Diagnostics, Asset Management
Image courtesy: Chris Vavra, CFE Media
Diagnostics, Asset Management July 17, 2019

Using robots in agriculture will create jobs

The agricultural industry is looking to technology to solve its challenges such as a labor and food shortage and robots are an important part of that strategy.

By Robotic Industries Association (RIA)
Figure 3: Three eXtended Reality (XR) technologies, such as augmented reality (AR), mixed reality (MR) and virtual reality (VR), and digital twin models can add value to manufacturer applications. Courtesy: Industrial Internet Consortium
Diagnostics, Asset Management July 10, 2019

Benefits of digitizing reality for workers in manufacturing

Digitizing reality is now possible for workers thanks to technology advances such as the Internet of Things (IoT). This new reality allows workers to benefit from augmented reality (AR), mixed reality (MR) and virtual reality (VR) to solve old problems in new and better ways.

By Michael D. Thomas
Courtesy: CFE Media
Diagnostics, Asset Management July 6, 2019

Smart manufacturing opens the door to real-time data

Smart manufacturing and the Industrial Internet of Things (IIoT)-enabled technologies can use real-time data to optimize processes and reduce costs for manufacturers.

By John Clemons
Once the testing modalities are chosen, devices can be selected and installed on assets. The devices and assets chosen will help prove the case for predictive maintenance efforts. Courtesy: Fluke Corp.
Diagnostics, Asset Management July 5, 2019

Redesigning maintenance processes to optimize PdM automation

Set the stage for a successful transition from manual to IIoT-enhanced, predictive maintenance processes.

By Frederic Baudart
For years, researchers from MIT and Brown University have been developing an interactive system that lets users drag-and-drop and manipulate data on any touchscreen, including smartphones and interactive whiteboards. Now, they’ve included a tool that instantly and automatically generates machine-learning models to run prediction tasks on that data. Courtesy: Melanie Gonick, MIT
Diagnostics, Asset Management June 28, 2019

Drag-and-drop data analytics using machine learning

MIT researchers have developed a system that lets nonspecialists use machine-learning (ML) models to make predictions for medical research, sales, and more.

By Rob Matheson
Courtesy: CFE Media
Diagnostics, Asset Management June 26, 2019

Deep embedded vision benefits for manufacturers

Deep embedded vision systems can work without operating systems and feature advanced algorithms for processing raw image streams from integrated image sensors.

By AIA
Diagnostics, Asset Management June 25, 2019

12 benefits of using standards in design, implementation for iMOM projects

Integrated manufacturing operations management (iMOM) is designed to increase and sustain business benefits for users such as improved accuracy and thorough implementation.

By Stan DeVries
Courtesy: CFE Media
Diagnostics, Asset Management June 21, 2019

Using AI to help robots remember

Researchers at the University of Maryland have developed a method to combine perception and motor commands using the hyperdimensional computing theory, which could fundamentally alter and improve how robots translate what they sense into what they do through artificial intelligence (AI).

By Gregory Hale
Image courtesy: Bob Vavra, CFE Media
Diagnostics, Asset Management June 18, 2019

Algorithm developed to predict and inform robots where humans are headed

MIT researchers have developed an algorithm that accurately aligns partial trajectories in real-time, allowing motion predictors to accurately anticipate the timing of a person’s motion to make human-robot interaction safer.

By Jennifer Chu
Figure: Comparison of transactional data extraction to the more sophisticated requirements of industrial data extraction across a number of factors. Courtesy: HighByte
Diagnostics, Asset Management June 12, 2019

Improve industrial data integration with ETL software

Extract, transform, load (ETL) software can help improve data gathering for operations technology (OT) applications, but there are major challenges with data integration that companies need to overcome.

By John Harrington