Big Data Driven Decision-Making For Batch-Based Production Systems

The era of big data has brought new challenges to chemical enterprises. In order to maximize the benefits, enterprises are considering to implement intelligent service technology into traditional production systems to improve the level of intelligence in business. This paper proposes a service framework based on big data driven prediction, which includes information perception layer, information application layer and big data service layer. In this paper, the composition of big data service layer is described in detail, and a sales predicting method based on neural network is introduced. The salability of products is divided, and the qualitative economic production volume mechanism is finally given. Based on the framework, an intelligent service system for enterprises with the characteristics of mass production is implemented. Experimental results show that the big data service framework can support chemical enterprises to make decisions to reduce costs, and provides an effective method for Smart Product Service System (PSS). (C) 2019 The Authors. Published by Elsevier B.V. Peer-review under responsibility of the scientific committee of the 11th CIRP Conference on Industrial Product-Service Systems