By providing a consistent methodology to assess data, manufacturers can establish a common vocabulary for describing the usability of data.
Manufacturers embarking on digital transformation projects face a series of early decisions that will ultimately determine if the projects succeed in transforming the company or become failed science experiments.
Manufacturers produce the largest volume, velocity, and variety of data. Manufacturing analytics hold the key to understanding. This paper provides a practical “how to” guide for launching a manufacturing analytics project. See how to avoid common roadblocks and pitfalls.
With more intelligent use of factory data, today’s manufacturer is in a better competitive position. See how to achieve real-time visibility into your automation systems and manufacturing operations.
For manufacturers, operational insight is masked by mountains of process and part data flowing from factory floor sensors, systems, suppliers, and other data sources. This paper makes the case for an advanced manufacturing analytics platform that helps uncover secrets from the factory floor for real-time, data-driven insight, enabling fact-based decisions.
Through our experience with dozens of companies embarking on digital transformation, Sight Machine has developed a standardized process to evaluate corporate readiness, identify appropriate projects — those most likely to succeed based on current readiness — and rank projects according to their readiness. We call this the Digital Readiness Index (DRI).
In this white paper, we discuss a new productivity metric that lets manufacturers directly link productivity data to profitability. We believe this approach provides the flexibility and ease of use that manufacturers are looking for as they evaluate potential investments, including investments in digitization.
This eBook demonstrates how Manufacturing Operations Management is still at the center of data collection, information handling, and operations management in most enterprises. The impact that IT trends are having on the Manufacturing Operations Management space are investigated, and suggestions are be given as to where thing will go in the coming years.
We are in the midst of one of the most transformative periods in industrial operations and technology over the past 40 years. As industrial executives attempt to make sense of changing business models and technology landscapes, it is critical that a formalized and structured approach is taken.
A key benefit of the digital enterprise is operational intelligence. A vast quantity of end-to-end manufacturing data is available in most plants and factories, but the question manufacturers often ask: How can we transform this huge repository of data into actionable intelligence to gain value from it?