The 30th edition of IMTS was the fourth largest in IMTS history and the largest six-day show ever.

Eclipse Automation is offering employees bicycles to promote environmental impact awareness.

Since 2012, Dr. Fübi has served as CEO for RWE Technology.

Clean energy gets attention from around the world. In June, the United States, Brazil and China made new commitments to fight climate change.

Manufacturers add three to policy and government relations division, member and board relations adds one.

Tariq Masud sat down with Quality to explain why this topic is so important. He will be presenting at The Quality Show on Tuesday, October 24.

The Oregon Manufacturing Innovation Center Research and Development (OMIC R&D) welcomed Heidenhain Corporation as its 33rd member.

Learn how design controls can help quality managers assess medical devices.

Force measurement is the measure of a push (compression) or pull (tension) against an object. It sounds elementary enough, but it’s a crucial part of quality control testing with more and more applications in today’s globalized supply chain. The needs for force measurement are all around us.

The single most important thing manufacturing leaders can do to engage their employees is to share the ‘why’ behind their daily work, says Kathleen Skarvan, CEO at New Prague, MN-based Electromed—Quality’s 2021 Plant of the Year.

Due to its ability to nondestructively capture, display and analyze the internal structures of objects in high resolution and three-dimensionally, industrial computed tomography is gaining importance as a precise 3D measuring technology for production in addition to the classic application fields of research and development and failure analysis.

Ensuring stringent medical part quality is challenging, but with the right vision system, manufacturers can utilize powerful technology to help determine that the challenges are being met. 

Measurement devices must be calibrated regularly to ensure they perform their jobs properly. While calibration covers a wide range of applications and scenarios, the goal is simple: ensure your device is measuring to your standards.

How LVHN used Lean Six Sigma tools and Minitab statistical analysis to achieve improvements in patient-centered care.

For their dedication to quality, Larsen Manufacturing (Mundelein, IL) has earned our 2022 Quality Plant of the Year award.

We review essential software specifications and cover how those attributes can be leveraged when considering computer-controlled physical product testing equipment in the lab or on the shop floor.

What level of quality do you feel is required in orthopedic implants, pacemakers and other critical, life-sustaining medical devices? The highest quality, of course!

We will explore the use of CMMs, advancements in technology, and their growing contribution to support leading developments in automation, artificial intelligence, and machine learning.

Gerresheimer, a manufacturer for the pharma and life science industry, will invest more than $88 million in expanding its manufacturing operations in Peachtree City, creating over 200 new jobs for Fayette County.

As the industry continues to trend toward a more patient-centric approach, we see an increasing buzz around the development and utilization of wearable injectors, also known as on-body delivery systems (OBDS)—the next evolution in needle-based drug delivery products.

Traditional machine vision used rule-based programming for controlled environments but struggled in less controlled settings. Edge learning AI, operating directly on vision systems, enhances machine vision's power and usability, revolutionizing quality assurance and manufacturing processes.

Torque testing raises unique challenges, and here we highlight varied examples in sectors where health and safety are paramount.

In the medical device industry, reliability is critical. Manufacturers conduct extensive testing to ensure devices meet required standards, such as 95/95 or 95/99 confidence and reliability, assessed using Minitab Statistical Software.

Automating testing and inspection requires careful consideration of tools, including robot type, end-of-arm tooling, and ancillary systems. While cobots are popular for quality tasks, their full collaborative capabilities may not be utilized in some applications, leading to higher costs without maximizing benefits.

System integration strategies vary by industry and project scale. Success relies on thorough planning and execution, especially in machine vision technology. Here are key integration elements for success with vision technologies.

Labor shortages continue to pressure manufacturers, with some dedicating up to 20% of their workforce to manual inspection. Embracing Quality 4.0 with automated in-line inspections and AI process analytics could provide significant value.

In this article we survey key considerations when making a lens selection. Of course, your lensing professional will be happy to advise – but they’ll ask you some of these questions anyway, so it’s helpful to make notes relative to your planned application.

Discovering, evolving, and sometimes unsettling, artificial intelligence mirrors our human learning. Yet, as it integrates further, questions arise: Can it handle quality assurance? What's in the future? And crucially, how much control are we comfortable relinquishing to it?

The famous quote "Adapt or die" applies to businesses like Kodak and Blockbuster, which missed out on opportunities by not embracing new technologies. This concept also applies to industries like manufacturing and logistics today.

Quality spoke with David Dechow of Machine Vision Source following his recent presentation at The Quality Show South about vision solutions for quality applications and integration that drives application success with current and emerging technologies.

In the fast-paced and dynamic world of manufacturing, one trend is clear: short-wave infrared (SWIR) imaging and sensing is revolutionizing the industry.

Manufacturers face complex challenges, including attracting and retaining labor and adapting to a volatile market. Skilled human labor remains crucial despite advancements in automation.

Industry solutions and products rely on common standards and interfaces, enabling seamless collaboration and increasing efficiency.

Machine vision has evolved significantly over the past forty years, and the demand for specialized solutions has increased in recent years. This article will explore current and future imaging requirements.

The growing use of AI in manufacturing has revolutionized quality control. Traditional inspection methods struggle to keep pace with complex production processes, but AI augments accuracy and efficiency, upholding high-quality standards.

In battery cell production, maintaining high quality and reducing material waste is crucial. Digital image processing and machine vision solutions enable reliable defect detection, ensuring the production of safe, high-quality battery cells for electric mobility.

No robot can replace a person, but they can handle dull, dangerous, or repetitive tasks, freeing up employees for more fulfilling work. Businesses need to embrace robotics to efficiently adapt to production cycles and address supply chain backlogs and labor shortages.

Selecting the correct LED lighting for machine vision can be challenging, even for experienced professionals. While red LEDs are commonly used, blue LEDs can be a superior choice for certain applications.

Machine vision projects often face challenges such as slow progress, difficulty in getting quotes, cost overruns, and unreliable operation. These issues require recognizing and adapting to the unique nature of machine vision projects compared to other types of projects.

Machine vision can measure with greater precision and accuracy than human vision. This series starts by exploring techniques for high-precision measurements in vision systems. The next installments will examine challenges and solutions for maintaining this precision and accuracy. First, we'll clarify key terms related to measurement accuracy.

The first part of this three-part series covered the principles that allow machine vision to make high-accuracy measurements. This second part examines challenges that the measurement environment imposes on machine vision and gives approaches to mitigate the effects and retain much of the high-accuracy capability.

Initially seen as science fiction, machine vision in manufacturing faced hesitance due to high costs and lack of awareness. However, interest has surged, shifting the focus from "Can it be done?" to "How will we do it?" This reflects significant transformative changes in the industry.

The first part of this series covered the basic principles that make high-accuracy measurements possible for machine vision. The second part of the series looked at challenges to accurate measurements due to the application conditions. This third part looks at characteristics and components of the vision system that can limit the achievable accuracy.

As businesses increasingly rely on machine vision to enhance quality, improve productivity, and increase the bottom line, technology providers are relying more on industrial computing solutions that enable faster processing speeds and higher efficiency, or that support new tasks altogether. 

Manufacturers focus on reducing their operating costs, but cannot afford buying more productive machinery.

The survival requirements of a part identification mark is an essential function to determine what marking system or method is best used.

79% of organizations are still managing shop floor quality processes with spreadsheets and paper. But the truth is, to remain competitive and reduce risk across your operations, it's time to modernize your programs and say goodbye to the spreadsheets.

The aerospace industry is known for manufacturing parts with critical dimensions and tight tolerances. Despite the high-demanding inspections they are required to perform, important players in the industry have managed to reduce bottlenecks and detect problems early in the manufacturing process.

Finding new talent can be an extremely difficult process for any organization, in any industry.

Are you a manufacturer researching ways to improve and increase productivity, as your cast parts become more complex?