Chemical industry deals with lots of data sets. Some of these data are relevant to product development and the rest of them mostly helps to identify external parameters governing the production process. Generally, big data help to facilitate cost cutting issues. It brings a new product to the market and improves industry environment. Intellectual sensors are integrated with the research and material related informatics. This process minimizes the time required for new innovation. Sensitive sensors can also help to predict the upcoming situation by measuring current situations. Big data works in the back end. This ensures worker's safety by analyzing the toxic level, heart rate, etc. Intelligent sensors diagnose the past chemical data and all possible combinations to predict the new combination. It smoothens the R&D process. Therefore, automation, safety guide and intelligent forecasting are the key mantra for success in the chemical industry.

 To read, follow:  https://www.environmentalleader.com/2016/02/23/how-big-data-is-changing-chemical-manufacturing/ 

Optimizing production for manufacturers with complex operations is not an easy task. There can be volatility in costs and prices, managing multiple plants and figuring out the combination of inputs for products are complex operations. These complexities are abundant in the chemical industry. Advanced data modelling and analytical techniques have helped this industry perform better. Data about companies’ performances can be put into a mathematical model which predicts production under different conditions. The resulting model brought sea changes in the companies’ production decisions, increased plants’ EBIT returns and production capacity. This change was not without a side benefit: better cross-unit collaboration and decisions were made with all constraints and trade-offs in mind. Read more at: http://www.mckinsey.com/insights/operations/taming_manufacturing_complexity_with_advanced_analytics