SYSTEM FOR INVENTORY CONTROL AND MANAGEMENT OF BAKERY PRODUCT USING SVM

Abstract

The study entitled on, “To build a classification model for inventory control and management of bakery product”. Business process is dynamic respect to time, place, product & seasons. Understanding the trend and changes of pattern becomes important to consider in making business decisions. Data mining techniques are extensively applied for classification, useful patterns extraction and predications which are very important for business support and decision making. Patterns from inventory data indicate market trends and can be used in prediction that helps in decision making and planning. The objective of this study is to manage inventory of Zplus company, a bakery manufacturer who supplies bakery products fresh on daily basis. The daily production volume depends on various factors including external and internal factors. Considering only the internal factor, prediction of daily production volume helps in inventory control, and avoids stagnation of products. Based on the patterns and trends in the data, each order is predicted to include in the manufacturing based on the priority. A prediction technique is applied using SVM to predict the priority of each order so that the orders can be manufactured in accordance with the sales requirement which eliminate stagnation of products and offer better control over inventories.