Factory BUILD

Real-time understanding of your production environment

manufacturing analytics

Factory BUILD is a stream-processing data pipeline that makes your data useful

Continuously generates a data foundation essential for understanding and improving production as a system.


Unique Challenges of Plant Data

  • Manufacturing data was never generated for the purpose of analysis.  It’s irregular, highly varied, out of order, and spread across multiple enterprise systems.
  • Factory BUILD uniquely addresses these challenges by integrating functions across the Sight Machine Pipeline, purpose-built over a decade of working with streaming plant data and designed to scale by applying advanced software development techniques to data processing.
manufacturing analytics


Staging: Pick, Pack & Ship

A critical step for working at scale is staging: knowing what data you have, what it’s called, and how to attach to and model it. Sight Machine’s pipeline begins with tools for these tasks, and for linking metadata to transforms and analysis.

Data Pipeline

Stream and Transform

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).

Environment Builder

Create & Model Plant Floor Lines in a Digital Twin

  • Sight Machine’s new Environment Builder puts more control in the hands of process experts and enables system-wide analysis of plant floor lines
  • Now you can create plant floor lines (that contain machines) within your facility with a drag-and-drop interface
  • Process experts can specify time offsets between machines, which allows for a more accurate representation of their place in the line
  • Developers can create lines and pipelines that are workspace-bound, which allows for faster iteration
  • Empowers process experts to create and contribute to the environment, even before all of the data is available
  • Working in parallel with Sight Machine’s Pipeline Builder, process experts can ultimately create a single view of data, or a manufacturing digital twin of their environment


Standardized Data Schemas and Common Data Models

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:

Production Schema

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.

  • Units of work can be defined using signal processing and/or time-based boundaries

Part Schema

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.

  • Units of output can be traced through the production process via serialization or a unique identifier available at each stage of production.  In many cases, serialization is not available at each step so the combination of process values, line speed for example, and conditional time-based offsets are used to associate units of work to each unit of output.

Common Models

  • KPIs
  • Factory
  • Line
  • Machine
  • Downtime
  • Supplier
  • Assembly
  • Batch
  • Defect

Pipeline Management

Sight Machine includes features for managing production data pipelines at scale

Preview, Copy, & Publish

Streamline the otherwise incredibly challenging and cumbersome process of developing and testing streaming data pipelines.

  • Test each transformation in the pipeline to ensure data integrity
  • Test changes in parallel, in the background, through our built-in version control system
  • Publish validated development pipelines seamlessly, with no downtime impact for operators

Developer Workflow Integration

  • Built-in version control
  • Editable via a DAG or JSON
  • Create your own transformations with Java


  • Know if there is an issue in your production pipeline with built-in logs, alerting, and notifications

Data Validation

  • Ensure a reliable data foundation with applications to aid in the validation of modeled data
Real Outcomes in Weeks

Getting Started is easy

Curious about how we can help? Schedule a chat about your data and transformation needs.

Sight Machine on Microsoft Surface