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This study is centered on the practicality of used cooking oil-based biodiesel (UCOB) as the dielectric for electrical discharge machining (EDM). To establish the usefulness of used cooking oil-based biodiesel as a dielectric for EDM, the essential properties of UCOB were determined and compared with ST EDM oil. Used cooking oil is an important source that can be employed for biodiesel production. Biodiesel was extracted by the process of transesterification. EDM performance was evaluated by applying a “one factor at a time” approach while machining Inconel-625 using EDM oil and bio-dielectric fluids. For both dielectric fluids, the material removal rate was observed to increase with discharge current. The lowest value of TWR was observed at 50 µs while the highest value was observed at 1000 µs. Thus, the performance trend for both fluids was similar. However, the performance of UCOB was slightly better than that of EDM oil. This variation is due to the difference in chemical composition of both dielectric fluids. The highest material removal rate 20.333 mm3/min was observed for UCOB operation at a discharge current of 12.48 A and the lowest material removal rate (0.123 mm3/min) was obtained with a discharge current of 1.56 A for EDM oil. It has been established that UCOB can be suitably utilized as dielectric fluid to increase the sustainability of the EDM process.

Biodiesel is a chemically modified eco-friendly fuel mainly used as a fuel in compression ignition engines. It is prepared from vegetable oil or animal fat. It is gaining worldwide popularity because it is a renewable, non-toxic, biodegradable, and non-flammable fuel. This paper gives an insight into various aspects of biodiesel. Literature review of biodiesel production, its performance in diesel engine, and the electrical discharge machining process are discussed along with other applications. An innovative biodiesel production plant of 20 L capacity has been designed and developed successfully. The conversion reaction was carried out for 20 L of used cooking oil and 4 L of methanol. The biodiesel production yield of 95.8% was observed for a 1:6 M ratio of methanol and used cooking oil using 200 gm of KOH catalyst at 60 °C for 1 h. In the second phase of the work, a framework for using biodiesel as a dielectric fluid during spark machining is presented. Using biodiesel during the spark machining process can reduce pollution and also enhances the sustainability of the process.

Careful selection and location of sensors are of key importance in the construction and implementation of an effective condition monitoring system. There is a continual call for depletion of maintenance and operational costs of rotating machine elements. Health monitoring of bearings, which is regarded as a crucial component of rotating machinery, is expected to facilitate in the preclusion of machine breakdown and ensure the machine availability by maintenance actions in time. The effectiveness and reliability of measurement approaches for monitoring the condition of the bearing are influenced by both the signal processing techniques and locations of the sensors selected for fault characteristic extraction. This paper proposes a low cost Non-contact optimal sensor placement (NC-OSP) methodology in order to get information of high quality related to the dynamic features of the machines. Experiments were conducted using different bearing conditions under different operating conditions and sensor placement positions. Mathematical models have been proposed based on the response parameters and input variables experimentation using response surface methodology. Results indicate that the most effective input variable to control the response parameters viz. FFT vibration amplitude of characteristic frequency and RMS value of time domain was the shaft speed followed by load and angle of incidence. The responses proposed by the optimal models have been observed at 8° angle of incidence with maximum load and speed. The optimal outcomes have been validated experimentally which proved that the predicted results were in sync with the actual ones. The proposed work has significant potential in industrial environment with complex systems, where the condition monitoring approach with proper placement of sensors can play an important role. Keywords: Condition monitoring (CM), Vibration signatures, Response surface methodology (RSM), Non-contact optimal sensor placement (NC-OSP), Non-contact vibration sensor

Condition monitoring is expected to assist in the prevention of machine failures and enhance the reliability with lower maintenance cost. With advancement in sensor and computer technologies, it is now possible to acquire and process a large amount of machine response data in order to extract the characteristic features which provide the indication about health condition of the system. In real applications, the machine has infinite node positions but sensors can be only placed at a finite number of locations. Hence selection of optimal node positions is a challenging task and needs to be addressed. The objective of sound sensor placement optimization is to obtain a sensor layout that gives as much information of the dynamic system as possible for condition monitoring. This paper proposes a methodology for placing sound sensor on a fixed-axis gearbox to obtain high-quality information regarding the dynamic characteristics of machine. The gearbox is operated under no load and load with varying levels of gear faults and sound sensor placement positions. Loudness, loudness level, and sharpness of sound has been considered as response parameters. Mathematical relations and models between input variables and response parameters are developed. Sound sensor placement is optimized for maximum Loudness, loudness level, and sharpness values. The models are experimentally validated and tested. Results indicate that an overall accuracy of 92.2% is achieved and the approach has significant utility in industrial environment where system complexity makes the choice of sensor placement vital for condition monitoring.