Data collection and storage varies widely from one type of plant to the next. In a process-oriented environment, you need to store and retrieve time-series data in rapid bursts and large volumes (many thousands of data points per second) – which is an ideal application for a plant-wide data historian. In a discrete environment, the data is largely event based, and is ideally stored in a relational database, such as Microsoft SQL. Most companies have both environments represented in their production facilities, so the ability to collect, store and, most importantly, normalize all types of plant floor data is absolutely essential.

Additionally, you need to store data for future retrieval in a way that never limits or constrains users. How well and how flexibly a system can retrieve data to meet the widely varying needs of all stakeholders is a function of the data model, and how effectively the data was stored in the first place. It is essential to have an off-the-shelf, standards-based data model, so the different Production Management solutions and configurations can be rapidly copied, deployed and then supported globally, greatly decreasing your Total Cost of Ownership.