The development of techniques that allow producing high-finish surfaces of geometrically-complex parts of difficult-to-machine materials by electrical discharge machining (EDM) is an emerging research area. The aim of this work is to study the application of electrolytic-plasma polishing technique for the high-quality surface finish of the parts obtained by EDM process. The structural alloy steel 38KH2N2MA (GOST 4543 – 71) was selected as the processing material. The morphology of the machined surface was examined using optical micrographs. It was observed that applying the electrolytic plasma polishing for the duration of 5 minutes results in reducing the surface roughness of the ED machined surface by a factor of 5. It is also concluded that the combined action of EDM with electrolytic plasma polishing method is suitable for attaining the desired surface finish.

Multi-criteria decision making approach is one of the most troublesome tools for solving the tangled optimization problems in the machining area due to its capability of solving the complex optimization problems in the production process. Turning is widely used in the manufacturing processes as it offers enormous advantages like good quality product, customer satisfaction, economical and relatively easy to apply. A contemporary approach, MOORA coupled with PCA, was used to ascertain an optimal combination of input parameters (spindle speed, depth of cut and feed rate) for the given output parameters (power consumption, average surface roughness and frequency of tool vibration) using L27 orthogonal array for turning on ASTM A588 mild steel. Comparison between MOORA-PCA and TOPSIS-PCA shows the effectiveness of MOORA over TOPSIS method. The optimum parameter combination for multi-performance characteristics has been established for ASTM A588 mild steel are spindle speed 160 rpm, depth of cut 0.1 mm and feed rate 0.08 mm/rev. Therefore, this study focuses on the application of the hybrid MCDM approach as a vital selection making tool to deal with multi objective optimization problems.

The present paper deals with the experimental analysis and multi objective optimization of gear cutting process of Inconel 718 using WEDM. The objective of the present work is to optimize the parameters in order to maximize the material removal rate and minimize the kerf in a gear cutting process to get the optimum value. The MRR and kerf play a major role in optimizing the parameters in WEDM process. The experiment is carried out in the wire EDM machine using brass wire as the electrode, Inconel 718 as the work-piece material and distilled water as the dielectric. The design array is created by using Design of Experiment in a Taguchi L16 orthogonal array repeated once. The gear has a base diameter of 20 mm, addendum diameter of 22.5 mm and a pressure angle of 20º with 16 numbers of teeth. The machining operation is carried out by taking 3 input parameters at 4 different levels each. The output parameters such as Material Removal rate and Kerf width were obtained and optimized using TOPSIS method to know the optimum setting. Microstructural analysis of both material and wire were studied to know the various defects during the machining operation. Various plots were obtained to know the effects of the process parameters in WEDM. A regression model was also obtained to validate the statistical model values with the experimental. ANOVA table and Response table were carried out to know the significant parameters and rank respectively in the Wire EDM process. Surface roughness, Addendum and Tooth width of gears were also found out at the optimum settings. The optimum setting of the gear obtained can be used to produce high quality gears and can also be applied for future findings.

Flexible manufacturing system (FMS) promises a wide range of manufacturing benefits in terms of flexibility and productivity. These benefits are targeted by efficient production planning. Part type selection, machine grouping, deciding production ratio, resource allocation and machine loading are five identified production planning problems. Machine loading is the most identified complex problem solved with aid of computers. System up gradation and newer technology adoption are the primary needs of efficient FMS generating new scopes of research in the field. The literature review is carried and the critical analysis is being executed in the present work. This paper presents the outcomes of the mathematical modelling techniques for loading of machines in FMS’s. It was also analysed that the mathematical modelling is necessary for accurate and reliable analysis for practical applications. However, excessive computations need to be avoided and heuristics have to be used for real-world problems. This paper presents the heuristics-mathematical modelling of loading problem with machine processing time as primary input. The aim of the present work is to solve a real-world machine loading problem with an objective of balancing the workload of the FMS with decreased computational time. A Matlab code is developed for the solution and the results are found most accurate and reliable as presented in the paper.

This paper investigates the effect of cutting parameters on the surface roughness and cutting force of titanium alloy Ti-6Al-4V ELI when turning using PVD TiAlN coated tool in dry environment. Taguchi L9 orthogonal array design of experiment was used for the turning experiment 2 factors and 3 levels. Turning parameters studied were cutting speed (50, 65, 80 m/min), feed rate (0.08, 0.15, 0.2 mm/rev) and depth of cut 0.5 mm constant. Linear and second order model of the surface roughness and cutting force has been developed in terms of cutting speed and feed. The results show that the feed rate was the most impact factor controlling the cutting force and surface roughness produced. MINITAB 17software was used to develop a linear and second order model of surface roughness and cutting force. Optimum condition was at 66.97 m/min of cutting speed, 0.08 mm/rev of feed rate. Surface roughness 0.57?m and cutting force 54.02 N were obtained at the optimum condition. A good agreement between the experimental and predicted surface roughness and cutting force were observed.

As the long arm of the grinding, deep financial crisis continues to haunt the global economy, the effects of inflation and time value of money cannot be oblivious to an inventory system. Inflation, defined as a general rise in the prices of goods and services over a period of time, has monetary depreciation as one of its major side effects. And, since inventories correspond to substantial investment in capital for any organization, it would be unethical if the effects of inflation and time value of money are not considered while determining the optimal inventory policy. Moreover, deterioration of items is a phenomenon which cannot be ignored, as it may yield misleading results. Further, under the inflationary conditions, the different cost parameters including the price are bound to vary from cycle to cycle over the planning horizon. Another important factor is shortages which no retailer would prefer, and in practice are partially backlogged and partially lost. In order to convert the lost sales into sales, the retailer offers such customers an incentive, by charging them the price prevailing at the time of placing an order, instead of the current inflated price. Therefore, bearing in mind these facts, the present paper develops an inventory model for a retailer dealing with deteriorating items under inflationary conditions over a fixed planning horizon. The objective is to derive the optimal number of cycles and cycle length that maximizes the net present value of the total profit over a fixed planning horizon. An appropriate algorithm has been proposed to obtain the optimal solution. Finally, a numerical example is provided to illustrate the proposed model. Sensitivity analysis of the optimal solution with respect to major parameters is carried out and some managerial inferences have been presented.

This paper investigates the role played by service quality at supplier-manufacturer dyad in small-medium manufacturing units, and presents a model to establish that contribution of both the supplier and manufacturer towards service quality could lead to satisfaction followed by loyalty. The research design for this study includes a combination of literature survey, exploratory interviews with practitioners, and a questionnaire survey conducted through interview schedule from 120 respondents working in different small-medium manufacturing units of North India. Structural equation modeling (SEM) is used for data analysis. The paper develops dual directional scales to evaluate service quality at supplier-manufacturer dyad and tests a set of four propositions. A model showing linkages of manufacturer (manufacturing unit’s) service quality with supplier service quality leading to satisfaction and loyalty is also developed. The model is empirically tested and is found to be fit. This study would be of interest to SME managers particularly engaged in ‘purchase’ function and researchers working on inter-firm supply chains in such units. This study recommends forming strong collaborative relationships with suppliers to achieve a win-win situation.

Altman Z score is an effective tool for measuring a company's financial strength and the possibility of bankruptcy. In this study, the Z score formula was utilized to measure the Indian automobile industry's financial soundness. The financial data of ten automobile companies listed in the National Stoke Exchange (NSE) was taken to analyze both original and emerging market formulae of the Altman Z score. Results suggest that companies of the industry listed in the NSE are financially sound. The study concluded that the Indian automobile industry is sound and robust, and the automobile companies are not prone to financial distress or bankruptcy in the near future.

Differential evolution (DE) is an effective and powerful approach and it has been widely used in different environments. However, the performance of DE is sensitive to the choice of control parameters. Thus, to obtain optimal performance, time-consuming parameter tuning is necessary. Backtracking Search Optimization Algorithm (BSA) is a new evolutionary algorithm (EA) for solving real-valued numerical optimization problems. An ensemble algorithm called E-BSADE is proposed which incorporates concepts from DE and BSA. The performance of E-BSADE is evaluated on several benchmark functions and is compared with basic DE, BSA and conventional DE mutation strategy. Also the performance results are compared with state of the art PSO variant.

The Indian cement industry has adopted various environmental protection technologies, but adoption of these new environmental technologies and development of working model could not resolve many issues related to environmental concern among Stakeholders. This paper examined the current technologies used by the cement companies and the challenges they are facing in adoption of these technologies. This research describes the effects of cement manufacturing on global warming, water, coal and other pollution emissions during cement production process and involves environmental manufacturing technologies. The study measures the challenges of introducing environmental technologies by creating a model of challenges. including challenges in perceived usability of technology, challenges in perceived utility, challenges in user engagement, and challenges in intent to use behaviour. The study examines the challenges of introducing environmental technologies into the Indian cement industry to mitigate air, water, and energy pollution and to highlight the new environmental technologies and development of the model. The data from 1540 professionals responsible for using the environmental technology were gathered and analysed with t test and regression analysis. The final outcome of the research is the model expressing the challenges in adoption of environmental technologies in India.