Dr. T. Mohanraj

Rapid industrialization and growth in population in urban regions augment the pollution levels from transportation sectors, especially from diesel fleets. A wide array of research activities were carried out to satisfy the energy needs as well as reduce the emission levels, which poses a big challenge to the research community. In this situation, biomass-derived fuels provide a ray of hope to the research community to address the emission problem by adapting closed carbon cycle at low cost. This chapter gives an overview to the readers about the present energy scenario, biomass-based fuel, upgradation techniques for biomass fuel, and engine adaptability of biomass-based fuels. This chapter provides a clear glimpse of biomass energy, one of the potential energy resources in the near future.

The most important improvement in metal the cutting industry is the continuous utilization of cutting tools and tool condition monitoring system. In the metal cutting process, the tool condition has to be administered either by operators or by online condition monitoring systems to prevent damage to both machine tools and workpiece. Online tool condition monitoring system is highly essential in modern manufacturing industries for the rising requirements of cost reduction and quality improvement. This paper summaries various monitoring methods for tool condition monitoring in the milling process that have been practiced and described in the literature.

This study focused on the assessment of muscle activities related to shoulder pain among the occupational ironing workers. The activity of the shoulder muscle response was observed as maximum during the ironing activity. The fatigue property was identified using the surface electromyography (sEMG). The structural spots were chosen on the basis of statistical survey and direct observation conducted before the investigation. The muscle activities of trapezius descendens of the right hand, deltoideus medius of the right hand, deltoideus anterior of the right hand, trapezius descendens of the left hand and deltoideus medius of the left hand was recorded by using the sEMG and the muscle activities were investigated for workers involved in ironing of clothes in laundry shops. The investigation reports were collected and processed. The study reports that the musculoskeletal disorder in the shoulder portion is due to the age, repetitive work, working time and iron box weight. The maximum response was observed in the deltoideus medius of the right hand. The age factor found to be the most prevailing symptom among the ironing workers. The aged persons were found to be at high risk due to repetitive task for a prolonged time period of ironing and also the table height influences fatigue. In order to overcome this problem, the workers were suggested to take adequate rest brakes during the ironing process and adjust the table height.

This paper describes an on-line tool wear monitoring system for milling operation by optimizing the input parameters while machining 7075T6 aluminium composite material. The input parameters considered are Spindle speed, feed rate and depth of cut. Coolant is the major factor that affects the tool wear to greater extent. So the type of coolant (different types of vegetable oils) is also taken as an input parameter for optimization. The experiments are carried out with different spindle speed, feed rate, depth of cut and coolant and the vibration produced in X, Y & Z directions were measured. Taguchi mixed level design (L18) is taken for optimization process using S/N ratio and ANOVA (Analysis Of Variance) analysis. The results show that the coolant has the most significance while measuring the vibration. © BEIESP.

Surface roughness and taper angle of an abrasive waterjet machined surface of 7075 Aluminum metal matrix composite were deliberately studied. Response surface methodology design of experiments and analysis of variance were used to design the experiments and to identify the effect of process parameters on surface roughness and taper angle. The jet traverse speed and jet pressure were the most significant process parameters which influence the surface roughness and taper angle, respectively. Increasing the pressure and jet traverse speed results in increasing the surface roughness and taper angle. At the same time, decreasing the standoff distance and jet traverse speed possibly enhances both the responses. The optimal process parameters of 1mm as standoff distance, 192MPa as water pressure and 30mmmin−1 as jet traverse speed were identified to obtain the minimum value of surface roughness and taper angle. Based on the optimal parameters, the confirmation test was conducted. The mathematical equation was obtained from the experimental data using regression analysis; it was observed that the error was less than 5% of the experimentally measured values.

The major difficulty faced in a machining process is predicting the failure of cutting tools and analyzing the stipulated time for tool replacement. The former and latter can be achieved through a monitoring system that surveys the effective condition. This present research work is focused on analyzing tool condition by adopting a vibration signature during the machining of a hybrid aluminum alloy composite using various coolants. The experiments were conducted employing various tools under optimum process parameters utilizing vegetable based cutting oil as a coolant. During the machining process, a vibration signature from the workpiece was acquired using an NI 6221 M series DAQ card allowing for various time domain features to be extracted. The arithmetic mean and skewness significantly increased for dull tools. Based on the extracted features, a decision making algorithm for tool condition monitoring system has been proposed. The result shows that the features extracted increased consecutively with an increase in flank wear.

An efficient method based on Taguchi's design of experiment coupled with the grey relational analysis was studied, concentrating on the optimization of process parameters over surface roughness, cutting force and tool wear rate in milling of mild steel. This study consists of three stages: experimental work, single response optimization using Taguchi's S/N value and multi-response optimization using grey relational analysis. In the first stage, the experimental work was carried out using Taguchi's design of experiments. The effects of process parameters (spindle speed, feed rate and depth of cut) on surface roughness, cutting force and tool wear rate were investigated using analysis of variance. In the second stage, Taguchi's signal-to-noise ratio was used to optimize the responses. Finally, multi-response optimization was carried out using grey relational analysis. Additionally, the analysis of variance (ANOVA) was applied to determine the most significant factor for the optimal response for milling of mild steel. From the ANOVA table, the most significant factor is the spindle speed. This proposed method can be an effective approach to enhance the multi-response optimization for milling process.

This paper presents a comparison of experimental results and a fuzzy rule based system model for calculating the cutting force in the turning operation. A full bridge dynamometer was used to measure the cutting forces over the mild steel work piece and Cemented Carbide Insert tool for different combinations of cutting velocity, feed rate and depth of cut. The rake angle, approach angle and nose radius of the cutting tool insert is kept constant throughout the experiment. This fuzzy model consists of 27 rules and Mamdani Max-min inference mechanism was used. The Taguchi designs of experiments were used to determine the number of experiments. Also, an attempt had been made to analyze the influence of the parameters using the regression analysis which yields a maximum error of 3.214% at the time of prediction which was smaller. The experiments are planned based on Taguchi's design and the measured cutting forces were compared with the predicted forces in order to validate the feasibility of the proposed design. The percentage contribution of each process parameter had been analyzed using Analysis of Variance (ANOVA). Experimental results were compared with the regression analysis and predicted fuzzy model. The difference between experimental and predicted results was obtained as around 98.84%.

In the current scenario most of the countries do not have sufficient skilled manpower specifically in agricultural sector and it affects the growth of developing countries. So it’s a time to automate the sector to overcome this problem. An innovative idea of our project is to automate the process of sowing crops such as sunflower, baby corn, groundnut and vegetables like beans, lady’s finger, pumpkin and pulses like black gram, green gram etc to reduce the human effort and increase the yield. The plantations of seeds are automatically done by using DC motor. The distance between the two seeds are controlled and varied by using Microcontroller. It is also possible to cultivate different kinds of seeds with different distance. When the Robo reaches the end of the field we can change the direction with the help of remote switches. The whole process is controlled by Microcontroller.