Value of the item set is considered as an utility of that item set and find out the high utility of the item set is the aim of utility mining .Some time database parameters are considered to find out high utility pattern eg. Profit, cost etc. In day to day life high utility pattern mining play important role in applications. Its current hot topic in today’s research area. Different existing algorithms are present in this area .It first of all identify the candidate itemsets by using their utilities, and simultaneously identify the exact utility of that candidate pattern. Problem of using this algorithm is large number of candidate itemsets are generated. But after computing exact utility it’s clear that most of the candidate having no high utility. For generating profitable product manufacturing plan its very important to understanding the customer preferences in industrial area. One of the approach in pattern mining, by considering the quantity, quality and cost of each product for generating high profitable product set, which employed to find out high utility pattern. For establishing highly profitable manufacturing plan which allow corporation to maximize its revenue, high utility pattern mining is important aspect. Large amount of stream data related to customer purchase behavior used for establishing manufacturing plan. Recent preference of the customers also helps in generating manufacturing plans. This survey work contains a list structure and a novel algorithm for generating high utility pattern over large data, on the basis of Sliding Window Control Mode. This approach avoid the generation of candidate pattern. Due to that algorithm not required large amount of memory space as well as computational resources for verifying candidate patterns. Due to this it’s very efficient approach.