An Application of Predictive Analytics in Manufacturing Sector for Price Prediction and Demand Prediction
Darshan Labhade1, Nikhil Lakare2, Aniket Mohite3, Siddhesh Bhavsar4, Sushma Vispute5
1Darshan Labhade, Computer Engineering, Pimpri Chinchwad College of Engineering, Pune, India.
2Nikhil Lakare*, Computer Engineering, Pimpri Chinchwad College of Engineering, Pune, India.
3Aniket Mohite, Computer Engineering, Pimpri Chinchwad College of Engineering, Pune, India.
4Siddhesh Bhavsar, Computer Engineering, Pimpri Chinchwad College of Engineering, Pune, India.
5Sushma Vispute, Computer Engineering, Pimpri Chinchwad College of Engineering, Pune, India.
Manuscript received on June 13, 2020. | Revised Manuscript received on June 23, 2020. | Manuscript published on July 10, 2020. | PP: 196-199 | Volume-9 Issue-9, July 2020 | Retrieval Number: 100.1/ijitee.H6465069820 | DOI: 10.35940/ijitee.H6465.079920
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Abstract: Predictive analytics is the examination of concerned data so that we can recognize the problem that may arise in the near future. Manufacturers are interested in quality control, and making sure that the whole factory is functioning at the best possible efficiency. Hence, it’s feasible to increase manufacturing quality, and expect needs throughout the factory with predictive analytics. Hence, we have proposed an application of predictive analytics in manufacturing sector especially focused on price prediction and demand prediction of various products that get manufactured on regular basis. We have trained and tested different machine learning algorithms that can be used to predict price as well as demand of a particular product using historical data about that product’s sales and other transactions. Out of these different tested algorithms, we have selected the regression tree algorithm which gives accuracy of 95.66% for demand prediction and 88.85% for price prediction. Therefore, Regression Tree is best suited for use in manufacturing sector as long as price prediction and demand prediction of a product is concerned. Thus, the proposed application can help the manufacturing sector to improve its overall functioning and efficiency using the price prediction and demand prediction of products.
Keywords: Analytics, Demand Prediction, Prediction, Manufacturing Sector, Machine Learning Algorithms, Prediction, Price Prediction, Regression Trees.
Scope of the Article: Machine Learning