Enterprise manufacturing intelligence

Enterprise Manufacturing Intelligence (EMI), or simply Manufacturing Intelligence (MI), is a term which applies to software used to bring a corporation's manufacturing-related data together from many sources for the purposes of reporting, analysis, visual summaries, and passing data between enterprise-level and plant-floor systems. As data is combined from multiple sources, it can be given a new structure or context that will help users find what they need regardless of where it came from. The primary goal is to turn large amounts of manufacturing data into real knowledge and drive business results based on that knowledge.

History of EMI

The term EMI was first applied to the Lighthammer "Illuminator" product in 2001. Lighthammer was one of the early pioneers in the area of Manufacturing Intelligence and Integration (and, in fact, the eponymous product SAP MII is the outgrowth of SAP's acquisition of Lighthammer in 2005). Other innovators in the area include Aegis Analytical Corporation with its Discoverant Process Intelligence software suite, Indx Software (now part of Siemens), AspenTech a leader in Process Industry Performance Management Solutions. Traditional plant floor automation vendors were later entrants into the market, including Oracle Corporation, OSIsoft, GEFanuc/Intellution, Rockwell Automation, Invensys Wonderware. At one point, both GEFanuc and Rockwell were OEM's of the Lighthammer technology, but each later created or acquired its own solution. Invensys (Wonderware) has recently introduced an EMI product called Wonderware Intelligence.

Additional pure-play EMI vendors include Informance, ActivPlant (formerly EMT, later acquired by CDC Software), Incuity (later acquired by Rockwell Automation), Manuvis, Zarpac Performance Index, Manifact CauseFindr Suite, and others.

Core Functions of EMI

AMR Research has identified five core functions every Enterprise Manufacturing Intelligence application should possess:

• Aggregation: Making available data from many sources, most often databases.
• Contextualization: Providing a structure, or model, for the data that will help users find what they need. Usually a folder tree utilizing a hierarchy such as the ISA-95 standard.
• Analysis: Enabling users to analyze data across sources and especially across production sites. This often includes the ability for true ad hoc reporting.
• Visualization: Providing tools to create visual summaries of the data to alert decision makers and call attention to the most important information of the moment. The most common visualization tool is the dashboard.
• Propagation: Automating the transfer of data from the plant-floor up to enterprise-level systems such as SAP, or vice versa.