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Walter Automobiltechnik Deploys Automated Quality Control Solutions From Creaform

Walter Automobiltechnik Deploys Automated Quality Control Solutions From Creaform

Creaform has installed a second robot-controlled measuring system at Walter Automobiltechnik GmbH (WAT) in Berlin, Germany. WAT is a system supplier of metal assemblies for the automotive industry. It focuses on complex welded assemblies such as motorcycle frames and engine mounts, with a great deal of its work including motorcycle frames, torsion struts and more for the BMW Group.

WAT recently landed the contract for development and series production of the engine mount for BMW’s new fully electric Mini Cooper SE. When the company needed to measure the vehicle’s complex tubular space frame, the decision fell on the MetraSCAN 3D-R, a powerful robot-mounted optical scanner that is Creaform’s automated quality control solution.

The WAT team uses MetraSCAN 3D-R for fully automated measurement of the complex tubular space frames with many connection points for peripheral equipment. 90 percent of the features were such that they could not be reworked, and they would immediately have caused the production line to stop if they were not made exactly to specification. Due to the high-temperature galvanizing required, the process required that many of these features had to be manually reworked. This means that qualitative safeguarding of the finished parts had to be conducted by carrying out 100 percent of the measurement of the series production within a given cycle time. A measurement report and 3D scan had to be saved for each frame, for traceability purposes.

Tommy Laukdrej, Head of Quality Assurance at WAT explained this: “We use two automated measuring cells with handling robots from Panasonic and the Creaform system, which consists of the MetraSCAN 3D-R scanner, the C-Track optical camera system, and the VXelements scanning software. We chose Polyworks from Duwe3d as the measurement evaluation software, because we have been using this software with success and complete satisfaction for over 10 years.”

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Collaborative Robots Open New Horizons In Quality Control Processes

Collaborative Robots Open New Horizons In Quality Control Processes

Today, with manufacturing in real need of flexible solutions, applications of the latest human and robot collaboration are highly demanded. By: Darrell Adams, Head of Southeast Asia & Oceania, Universal Robots

Across different sectors and regulatory environments, all manufacturers need to ensure consistency of product. Conducting inspections on business-critical systems ensures that the loss of quality and production stoppages are prevented. Collaborative robots (cobots) offer suitable solutions to manufacturers. Hence, cobot-based quality control and inspection systems that can transition between different end products in very little time has become very attractive.

Flexible operation with cobots

Manufacturers are constantly striving to meet the quality control demands of high-mix and low volume production runs. Easy to incorporate into existing production lines and a cinch to program, UR cobots are uniquely positioned to deliver results in fast-moving quality control environments. With the ability to shift from pick and place and handling roles to inspection tasks quickly, cobots are easily reconfigured to inspect new parts. This makes cobots the perfect technology for both future-proofing inspection processes and ensuring business continuity in difficult times. This operational flexibility extends to human-robot collaboration. Human-robot teams will improve the accuracy of quality control operations while human workers can be reassigned to more interesting tasks.

One of the world’s largest manufacturers of bathroom accessories and auto parts, Xiamen Runner Industrial Corporation in China, has installed 64 UR robots to upgrade the efficiency of the production process. Before deploying UR robots, most operations at Runner Corporation were manual with operator fatigue posing risks on both safety and product yield. The company was devoted to developing a highly efficient, flexible, and reliable production line. Ever since the deployment of UR robots, Runner Corporation has witnessed a sharp increase in its product yield while redeployment of staff positions effectively helped reduce the company’s employee turnover rate. The UR robots enabled automated production with unprecedented flexibility.

Improvement of quality and productivity on production lines

Meanwhile, Japan-based Koyo Electronics Industries, a member of the JTEKT Group who boasts the world’s top share in the automotive steering bearings, deployed UR robots to improve quality and productivity. The company has been consistently involved in the development, manufacturing, and sales of electronic equipment since its establishment in 1955, continuing to create products that surpass reliability and functionality standards. In the production of products that require strict quality, the challenge has become how to increase productivity according to an increase in demand.

As such, UR3 cobot was introduced in the touch panel quality inspection process. The cobot works with higher accuracy and stability as compared to human workers, this drives improvement in the quality of work. In fact, for in-vehicle products that require strict quality standards, productivity has also increased 31 percent due to the operational stability of the cobot. The experience from implementing UR cobots has built confidence and high hopes for future development within Koyo Electronics.

Easier quality control (QC) related cobot deployments

UR cobots are proven technologies for quality inspection applications and success stories like these abound. With the launch of the new UR+ Application Kit platform, designed to help manufacturers streamline cobot deployments by providing proven software and hardware for the most popular cobot applications, QC-related cobot deployments are made easier with the addition of kits such as the Q-Span Workstation Kit. The Workstation is a flexible solution for quality control measurement inspection developed by UR partners at New Scale Robotics. The system’s measurement resolution of 2.5 µm (0.0001 inches) enables manufacturers to improve precision, consistency, yield, and quality in small-part measurement.

As customer expectations and demand increases, manufacturers aim to maintain quality standards and focus on delivering products efficiently without sacrificing quality. Whether manufacturers are looking for a way to ensure business continuity or shifting production to new products with different inspection requirements, cobots are ready to help make automated quality control processes easier to deploy and more efficient than ever.

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High-precision Layer Work



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High-precision Layer Work

High-precision Layer Work

Find out how MBFZ toolcraft ensures holistic quality control and precision in additive manufacturing. Article by ZEISS

Frederik Mack, Materials Engineer at toolcraft, examines a test specimen under the ZEISS Axio Imager microscope, which he sawed out of a 3D-printed part and ground.

Additive manufacturing is an uncharted territory for many companies, but not for MBFZ toolcraft GmbH. The company in Georgensgmünd, Southern Germany, manufactures high-end precision parts for the aerospace, automotive, medical technology and semiconductor industries, among others, and since 2011 also parts using 3D printing. The young established production technology is a challenge for quality assurance. Toolcraft is mastering this challenge with ZEISS 3D ManuFACT, the only solution on the market for continuous quality assurance in additive manufacturing.

Heat, noise, the smell of oil: They belong to industrial manufacturing like Yin to Yang. Yet this is quite different in the glass hall at toolcraft in Georgensgmünd. Anyone who has access to the area with their employee ID card hears nothing. They smell nothing either. There are few reminders of factory life as we have known it for a hundred years, because parts are not manufactured the way they have been for a hundred years. Instead of peeling the mold out of cast or forged metal blocks by drilling, milling and turning, additive manufacturing comes at the process from the other way.

Through small windows on the twelve 3D printing machines at toolcraft, you can watch glistening laser beams dancing over a wafer-thin layer of metal powder. Where the spot of light hits, the powder melts in a flash and immediately solidifies again, followed by the next layer. Thousands of hair-thin layers are used in 3D laser melting to create „impossible“ components that could never be produced with traditional subtractive manufacturing. Whereas ten years ago only prototypes and design studies were produced by using additive manufacturing, manufacturers of aircraft turbines, racing cars or medical equipment are increasingly incorporating them directly into their series products. 

Challenges for Quality Assurance

As always, when a new technology emerges in a market, there are always questions. One of them is quality assurance. Jens Heyder points to a monitor that shows two images taken with the ZEISS Axio Imager light microscope at 50x magnification. On the left you can see a section of a good component. There are no large defects visible, only small pores. The material has an even, homogeneous structure. On the right, there is a cross cut shown, in which blowholes and welding defects are present. The construction process here was not optimal, which is why errors occurred during solidification of the melt.

“Crack formation could occur under high loads,” warned Heyder, who has been working as a material engineer in toolcraft’s materials laboratory for three years. Together with his colleagues, he checks the grain size distribution of the metal powder used. They help to optimize the manufacturing process in such a way that no defects occur in the part during melting and solidification. 

However, the materials laboratory is only one component in the seamless quality assurance at toolcraft. Each process step is followed by a test: when a part comes out of the printer, after heat treatment and finally after milling into the final form, before the part is sent to the customer. Not every part is inspected. Random samples are taken according to customer requirements where typical parts only undergo a final inspection. For more demanding customer requirements, such as the aviation industry, 100 percent inspection and precision is required. 

But one thing is for sure: when a part is inspected, it is done on a machine with the ZEISS logo. These can be found in several places in measuring rooms and in production at the company: two microscopes (ZEISS Axio Imager and ZEISS Axio Zoom.V16), several coordinate measuring machines (two ZEISS ACCURA, one ZEISS CONTURA and one ZEISS DuraMax) as well as an optical 3D scanner. Although the latter bears the GOM logo, the company also belongs to the ZEISS family since spring 2019.


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The Importance Of A Calibrated And Traceable Artefact

The Importance of a Calibrated and Traceable Artefact

What is the most accurate way to check if a measuring tool works within its specifications? Guillaume Bull, product manager at Creaform, explains in this article.

When replacing old measuring equipment, it is common to validate that both the old device and the new device measure the same data and provide quality control (QC) with the same results. To do this, correlation tests are performed.

To facilitate and speed up the work, it is tempting to test a regularly manufactured part. After all, its specifications are well known. However, this choice of part may lead to a false diagnosis and an incorrect conclusion regarding the accuracy of the new measuring device.

Therefore, the most accurate way to check if a measuring tool works within its specifications is to use a calibrated artefact for which measurements have been previously validated and the data is traceable.

READ: Quality Assurance Brings New Confidence

Using a common artefact for the old device and the new device helps to minimize the variables that can influence the correlation tests. Among these variables, which will induce measurement differences, are the extraction methods that are different from one technology to another, the alignment methods that are rarely the same, software that does not process or calculate data in the same way, the setups that are generally different depending on the technologies, and the environment that, if not maintained exactly the same, will greatly influence the measurements.

Using a calibrated and traceable artefact enables operators to validate that both devices work within their specifications. As a result, if the measurements taken on this calibrated artefact give the right value, we will know for sure that the measuring devices work properly.


A manufacturing company working in the automotive industry wants to replace its CMM with a 3D scanner. In order to validate the new equipment, a correlation test is performed between the two devices—the old and the new. When the two measurements are compared, there is a difference; the instruments do not correlate with each other. Why? Should we not get the same measurement on both instruments? What is causing this difference? Since we know that the old equipment has been accurate historically, should we conclude that the new equipment has an accuracy issue?

READ: Optimising Aerospace Parts Manufacturing

When testing for correlations between two types of equipment (i.e., comparing the measurements obtained on the same part with two instruments), there are many variables that can induce errors in the measurements. These variables include extraction and alignment methods, software calculation, setup, and environment.

Extraction Methods

We measure the same part, but we do not extract the same points with one measuring tool as we do with the other tool. The consequence is a difference in measurement due to the imperfection of the geometry of the part. Indeed, when we probe a surface plan by taking a point at the four corners, this method does not consider the surface defaults of the plan. Conversely, if we scan this plan, we measure the entire surface and get the flatness. Therefore, if the surface has a slight curve, the scanned plan might be misaligned compared to the probed plan. Thus, there will be a difference in measurement between the two methods.

Alignment Methods

We measure the same part, but we use two different methods of alignment. The consequence is a slight difference in the alignment method, which can lead, due to leverage, to large deviations at the other end of the part. Even if the same method of alignment is used, as mentioned above, a difference in the extraction method of the features used in the alignment can lead to a misalignment of the part. The positioning values are based on the alignment, which must not differ from one instrument to another, neither in the construction method, nor in the way it is measured.

Software Computation

We measure the same part, but we use different software that does not use the same algorithms for data processing. The consequence is a difference in the calculation of a feature from the software, even though the measured data is the same. The more complex the construction of the measurement is, the more likely it is to have deviations between calculations.

READ: A Guide to Machining Better Castings Through Optical Metrology


We measure the same part, but we do not have the same setup on both instruments. The consequence is different measurements of this same part. For example, a part of large dimensions is measured on a CMM. The marble on which the part is placed has an excellent flatness (30 microns). The same part is then measured with a 3D scanning system. But the surface on which the part is put has a different flatness (800 microns). As a result, the part twists and deforms slightly when placed on the second marble. Although the same part is measured, the two setups give different measurements because the support surfaces have different degrees of flatness.


We measure the same part but under different conditions. The consequence is a difference in the measurements. Indeed, if we measure an aluminium part of one meter on a CMM at an ambient temperature of 20 deg C and we measure the exact same part at 25 deg C, then the difference in temperature will result in a lengthening of the part by 115 microns at 25 deg C.

Common Artefact

It is crucial for quality control to minimize these different variables that could lead to correlation errors. The easiest way is to use, on both instruments, a common artefact for which measurements have been previously validated and the data is traceable.

Artefacts have the distinguishing characteristics of being calibrated and traceable. All features have been previously measured and verified in a laboratory, eliminating any doubt and uncertainty regarding measurements.

READ: Creaform Launches 3D Scanning Solution Suite for the Aerospace Industry


A value commonly obtained with a traditional measuring instrument is not a reference value that can be relied upon 100%. The reason for this is that equipment is not an artefact. There is always uncertainty associated with any measuring instrument. Therefore, the verification, validation, or qualification of a measuring instrument cannot be done with any part for which dimensions have not been previously validated.

The only way to certify that a measuring tool works within its specifications is to compare it with an artefact whose dimensions are calibrated in a known laboratory. Only an artefact makes it possible to correlate measurements between equipment because only an artefact can subtract all the variables that could interfere with the measurement. Thanks to an artefact, there is no doubt; the equipment measures accurately.

If two devices get the same measurement with an artefact, but do not correlate on a specific part, then the difference is not attributable to the instruments. Rather, it will result from measurement processes that will need to be checked and scrutinized further to obtain the desired measurement.


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Bruker Interference For Optimal Accuracy

Bruker Interference For Optimal Accuracy

A non-contact, high-resolution and fast measurement technique known as optical interference technology can be used as a measure for development and quality control. By Dr Sun Wanxin, Senior Applications Manager, Nano Surfaces Division, Bruker.

Surface finish plays a significant role in the functions and reliabilities of materials and devices. Understanding surface wear and its underlying causes can be critical to the manufacture and maintenance of automotive and aerospace parts, such as bearings, seals, drive trains, shafts and brake components.

Improving the adhesion energy between coatings and substrates can make parts more reliable. For example, by controlling the surface roughness of engine parts, lubrication can be improved as lubricant trapped on the surface is tailored by surface texture optimisation.

Additionally, by controlling the properties of the surface texture, visual effects can be changed significantly, such as making car paint look premium.

Limitations Of Stylus Profiling

Quantitative measurements of surface finish can be traced back to the 1930s. A tiny stylus was scanned across the sample surface and the vertical movement of the stylus was recorded against the lateral position, forming a line profile.

From the line profile, more than 100 parameters have been defined to describe the surface texture, including commonly used average roughness (Ra), root mean square roughness (Rq), peak counts (RPc) and more.

However, the stylus profiling method has a few limitations. First, stylus profiling is a contact-based technique; there is a possibility of damaging or contaminating the sample. In addition, the size of stylus limits the spatial resolution of this method. Lower spatial resolution may result in measured results that are not relevant to the application. The third limitation of stylus profiling is its limited sampling size, where only a line is measured and important characteristics of the surface might be missed.

To circumvent this problem, most commercial stylus profilers now have 3D mapping, which is performed by scanning multiple lines to form a 3D surface. However, the time taken for one measurement can take hours to perform. This makes it prohibitive to use 3D mapping in routine surface measurements.

Measurements Through Optical Interference

It is highly desirable to have a non-contact, fast, high-resolution, and 3D surface measurement technique for development and quality control. The answer is 3D optical microscopes: these devices measure surface finish through optical interference technology.

A resolution of sub-nanometre in Z and sub-micrometre in XY has been demonstrated on 3D optical microscopes. The typical time used for one measurement ranges from a few seconds to a few minutes depending on the surface roughness.

The 3D optical profiling data gathered would be the equivalent to taking hundreds of parallel line scans with the stylus profilers, which could easily take many hours to complete.

Technical Applications

One unique merit of 3D optical microscopes such as Bruker’s NPFLEX 3D surface metrology system is that the sub-nanometre resolution in Z is independent of the measurement range in XYZ. For some samples, the height variation in one field of view can be up to several millimetres.

The device can also measure sub-nanometre resolution within the 10 mm Z range. In terms of XY dimensions, one measurement can cover an area from tens micrometres to a few millimetres by using different objectives.

If an even larger measurement area is required, the 3D microscope can do a stitching scan, where a series of single measurements will be stitched together to form a large area up to eight inches in XY. In routine measurements for quality control processes, all the measurements can also be automated.

After each measurement, the required surface parameters can be calculated automatically and checked against the preset criteria to report a fail or pass. If robotics is integrated, the 3D optical microscope can also be used as a sorting tool based on part quality.

Data Analysis Provides A Better Understanding

The rich information in the 3D data provides a more comprehensive understanding of the surface.

For example, shape and volume of each corrosion pit can be analysed automatically through one measurement. Spectral distribution and angular distribution of surface finish can be calculated automatically, which is important to understand the root cause of such surface texture and quality control for some products, such as sealing components.

To meet the requirements of different applications, all the surface parameters in ISO standard have been implemented in the analysis software, including commonly used roughness parameters for 2D profile and 3D surface, spectrum for periodicity and directionality analysis of surface texture, geometric parameter extraction, such as height, depth, width, area and volume. To support production environment and eliminate human error, data analysis and data logging can be automated.

In summary, 3D optical profiling provides a versatile, rapid, non-contact characterisation of surface texture for both research laboratories and production floors. 3D optical microscopes are a vital metrology platform for precision engineering, engineering materials, microelectronics, manufacturing, automation and quality control.


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Machine Vision Market To Reach US$18.24 Billion By 2025

Machine Vision Market To Reach US$18.24 Billion By 2025

The global machine vision market is expected to hit US$18.24 billion by 2025 at a 7.7 percent CAGR during the forecast period of 2014 – 2025. And based on a report by Grand View Research, Inc, the ability of machine vision systems to process extensive amounts of data in a just a few seconds is a major factor driving market demand. This is because, it is through this capability that manufacturers are able to achieve milestones in manufacturing products with minimal defects. Furthermore, as the use of robotics in manufacturing increases, vision-guided robotic systems are becoming increasingly common and this is fueling the demand for machine vision systems.

In general, industrial machine vision systems are more robust and demand high reliability, stability, and accuracy as compared to those used in institutional or educational applications and they are relatively cheaper than systems used in military, aerospace, defense and government applications. Thus, there is a greater uptake from industrial sectors when it comes to the adoption of machine vision systems and this has led to market growth for the machine vision industry.

Furthermore, as machine vision systems gain traction in medical and healthcare applications, growth can be seen to increase. This is because, analysis of medical images and robotic applications for carrying various medical activities are key roles of the technology in these sectors.

However, it is the automotive industry that contributed to the largest market share for machine vision in 2017, due to the vital role that the system plays in quality inspection processes.

Overall, Asia Pacific accounted for the biggest market share in 2017 and is expected to have the highest growth rate during the forecast period. This can be attributed to the growth of manufacturing in the region and countries such as China, Japan, South Korea, and India are considered to be potential markets for upcoming technologies, including machine vision. To add to this, factors such as a growing interest in research and development and the expanding manufacturing base in the region are expected to spur the market in Asia Pacific.

However, restraining factors for market growth include a lack of user awareness on machine vision systems and the general complexity that the system entails in integration and usage.


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Market Outlook For Global 3D Laser Scanners

Market Outlook For Global 3D Laser Scanners

According to Research And Markets, the global 3D laser scanners market is expected to grow from USD 2.30 billion in 2017 to USD 5.46 billion by 2026 with a CAGR of 10.1 percent. And factors contributing to this growth are the rising level of eminent control and check up standards offered by 3D laser scanners as well as the significant rise in adoption of 3D laser scanners in different industries and the growing demand for 3D printers globally. However, the high expense associated with 3D laser scanners in the market is also a key factor inhibiting market growth.

3D laser scanners are capable of producing lasers to compute and capture size and shape of free forms in order to generate accurate “cloud points” which are then predicted by specialised software on computers for further probe or study. This is favourable for the probing of contoured surface and complex geometries which mandate accurate data sets in order for effective study and development.

Similarly, 3D laser scanners are pivotal in quality control measures which is in turn an important part of the production process. Currently, some of the key players in the global 3D laser scanner market include Nikon Metrology NV, Hexagon AB, Rapid3D Ltd., Topcon Corporation, Perceptron, Inc., Kreon Technologies, 3D Digital Corporation, Nextengine, Inc., Dewalt Corporation, ShapegrABBer Inc., Wenzel America, Ltd., Riegl Laser Measurement Systems GmbH, Faro Technologies, Inc., Trimble Inc., Basis Software, Inc, Proto3000 Inc., Laser Design, ShapeGrabber Inc., JoeScan, Laser Scanning, Creaform, Wenzel America, Ltd., Dewalt Corporation and Carl Zeiss Optotechnik GmbH.


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