Accelerating the Industrial Internet of Things
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Use Cases Factory Operations Visibility & Intelligence

Factory Operations Visibility & Intelligence

Visualizing factory operations data is a challenge for many manufacturers today. One of the IIoT initiatives some manufacturers are pursuing today is providing real-time visibility in factory operations and the health of machines. The goal is to improve manufacturing efficiency. The challenge is in combining and correlating diverse data sources that greatly vary in nature, origin, and life cycle.

Factory Operations Visibility and Intelligence (FOVI) is designed to collect sensor data generated on the factory floor, production-equipment logs, production plans and statistics, operator information, and to integrate all this and other related information in the cloud. In this way, it can be used to bring visibility to production facilities, analyze and predict outcomes, and support better decisions for improvements.



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Huawei Inverter Installation with AR instructions
Huawei Inverter Installation with AR instructions
The project presented a series of technical and organizational challenges to the partners. First, the team members collaborating on the project were located in different regions of the world (US, Europe and China) and all development and testing had to be performed remotely.Huawei required that the application rely entirely on 3D Object Tracking. Finally, the solution had to work outdoors, in highly variable climatic and lighting conditions in which the SUN2000 inverters are usually installed.
How Touchscreens Can Motivate Assembly Line Workers to Do Quality Work
How Touchscreens Can Motivate Assembly Line Workers to Do Quality Work
When UTC Aerospace required a solution to manage assembly line workers with no previous manufacturing experience, it decided to try something new that set a precedent for its future manufacturing operations management (MOM) strategy.
Scaling Data Science for the Industrial IoT
Scaling Data Science for the Industrial IoT
Conventional techniques for extracting and testing algorithms must get smarter to keep pace with the phenomena they’re tracking. The challenges are mainly in the following areas: - Volume, velocity, and variety of data - Unbounded amount of factors that may affect the output - Fast changing environment calls for constantly evolving models

The industrial control and factory automation market are expected to reach USD 269.5 billion by 2024 from USD 160.0 billion in 2018, at a CAGR of 9.08%.

Source: markets and markets

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