The aim of any industrial plant, which is dealing in the energy sector, is to maximise the revenue generation at the lowest production cost. It can be carried out either by optimizing the manpower or by improving the performance index of the overall unit. This paper focuses on the optimisation of a biomass power plant which is powered by G50 hardwood chips (Austrian standard for biomass chips). The experiments are conducted at different operating conditions. The overall effect of the enhanced abilities of a reactor on the power generation is examined. The output enthalpy of a generated gas, the gas yield of a reactor and the driving mechanism of the pyrolysis are examined in this analysis. The thermal efficiency of the plant is found to vary from 44 to 47% at 400◦C, whereas it is 44 to 48% for running the same unit at 600 ◦C. The transient thermal condition is solved with the help of the lumped capacitance method. The thermal efficiency of the same design, within the constraint limit, is enhanced by 5.5%, whereas the enthalpy of the produced gas is magnified by 49.49% through nonlinear optimisation. The temperature of biomass should be homogenous, and the ramping rate must be very high. The 16% rise in temperature of the reactor is required to reduce the mass yield by 20.17%. The gas yield of the reactor is increased by up to 85%. The thermal assessment indicates that the bed is thermally thin, thus the exterior heat transfer rate is a deciding factor of the pyrolysis in the reactor.

A metrological verification of a high precision digital multimeter was made by the laboratory of calibration of programmable electrical multifunction instruments of the National Institute of Metrological Research (INRIM) in order to verify its accuracy and stability. The instrument had been tested for a period of six months for five low-frequency electrical quantities (DC and AC Voltage and Current and DC Resistance). Its stability and precision were compared with the accuracy specifications of the manufacturer. As a new approach, a performance index of the DMM was introduced and evaluated for each examined measurement point. The DMM showed a satisfactory agreement with its specifications to be considered at the level of other top-class DMMs and even better in some measurements points.

Indian SMEs are going to play pivotal role in transforming Indian economy and achieving

double digit growth rate in near future. Performance of Indian SMEs is vital in making

India as a most preferred manufacturing destination worldwide under India’s “Make in India

Policy”. Current research was based on Indian automotive SMEs. Indian automotive SMEs

must develop significant agile capability in order to remain competitive in highly uncertain

global environment. One of the objectives of the research was to find various enablers of

agility through literature survey. Thereafter questionnaire administered exploratory factor

analysis was performed to extract various factors of agility relevant in Indian automotive

SMEs environment. Multiple regression analysis was applied to assess the relative importance

of these extracted factors. “Responsiveness” was the most important factor followed by

“Ability to reconfigure”, “Ability to collaborate”, and “Competency”. Thereafter fuzzy logic

bases algorithm was applied to assess the current level of agility of Indian automotive SMEs.

It was found as “Slightly Agile”, which was the deviation from the targeted level of agility.

Fuzzy ranking methodology facilitated the identification & criticalities of various barriers

to agility, so that necessary measures can be taken to improve the current agility level of

Indian automotive SMEs. The current research may helpful in finding; key enablers of agility,

assessing the level of agility, and ranking of the various enablers of agility to point out the

weak zone of agility so that subsequent corrective action may be taken in any industrial

environment similar to India automotive SMEs.