Analysis of tea withering process through fuzzy logic approach

R.Gupta¹, S.K.Dey² and Abhijit Sinha^3*

¹Director, National Institute of Technology, Srinagar, J & K, India.

²Inspector of Factories, Government of Assam, India.

³Research scholar, Deptt. of Mechanical Engg. National Institute of Technology, Silchar, Assam, India.

Corresponding author Email: r_guptanitsil@yahoo.com

Accepted 30 March, 2012.

Abstract

Determination of the completion of withering process at the right instant bears great significance in black tea manufacturing in so far as the quality of the finished product and cost of production are concerned. Daily harvest of plucked tea leaf whether under or over withered, is undesirable for producing quality tea. At present, this is based on the subjective experience and judgement of the tea professionals in charge of the withering section and hence imprecise in nature. The reasons being the combined effects of a number of factors on withering and inherent complicated physics involved in the process. In this paper an attempt has been made to simulate the tea withering process to predict the standard of withering with a desired degree of wither, required for a harvest of green leaf to plan the schedule of tea processing for the achievement of maximum quality utilising minimum energy. This is done by using fuzzy nonlinear simulation methods. For this, withering standard (WS) have been considered as a function of five non-interactive inputs which for a tea industry were identified as moisture content (MC), standard of plucking (SP), thickness of spread (TS), period of withering (PW) and drying capacity (DC) of withering air. A set of fuzzy rules based on expert human judgement were formulated to correlate different fuzzy inputs and output. Fuzzy set operations were used to calculate withering standard of a tea industry. With the application of the developed model in Rosekandi tea estate factory, Silchar, Assam, India, it was possible to predict the withering standard which belonged to the fuzzy category of “good” with a crisp value 70.55.

Keywords: Vagueness, Fuzziness, Degree of wither, Fuzzy set.