Proportional Assessment (COPRAS), Visekriterijumsko Kompromisno Rangiranje (VIKOR) and Weighted Distance Based Approximation (WDBA). In order to demonstrate the applicability and utility of the proposed methods, an empirical example related to the selection of E-learning websites that are widely used to learn the ‘C’ Programming Language for the software development is carried out. In addition, the results of these three methods are also compared to analyze the critical aspects of the selection indexes. It strongly shows that the developed FMADM model of this paper could be an efficient and effective assessment tool.

The present work predicts the numerical progressive failure response and crack growth of finite plate laminated composites with cutout and multiple cracks under in-plane tensile and compressive loads. The ply to ply failure response of the finite plate is predicted using ABAQUS user define field variables subroutine approach, whereas the extended finite element method is used for examination of crack growth direction for multiple through crack of laminated composite finite plate. The subroutine predicted results are compared and validated with published experimental results and extended finite element method results. The effect of changing mesh size, fibre orientation, crack length, crack inclination angle on failure load, progressive stress intensity factor and damage toughness of various crack types is presented and discussed.

Powder mixed electro discharge machining (PMEDM) is a hybrid machining process where the electrically conductive powder is mixed into the dielectric fluid to enhance the machining efficiency. In this investigation, PMEDM is performed for the machining of AISI 304 stainless steel when silicon carbide powder is mixed into the kerosene dielectric. Peak current, pulse on time, gap voltage, duty cycle and powder concentration are considered as process parameter while material removal rate (MRR), tool wear rate (TWR) and surface roughness (Ra) are considered as response. A face centered central composite design (FCCCD) based response surface methodology (RSM) is applied to design the experiment. A hybrid optimization technique like desirability coupled with fuzzy-logic method is performed to get the optimum level of the multiple performance characteristics. Analysis of variance (ANOVA) is performed for the statistical analysis. The result shows that peak current is the most significant parameter for MRR, TWR and Ra. The optimal setting for maximum MRR, minimum TWR and Ra have been obtained by desirability coupled with fuzzy-logic method.

Optimization of hole-making operations plays a crucial role in which tool travel and tool switch scheduling are the two major issues. Industrial applications such as moulds, dies, engine block etc. consist of large number of holes having different diameters, depths and surface finish. This results into to a large number of machining operations like drilling, reaming or tapping to achieve the final size of individual hole. Optimal sequence of operations and associated cutting speeds, which reduce the overall processing cost of these hole-making operations are essential to reach desirable products. In order to achieve this, an attempt is made by developing an effective methodology. An example of the injection mould is considered to demonstrate the proposed approach. The optimization of this example is carried out using recently developed particle swarm optimization (PSO) algorithm. The results obtained using PSO are compared with those obtained using tabu search method. It is observed that results obtained using PSO are slightly better than those obtained using tabu search method.

Turning experiments were carried out on AA 7075/SiC composite workpiece in dry and spray cooling environments based on L16 Taguchi design of experiments. Multiple performance optimization of process parameters was performed using grey relational analysis. The performance characteristics considered were average surface roughness, cutting tool temperature and material removal rate. Uncoated carbide inserts were used for machining the workpiece in a high speed precision lathe. A grey relational grade obtained from grey relational analysis was used to optimize the process parameters. Optimal combination of process parameters was then determined by the Taguchi method using the grey relational grade as the performance index. Experimental results indicated that the turning in spray cooling environment was beneficial compared to that in dry environment for the quality response characteristics under consideration. Analysis of variance showed that feed was the most significant parameter for the multiple performance characteristics during turning in both the environments.

The powder coating is an economic, technologically superior and environment friendly painting technique compared with other conventional painting methods. However large variation in coating thickness can reduce the attractiveness of powder coated products. The coating thickness variation can also adversely affect the surface appearance and corrosion resistivity of the product. This can eventually lead to customer dissatisfaction and loss of market share. In this paper, the author discusses a dual response surface optimization methodology to minimize the thickness variation around the target value of powder coated industrial enclosures. The industrial enclosures are cabinets used for mounting the electrical and electronic equipment. The proposed methodology consists of establishing the relationship between the coating thickness & the powder coating process parameters and developing models for the mean and variance of coating thickness. Then the powder coating process is optimized by minimizing the standard deviation of coating thickness subject to the constraint that the thickness mean would be very close to the target. The study resulted in achieving a coating thickness mean of 80.0199 microns for industrial enclosures, which is very close to the target value of 80 microns. A comparison of the results of the proposed approach with that of existing methodologies showed that the suggested method is equally good or even better than the existing methodologies. The result of the study is also validated with a new batch of industrial enclosures.

In the existing literature of inventory modeling under the conditions of permissible delay in payments, researchers have assumed that the retailers have to settle their accounts at the end of credit period i.e. supplier accept only full amount at the end of the credit period. However in reality, supplier may either accept the partial amount at the end of the credit period and unpaid balance subsequently or the full amount at a fix point of time after the expiry of the credit period, if the retailer finances the inventory from the supplier itself. Further, in the classical deteriorating inventory models, the common unrealistic assumption is that all the items start to deteriorate as soon as they arrive in the system. However, in realistic environment, it is observed that there are several non-instantaneous deteriorating items that have a shelf life and start to deteriorate after a time lag, like dry fruits, potatoes, yams and even some fruits and vegetables etc. Considering the importance of above mentioned facts, the present study formulates a fuzzy inventory model for non-instantaneous deteriorating items under conditions of permissible delay in payments. The paper discusses all the possible cases which may arise and yet not considered in the previous inventory models under permissible delay in payments. Further, this paper also considers price-dependent demand and the possibility of higher interest earn rate than interest payable rate. The objective of this study is to determine the optimal decision policies for the retailer which maximizes the total profit. Finally, the numerical examples are solved by using the proposed algorithm to show the validity of the model followed by the sensitivity analysis.

This paper deals with an integrated multi-stage supply chain inventory model with the objective of cost minimization by synchronizing the replenishment decisions for procurement, production and delivery activities. The supply chain structure examined here consists of a single manufacturer with multi-buyer where manufacturer orders a fixed quantity of raw material from outside suppliers, processes the materials and delivers the finished products in unequal shipments to each customer. In this paper, we consider an imperfect production system, which produces defective items randomly and assumes that all defective items could be reworked. A simple algorithm is developed to obtain an optimal production policy, which minimizes the expected average total cost of the integrated production-inventory system.

An effective and expeditious method of the synthesis of a highly functionalized piperidines, catalyzed by nontoxic, recyclable and environment friendly sodium lauryl sulfate (SLS), via one-pot multi-component condensation of aldehydes, amines and β-ketoesters in water at room temperature, has been developed. This new protocol has advantages such as moderate to high yields of products obtained after simple post reaction workup. Structure of the synthesized compounds 4a–4j have been elucidated based on the 1H NMR, 13C NMR, FT-IR spectroscopy and elemental analysis.