EUF-analysis of tea soils of Southern India and tea productivity

The relationship between EUF extractable nutrients and conventional soil test extractable nutrients in the acid soils of Southern India on one hand and that between EUF values and tea productivity on the other are described. Close correlation exists between EUF-NO3–N at 20°C and CuSO4–Ag2SO4-extractable NO3–N (r=0.98***), EUF-Norg and Morgan's reagent extractable NH4–N (r=0.97***), total EUF-N and CuSO4–Ag2SO4-extractable NO3–N plus Morgan's reagent NH4–N (r=0.96***), EUF-P at 20°C and modified Bray II-P (r=0.93***) and EUF-P at 20°C plus that at 80°C and modified Bray II-P (r=0.91***). The EUF-K at 20°C shows close correlation with NH4OAc–K (r=0.80***), Ag-thiourea-K (r=0.86***) and Morgan's reagent-K (r=0.84***) whereas the EUF-K at 80°C shows close correlation with the difference in K contents of NH4OAc–K and Ag-thiourea-K (r=0.92***) or of NH4OAc–K and Morgan's reagent-K (r=0.93***) and fixed NH4–N (r=0.89***). EUF-Ca, EUF-Mg and EUF-Mn do not show any relationship with conventional soil test values. Tea productivity is strongly associated with EUF-N and EUF-P extracted at 20°C.

Recent Advances and Industrial Applications of Multilevel Converters

Multilevel converters have been under research and development for more than three decades and have found successful industrial application. However, this is still a technology under development, and many new contributions and new commercial topologies have been reported in the last few years. The aim of this paper is to group and review these recent contributions, in order to establish the current state of the art and trends of the technology, to provide readers with a comprehensive and insightful review of where multilevel converter technology stands and is heading. This paper first presents a brief overview of well-established multilevel converters strongly oriented to their current state in industrial applications to then center the discussion on the new converters that have made their way into the industry. In addition, new promising topologies are discussed. Recent advances made in modulation and control of multilevel converters are also addressed. A great part of this paper is devoted to show nontraditional applications powered by multilevel converters and how multilevel converters are becoming an enabling technology in many industrial sectors. Finally, some future trends and challenges in the further development of this technology are discussed to motivate future contributions that address open problems and explore new possibilities.

Industrial validation of processing maps of 316L stainless steel using hot forging, rolling, and extrusion

The development of microstructure in 316L stainless steel during industrial hot forming operations including press forging (strain rate of 0 . 15 s(-1)), rolling/extrusion (strain rate of 2-8 . 8 s(-1)), and hammer forging (strain rate of 100 s(-1)) at different temperatures in the range 600-1200 degrees C was studied with a view to validating the predictions of the processing map. The results showed that good col relation existed between the regimes indicated in the map and the product microstructures. The 316L stainless steel exhibited unstable flow in the form of flow localisation when hammer forged at temperatures above 900 degrees C, rolled below 1000 degrees C, or press forged below 900 degrees C. All these conditions must therefore be avoided in mechanical processing of the material. Conversely, in order to obtain defect free microstructures, ideally the material should be rolled at temperatures above 1100 degrees C, press forged at temperatures above 1000 degrees C, or hammer forged in the temperature range 600-900 degrees C. (C) 1996 The Institute of Materials.

Diaphragmless shock wave generators for industrial applications of shock waves

The prime focus of this study is to design a 50 mm internal diameter diaphragmless shock tube that can be used in an industrial facility for repeated loading of shock waves. The instantaneous rise in pressure and temperature of a medium can be used in a variety of industrial applications. We designed, fabricated and tested three different shock wave generators of which one system employs a highly elastic rubber membrane and the other systems use a fast acting pneumatic valve instead of conventional metal diaphragms. The valve opening speed is obtained with the help of a high speed camera. For shock generation systems with a pneumatic cylinder, it ranges from 0.325 to 1.15 m/s while it is around 8.3 m/s for the rubber membrane. Experiments are conducted using the three diaphragmless systems and the results obtained are analyzed carefully to obtain a relation between the opening speed of the valve and the amount of gas that is actually utilized in the generation of the shock wave for each system. The rubber membrane is not suitable for industrial applications because it needs to be replaced regularly and cannot withstand high driver pressures. The maximum shock Mach number obtained using the new diaphragmless system that uses the pneumatic valve is 2.125 +/- 0.2%. This system shows much promise for automation in an industrial environment.

Modelling, simulation, and graphical user interface for industrial gas carburising process

A mathematical model has been developed for the gas carburising (diffusion) process using finite volume method. The computer simulation has been carried out for an industrial gas carburising process. The model's predictions are in good agreement with industrial experimental data and with data collected from the literature. A study of various mass transfer and diffusion coefficients has been carried out in order to suggest which correlations should be used for the gas carburising process. The model has been interfaced in a Windows environment using a graphical user interface. In this way, the model is extremely user friendly. The sensitivity analysis of various parameters such as initial carbon concentration in the specimen, carbon potential of the atmosphere, temperature of the process, etc. has been carried out using the model.

Total Factor Productivity Growth and Output Growth in Indian Electronics Industry in the Liberalization Era: An Empirical Examination

This paper analyses the efficiency and productivity growth of Electronics industry, which is considered one of the vibrant and rapidly growing manufacturing industry sub-sectors of India in the liberalization era since 1991. The main objective of the paper is to examine the extent and growth of Total Factor Productivity (TFP) and its components namely, Technical Efficiency Change (TEC) and Technological Progress (TP) and its contribution to total output growth. In this study, the electronics industry is broadly classified into communication equipments, computer hardware, consumer electronics and other electronics, with the purpose of performing a comparative analysis of productivity growth for each of these sub-sectors for the time period 1993-2004. The paper found that the sub-sectors have improved in terms of economies of scale and contribution of capital.The change in technical efficiency and technological progress moved in reverse directions. Three of the four industry witnessed growth in the output primarily due to TFPG and the contribution of input growth to output growth had been negative/negligible, except for Computer hardware where contribution from both input growth and TFPG to output growth were prominent. The paper explored the possible reasons that addressed the issue of low technical efficiency and technological progress in the industry.

Total Factor Productivity in Indian Electronic Sector after Liberalisation: Sources and Outcomes

This paper analyses the efficiency and productivity growth of the Electronic Sector of India in the liberalization era since 1991. The study gives an insight into the process of the growth of one of the most upcoming sector of this decade. This sector has experienced a vast structural change along with the changing economic structures in India after liberalisation. With the opening up of this sector to foreign market and incoming of multinational companies, the environment has become highly competitive. The law that operates is that of Darwin’s ‘Survival of the fittest’. Existing industries experience a continuous threat of exit due to entrance of new potential entrants. Thus, it becomes inevitable for the existing industries in this sector to improve productivity growth for their survival. It is thus important to analyze how the industries in this sector have performed over the years and what are the factors that have contributed to the overall output growth.

Distributed Simulation Of Flexible Manufacturing Systems

Flexible Manufacturing Systems (FMS), widely considered as the manufacturing technology of the future, are gaining increasing importance due to the immense advantages they provide in terms of cost, quality and productivity over the conventional manufacturing. An FMS is a complex interconnection of capital intensive resources and high levels of system performance is very crucial for survival in a competing environment.Discrete event simulation is one of the most popular methods for performance evaluation of FMS during planning, design and operation phases. Indeed fast simulators are suggested for selection of optimal strategies for flow control (which part type to enter and at what instant), AGV scheduling (which vehicle to carry which part), routing (which machine to process the part) and part selection (which part for processing next). In this paper we develop a C-net based model for an FMS and use the same for distributed discrete event simulation. We illustrate using examples the efficacy of destributed discrete event simulation for the performance evaluation of FMSs.

Patent intelligence and its implications for patent productivity

The prevailing hypercompetitive environment has made it essential for organizations to gather competitive intelligence from environmental scanning. The knowledge gained leads to organizational learning, which stimulates increased patent productivity. This paper highlights five practices that aid in developing patenting intelligence and empirically verifies to what extent this organizational learning leads to knowledge gains and financial gains realized from consequent higher patent productivity. The model is validated based on the perceptions of professionals with patenting experience from two of the most aggressively patenting sectors in today’s economy, viz., IT and pharmaceutical sectors (n=119). The key finding of our study suggests that although organizational learning from environmental scanning exists, the application of this knowledge for increasing patent productivity lacks due appreciation. This missing link in strategic analysis and strategy implementation has serious implications for managers which are briefly discussed in this paper.

Biocorrosion in industrial applications

Industrial situations afflicted by corrosion induced by microorganisms are illustrated with examples. The types and characteristics of microorganisms involved in biocorrosion processes are discussed. Possible mechanisms in biocorrosion as occurring under sub-soil, sea water and fresh water conditions are analyzed. Methods to combat biocorrosion are also outlined.

Evolutionary Algorithm for the Determination of Optimal Mode of Bioreactor Operation

Stirred tank bioreactors, employed in the production of a variety of biologically active chemicals, are often operated in batch, fed-batch, and continuous modes of operation. The optimal design of bioreactor is dependent on the kinetics of the biological process, as well as the performance criteria (yield, productivity, etc.) under consideration. In this paper, a general framework is proposed for addressing the two key issues related to the optimal design of a bioreactor, namely, (i) choice of the best operating mode and (ii) the corresponding flow rate trajectories. The optimal bioreactor design problem is formulated with initial conditions and inlet and outlet flow rate trajectories as decision variables to maximize more than one performance criteria (yield, productivity, etc.) as objective functions. A computational methodology based on genetic algorithm approach is developed to solve this challenging multiobjective optimization problem with multiple decision variables. The applicability of the algorithm is illustrated by solving two challenging problems from the bioreactor optimization literature.