Process and discrete manufacturing processes and automation equipment are vastly different. Process automation systems utilize closed-loop feedback control of process variable measurements to control automated processes. Discrete automation typically relies on on/off, logic, and/or motion control to produce and assemble discretely identifiable products. Historically, process and discrete automation have functioned in separate universes. This separation has perpetuated siloes of information, conflicting asset strategies, and more importantly delays from insight to action. In addition, such compartmentalization undermines the effectiveness of the digital enterprise.
The common denominator of digital enterprise technologies such as analytics, machine learning, smart machines, and plant apps is the enhancement of the decision-making process ̶ enhancing what people can do, how fast they can do it, and the accuracy of the decisions that they make. The digital enterprise requires a holistic approach including systems capable of processing multiple types of real-time data. Real-time information at both the plant and enterprise level is vital to ensure decisions are made on the best possible information.
To fulfill its promise, Industrial Internet of Things requires solutions capable of connecting and analyzing multiple data types in real-time. Integrated and collaborative solutions such as Enterprise Impact from GE Oil & Gas Digital Solutions breakdown the traditional process and discrete siloes by integrating dynamic wave form data and process and process trend analyses, and applying multi-stage analytics to identify and prioritize asset health issues in a single application. As a Predix-enabled solution, Enterprise Impact architecture also bridges legacy systems into an IIoT environment. By aligning condition monitoring diagnoses with asset strategies Enterprise Impact increases productivity and reduces risk.
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