The pipeline is transparent, enabling visibility into raw data, transforms, and generated data tables. It’s configurable and includes libraries of stateful transformations, as well as the ability to apply your own. And it’s robust. The pipeline accommodates late, missing, and out-of-order data, and it is built to handle changes in originating data environments.
It empowers the rapid and iterative construction of Manufacturing Applications that are inexpensive to maintain and update (because of the stability of the data foundation).
Sight Machine’s Pipeline incorporates sophisticated data management tools: regions of data are identified and selected for analysis, derivative calculations and transformations are applied, and generated information is automatically produced as data is mapped. Data is streamed into Standardized Data Schemas, which in turn automatically generate Common Data Models. Common Data Models are applied to all manufacturing activities regardless of the product made or assets used.
These schemas and models have been proven across a wide variety of industries. Models include:
Understand production activity at different levels—machines, lines, and plants—by modeling units of work done by machines. Types of work are limitless, but the idea of the unit of work is common, almost elemental. A unit of work is just the repeated cycle of activity by a machine.
Every time a machine performs a unit of work, a row of information is generated from all the data associated with that work. The unit of work is described with data from sensors on the machines, quality systems, MES, historians, ERP, and even ambient data like temperature and humidity, or other data about raw material characteristics.
Understand everything that went into a unit of output along with its resulting quality. Sight Machine tracks the flow of material through the production process and associates all units of work to a unit of output.
Streamline the otherwise incredibly challenging and cumbersome process of developing and testing streaming data pipelines.
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