Artificial Technology Enabled Strategy Planning for Performance and Productivity Improvement for Large Scale Industries
Roopika Palukurthi, Ravi Raiyani and Dhairya Badiyani
Electronics and Telecommunication Engineering, MIT Pune, Pune University, Paud Road, Kothrud, Pune-411038, Maharashtra, India.
The performance and productivity of any company depends on innovative ideas (in the product and process methods), market study, competitor study, customer requirements, retention of staff, future thinking and globalisation. The paper focuses on proper strategy planning to increase the overall productivity of any industry. The paper elaborates upon the strategies with example of a steel manufacturing plant as a case study. The paper also proposes an artificial neural network model which can be used for the stock market analysis. The predictions of this model can be used for proper strategy planning.
Keywords: Prediction, Back-propagation, Productivity, Strategy planning, Artificial neural network.
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