Hexagon’s Manufacturing Intelligence division has released a new multi-sensor CMM that facilitates smart manufacturing by providing a cost-effective entry point into automated measurement.

Fully compatible with a range of Hexagon smart technologies, the Optiv Lite 3.2.2 is a benchtop CMM designed to deliver a smooth transition from manual to automatic quality methods for greater inspection accuracy, reliability and efficiency. In addition, the CMM offers connectivity to end-to-end manufacturing solutions for process and product improvements traditionally beyond the scope of entry-level machines.

Optiv Lite 3.2.2 is purpose-built for the quick and precise non-contact and tactile measurement of small parts across a range of industries, including e-mobility, precision engineering and medical. Offering complete traceability of measurement results and a simplified interface for ease-of-use, Optiv Lite 3.2.2 is suitable for manufacturers looking to adopt automated inspection procedures or meet expanding production demands.

The Optiv Lite 3.2.2 can offer inspection close to production environments, with its rugged mechanical design, high machine dynamics and capabilities for precise measurement in a wide temperature range. This lightweight machine offers a small factory footprint and high accuracy with its 6x motorised zoom lens and high-resolution digital colour camera. An optional touch-trigger probe (HP-TM) is available, as well as the HR-MP probe changer rack that can hold up to three probe modules. Further options include a laser triangulation sensor and a rotary indexing table.
PC-DMIS metrology software comes as standard with Optiv Lite 3.2.2, and users can increase operational simplicity with ‘Inspect’, a stand-alone app that allows production-level operators to easily execute measurement routines using a user-friendly interface.

For further information
www.hexagonmi.com

Newcastle-based ExplantLab is an independent research organisation that aims to improve the performance of medical implants such as hip and knee replacements. The company combines extensive surgical, bioengineering and medical knowledge to understand the performance of medical implants following their removal from a patient’s body (explants).

When ExplantLab receives an explant, the company’s team employs a range of advanced technologies to reverse engineer them and accurately determine their ‘as-new’ shape. For several years ExplantLab has used a Mitutoyo Legex 322 CMM for this purpose, the success of which – alongside and an ever-increasing volume of explants – recently prompted the purchase of a second Mitutoyo CMM.

ExplantLab director David Langton says: “In consultation with Mitutoyo’s experts we decided that a Strato Apex 574 CNC CMM with an XYZ capacity of 500 x 700 x 400 mm was the ideal solution to our accuracy and scanning speed requirements.”

As ExplantLab’s recently installed Strato Apex 574 CNC CMM has a large component support, the company’s employees are now able to load multiple explants on to the machine and perform rapid, fully automated reverse-engineering routines.

A typical use for the Strato Apex 574 CMM is the scanning of explant bearing surfaces to establish multiple data points for in-depth analysis. Automated programs allow the Mitutoyo CMM to distinguish between the unworn parts of bearing surfaces and determine their precise as-new geometries. From the unworn areas, it is possible to reverse-engineer the original component geometries. By comparing the actual surface (the post revision geometry) of a component with the original (as manufactured) surface, the magnitude of wear can be calculated and accurately mapped. The machine generates comprehensive reports relating to the precise status of each explant.

For further information
www.mitutoyo.co.uk

Based on its recent analysis of the global industrial computed tomography (CT) market, Frost & Sullivan has presented Wenzel with its 2020 Global New Product Innovation Award for the exaCT L, one of the most compact, high-value and cost-effective offerings in the 225 kV, 1600 W performance class. The solution’s three independent axes enable accelerated measuring and a simple and effective workflow across the entire CT process.

“Compared with many tactile or optical measuring machines that carry out measurements at the component, the exaCT L can measure inside and outside objects with high precision,” says Mariano Kimbara, senior industry analyst at Frost & Sullivan. “The exaCT L has superior X-ray performance combined with a fast detector, allowing it to measure objects and defects rapidly. Wenzel has made significant inroads into the market with intuitive user guidance that employs intelligent software to automate all measuring parameters, delivering robust customer value.”

Wenzel’s exaCT series, including the exaCT L, can support several metrology and non-destructive testing applications, including aluminium castings and combustion engines. The company equips the exaCT L 150 kV version with a high-resolution micro-focus X-ray source featuring a 6000-pixel detector. By establishing a new benchmark with one of the highest-powered X-ray sources available in the 225 kV segment, exaCT L offers up to 1600 W with high flexibility in applications for larger measuring volumes. Another benefit is Wenzel’s configurable and modular system for individual requirements.

The Wenzel exaCT L is configurable with existing CT system power sources and detectors, depending on application requirements. Providing 225 kV output, scanning high-density materials such as plastics, metal and multi-materials, only takes minutes.

For further information
www.wenzel-group.com

Faro Technologies has hired two industry veterans to manage the global hardware and software R&D teams.

Avi Ray-Chaudhuri, who serves as vice president of hardware R&D, and Wesley Tilley, who serves as vice president of software R&D, joined the company at the end of last month.

“We’re adding critical talent to the executive team to lead both our software and hardware R&D organisations, a move that will accelerate our product development efforts,” says Michael Burger, president and CEO of Faro.

Ray-Chaudhuri has over 20 years of leadership success in diverse industries including semiconductor, advanced lithography and laser development. Most recently, he served as VP engineering – commercial lasers for Lumentum, where he reduced the product development cycle time and implemented best-in-class programme management, engineering and operations practices. Ray-Chaudhuri earned a doctorate from the University of Wisconsin and a degree in electrical engineering from Princeton University.

Tilley brings has more than 30 years of experience in the telecommunications industry, primarily in the areas of product management and R&D leadership. He most recently served as VP communications SaaS at Oracle, where he led a strategic shift in global business unit strategy to cloud-native, SaaS offerings in the telecommunications space. Tilley has an MBA from Duke University and a degree in computer science from North Carolina State University.

For further information www.faro.com

High demands on products, as well as high time and cost pressure, are decisive competitive factors across all industries. Quality, safety and speed are today – more than ever before – factors that determine the success of a company, whatever the sector.

Zero-defect production is the goal. But how can it be guaranteed that only flawless products leave the production line? In order to make quality inspection as efficient, simple, reliable and cost-effective as possible, the German company sentin GmbH develops solutions that use deep learning and industrial cameras from IDS to enable fast and robust error detection. A sentin Vision system uses AI-based recognition software and can be trained using a few sample images. Together with a GigE Vision CMOS industrial camera from IDS and an evaluation unit, it can be easily embedded in existing processes.

Sentin’s intelligent Vision system uses AI-based recognition software and can be easily trained using a selection of test images. The system is capable of segmenting objects, patterns and defects. Even surfaces that are difficult to detect cannot stop the system. Applications can be found, for example, in the automotive industry, such as defect detection on metallic surfaces.

Depending on the application, the AI is trained to detect errors or anomalies. With the latter, the system learns to distinguish good parts from bad. If, for example, a surface structure is inspected, errors are detected by AI deviations from a comparison with reference images. By using anomaly detection and pre-trained models, the system can detect defects based on just a few images of good parts.

For further information https://en.ids-imaging.com