Four Lessons Manufacturers Learned from the Pandemic
Many investments made by manufacturers over the past two years delivered new capabilities and efficiencies that should be carried forward as manufacturers look to the future in search of new business growth.
AI for End-to-End Quality
Artificial intelligence (AI) is gaining favor as a solution for quality problems, but many manufacturers struggle with the perceived cost and complexity of implementing new technology.
When Should You Hire a QMS Consultant
When beginning an ISO 9001 implementation, organizations often ask whether they should tackle the project on their own or if it would be worthwhile to bring a consultant in to help accomplish the task.
Managing Employee Shortages with IIoT
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Manufacturers are facing a troubling scenario: the need to maintain production levels in the midst of the largest workforce shakeup in our lifetime. The Industrial Internet of Things (IIoT) provides a highly effective, flexible and cost-efficient solution.
AIoT and Edge Analytics: a Powerful Combination
Swedish philosopher Nick Bostrom once said, "machine intelligence is the last invention that humanity will ever need to make". AI decision making, with real time communication and data analytics, has the ability to transform the way manufacturers understand machines.
Progress in MicroLED Fabrication and Quality: Closing the Commercialization Gap
Establishing cost-effect fabrication processes for microLED displays has proven to be challenging, and manufacturers are still working to close the gap between promise and market reality.
Fulfillment Optimization is Not an Impossible Task
Part of optimizing any logistics operation is to make sure that you are not incurring additional and lasting costs on the path to speeding up your rate of fulfillment. The goal is to move more product through your system and out the door - but you also must watch expenses.
How factories Can Build Capacity and Improve Manufacturing Processes with ML
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Without making wholesale production changes, factories can improve process efficiency with machine learning (ML). ML can increase production capacity by up to 20% while lowering material consumption rates by 4%.
Determining if a Digital Twin is right for your Manufacturing Operation
Q&A with Chris Nicholson, CEO of Pathmind. A digital twin is at once capable of simulating things that have never happened before, as well as mirroring a real, underlying physical reality and monitoring its performance.
Leverage the Edge - the Benefits of Processing Data at the Edge, Not the Cloud
The edge is an essential layer of the manufacturing technology stack. Machines on the factory floor collect vast amounts of raw data from various sources using numerous protocols, which all needs to be processed quickly to gain actionable insight.
How to manage a complex network of new and legacy equipment
With rapid advancement in automated and connected technologies, managing both new and old equipment simultaneously can be a challenging balancing act.
What Does Digital Manufacturing Mean and How Can We Move Toward It?
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Siemens used IoT sensors and data analytics to create a digital twin of the factory. By analyzing and adjusting various parts of this model, the facility could see where inefficiencies were and which changes would have the greatest impact.
Why Combining Your HMI & PLC Is the Smarter Move
While PLCs control mechanisms, electronics, and other low-level devices, HMIs empower operators with visualization and touch controls. Together, HMIs and PLCs pave the way for efficient and flexible industrial workflows.
Applying ISA-95 in an Industry 4.0 world
Given the criticality of usable data at scale for Industry 4.0, many manufacturers have turned to ISA-95-probably the most commonly recognized data-modeling standard around the world-for guidance.
Lessons to Learn from Intel's $20 Billion Manufacturing Investment
The Intel announcement is a recognition of the value of U.S.-based manufacturing, and the business will support a very long supply chain of semiconductor assembly tool designs and manufacturing in the U.S.
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