Data Acquisition Systems (DAQ or DASs) and Management
The Industrial Internet of Things (IIoT) and machine-to-machine communication common to Industry 4.0 widely leverage internal sensors and data collection systems to monitor machine operation data and share that data with upstream/downstream systems and networks. While technicians and maintenance personnel used to be the only plant employees interested in data acquisition systems (DASs)(DAQ), today’s discreet and process manufacturers alike leverage machine performance data across the enterprise — in the front and back office. Operational equipment yields information about the efficiency of manufacturing equipment, sources of rework and material loss, and opportunities to improve productivity. It is not an overstatement to say that data acquisition systems are the new heart and blood of the modern enterprise. With this in mind, it’s critical for Edgewater Automation customers to fully understand the sources, methods, management, and utilization of data acquisition systems and their ability to provide insights that can lead to process and production improvements.
Data Acquisition System Sources and Interfaces
Today’s manufacturing plants have many different data networks powering layers of enterprise software and data collection. Some of the most common sources of data for DAQ/DAS include supervisory control and data acquisition (SCADA) software systems used to control manufacturing equipment and processes. For larger networks with more than 3,000 data collection points, distributed control systems (DCSs) are a common architecture, while individual machines are often directed by programmable logic controllers. All of these systems generate data that provides insights into the efficiency of