Identification of Industrial Health using ANN

The customary practice of identifying industrial sickness is a set traditional techniques which rely upon a range of manual monitoring and compilation of financial records. It makes the process tedious, time consuming and often are susceptible to manipulation. Therefore, certain readily available tools are required which can deal with such uncertain situations arising out of industrial sickness. It is more significant for a country like India where the fruits of development are rarely equally distributed. In this paper, we propose an approach based on Artificial Neural Network (ANN) to deal with industrial sickness with specific focus on a few such units taken from a less developed north-east (NE) Indian state like Assam. The proposed system provides decision regarding industrial sickness using eight different parameters which are directly related to the stages of sickness of such units. The mechanism primarily uses certain signals and symptoms of industrial health to decide upon the state of a unit. Specifically, we formulate an ANN based block with data obtained from a few selected units of Assam so that required decisions related to industrial health could be taken. The system thus formulated could become an important part of planning and development. It can also contribute towards computerization of decision support systems related to industrial health and help in better management. Artificial Neural Network (ANN) to deal with industrial sickness with specific focus on a few such units taken from a less developed north-east (NE) Indian state like Assam. The proposed system provides decision regarding industrial sickness using eight different parameters which are directly related to the stages of sickness of such units. The mechanism primarily uses certain signals and symptoms of industrial health to decide upon the state of a unit. Specifically, we propose an ANN based block with data obtained from a few selected units of Assam so that required decisions related to industrial health could be taken. The system thus formulated could become an important part of planning and development. It can also contribute towards computerization of decision support systems related to industrial health and help in better management. The ANN is a non-parametric tool which can learn from the surrounding environment and use the knowledge thus acquired for subsequent decision making similar to biological systems (11). This ability of the ANN has made it a popular mechanism for dealing with a range of applications in engineering, technology, finance, management and related disciplines. The system thus formulated could become an important part of planning and development. It can also contribute towards computerization of decision support systems related to industrial health and help in better management. The rest of the paper is organized as follows. Section II includes a brief theoretical background relevant for the work. Primarily, this section focuses on different stages of industrial health (Section II-A) and the basics of ANN (Section II-B). Section III describes the details of the proposed soft- computational framework for analyzing industrial health. The experiments performed and the results derived are included in Section IV. Section V concludes the description.