Boxes containing small metal parts are stacked to the ceiling in a narrow bay resulting in barely enough space to manoeuvre a single pallet between the wall and liquid tanks. Behind this assembly, there are rows of tightly packed electroplating tanks.

On the electroplating floor of Collini’s Swiss site near Zurich, Switzerland, space is certainly at a premium. That is why the company, which specialises in surface coatings, was looking for a space-saving solution that would give it a fast and reliable way of hanging small parts on racks for the electroplating bath. The conventional method of loading the racks by hand requires a lot of space and human resources because several racks need to be loaded at the same time.

“For that reason, we wanted to switch to a new coating system with automated loading,” explains Marco Fuchs, Head of Product Engineering at Collini. Since a system of this type has yet to be created, he embarked on a search for companies that would have the pioneering spirit to accept the challenge.

Fuchs found the right partner in Swiss automation company Roth Technik, which in turn relies on smart sensor solutions from Baumer for its projects. A specialist in smart, bespoke automation solutions, Roth Technik collaborated closely with its customer Collini to develop a fully automatic and compact loading line.

At the heart of the line are four robots that automatically load parts onto the empty hooks on the racks. The biggest challenge for the system to overcome was the fact that no two racks are the same. The hook positions are not located exactly in the same place on the welded racks every time, and some hooks may be bent, or missing entirely. This is not a problem for human personnel to deal with, but it is very much for robots that require precise positioning data. The enormous variety and high throughput of parts presented two more challenges.

Robots guided efficiently by a smart Baumer sensor

So how did the Roth Technik team solve the problem of rack position inaccuracy, enabling the robots to learn the exact positions of the hooks for each rack?

The development team found a simple yet effective solution in the compact OXM200 profile sensor from Baumer. Mounted on the robot arm, it detects the exact position of each individual hook as it moves down the rack and reports this back to the robot control. With the help of a camera, the robot then picks up one part after the other from the separating carousel and hangs it on a hook. The robot uses the position coordinates previously collected by the profile sensor to finely adjust the position of the part. This method is what enables the smart profile sensor to guide the robot precisely and quickly on the electroplating rack.

To begin with, Markus Roth’s team tested various solutions with camera-based systems and other laser-based scanners. “In the end, we went with the profile sensor from Baumer because it was the best solution for our strict requirements regarding accuracy, compact design, and ability to detect objects,” states Markus Roth, CEO of Roth Technik. The compact OXM200 reliably detects the thin hooks and is still able to scan several hook positions at the same time. Using the control, it then decides whether or not to load the hook.

Thanks to powerful, integrated measuring tools, the sensor outputs measured the values for the X and Z coordinates directly in mm, significantly reducing the number of calculations in the control. The conclusion is that these smart ultra-compact profile sensors are ideal in applications where space is at a premium, whilst eliminating the need for additional human resources.

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Some trades are passed down from father to son – along with a passion for excellence. When Bruno Mériaudeau speaks about the sophistication of the components produced in his workshop, the sparkle in his eyes and the enthusiasm in his voice, tinged with pride, say it all. This affable and good-humored leader has clearly inherited a deep appreciation for precision engineering.

Méca-Précis was founded in 1975 by his father, driven by a strong entrepreneurial spirit and a desire to put his expertise in highly technical component manufacturing to work. This expertise was honed during his time working for the military, where he designed and produced one-off parts tailored to highly specialised applications. His son joined the company in 1982, at a time when Bruno Mériaudeau was the eighth employee of the family business.

Today, he is preparing to pass the torch to his own son, Nicolas, who took over the management of Méca-Précis in 2023. The company now employs 45 people and operates a fleet of 25 machine tools, 18 of which are CNC-controlled. Over the course of nearly half a century, the company – based in Chatillon-sur-Indre (36) – has continuously strengthened both its technical expertise and its production capabilities.

Méca-Précis has more than one string to its bow. It now specialises in prototype parts, one-off components, small and medium production runs, and welded mechanical assemblies. As a manufacturer of complex parts for the aerospace and satellite industries, the company has also maintained, for 48 years, the trust of a global leader in carton packaging machinery, for whom it produces parts and complete sub-assemblies.

While having the expertise and equipment to manufacture sophisticated components is essential, ensuring these parts meet stringent dimensional requirements is equally critical. To this end, Méca-Précis operates a standard measuring machine on the shop floor, as well as a coordinate measuring machine (CMM) housed in a thermally controlled environment. However, certain aerospace and space-sector clients require 100% inspection of all dimensions on every single part produced, both before and after surface treatment.

When inspection becomes a bottleneck in production

“Dimensional inspection of a single pin takes just one minute – but there can be as many as 300 to check. At the other end of the spectrum, inspecting a single complex component for a satellite can require up to 80 hours,” explains Nicolas Mériaudeau.

In this context, as production volumes increased and multiple palletised machining centres operated through the night, the coordinate measuring machine was no longer able to keep pace. “Our two inspectors were overwhelmed. To maintain a high level of service and manufacturing quality, and to ensure reasonable lead times for our customers, we needed to find a solution to eliminate the bottleneck in the inspection process. We therefore began searching for a way to automate and roboticise the inspection process,” explains Bruno Mériaudeau.

As the manufacturer of the coordinate measuring machine (CMM) used by Méca-Précis was unable to provide a suitable solution, Nicolas Mériaudeau turned to Mitutoyo. Mitutoyo proposed the design of a robotic measurement cell integrating the MiSTAR coordinate measuring machine, in collaboration with Engineering Data, a company specialising in fixturing solutions and the automation of machining centres.

Deployment of the robotic measurement cell

Less than a year after the initial meeting between the teams from Mitutoyo, Engineering Data, and Méca-Précis – with both quality inspectors closely involved throughout the project—the robotic measurement cell was installed in the workshop. Following phases dedicated to developing part inspection programs, system commissioning, configuration, and technical fine-tuning, an additional six months were required before the system became fully operational.

“We have effectively removed the bottleneck that was located in the quality control process. This solution brings us greater flexibility and allows us to significantly increase inspection capacity,” says Bruno Mériaudeau with satisfaction.

“If we did not have this robotic measurement cell, we would not be able to cope with the growing production volumes of series-manufactured parts, which are highly demanding in terms of quality control. We now have a solution that fully meets our needs. Throughout this project, we benefited from the quality of exchanges, responsiveness, attentiveness, and geographical proximity of the Engineering Data and Mitutoyo teams,” adds Nicolas Mériaudeau. As a result, the pressure that had been weighing on Méca-Précis’s two inspectors has been significantly reduced.

They can now rely on two measurement solutions to perform all the necessary checks in-house. The robotic cell has significantly reduced their workload by performing automated inspections during the day as well as overnight. Before leaving the workshop, they can load parts into the robotic system, which then carries out the inspections automatically in their absence.

Architecture and operation of the robotic measurement cell

This solution is the result of Engineering Data’s expertise in machine tool loading automation, combined with Mitutoyo’s know-how in dimensional control. The robotic measurement cell is installed within an enclosed structure, defined by glass panels that ensure operator safety while providing full visibility of the system’s internal operation. The cell integrates a multi-axis articulated robot responsible for handling operations, a Mitutoyo MiSTAR coordinate measuring machine designed for shop-floor use, and an automated storage unit capable of accommodating up to 20 pallets on which the parts to be inspected are secured. A loading station, accessible from outside the cell, allows interaction with the operator without interrupting overall operation.

The process begins with the loading phase. The operator places a pallet carrying a part onto the dedicated loading station. Each pallet is designed to hold the component in a position compatible with robotic handling and measurement operations. Using the cell’s human–machine interface, the operator selects the relevant part type. This information is transmitted to the cell’s control system, which automatically associates the component with the corresponding control program. The robot then picks up the pallet and transfers it to the storage unit. This operation can be repeated until the storage system is fully loaded.

Once the pallets have been loaded, the operator initiates the inspection cycle via the interface. The cell then operates autonomously. The robot successively retrieves the stored pallets and places them on the surface plate of the CMM, which is equipped with a clamping device ensuring proper positioning and stability during measurement. The coordinate measuring machine executes the inspection program associated with the part, performing the required dimensional measurements. The duration of this phase depends on the number of features to be checked and the complexity of the component, ranging from a few minutes to several hours.

At the end of the inspection, the robot retrieves the pallet and returns it to the storage cabinet. The cycle then continues automatically until all loaded parts have been inspected. The measurement results are recorded by the system and can be reviewed later by metrology engineers.

The overall operation relies on coordination between the control system, the robot, and the measuring machine. The automation of pallet handling allows the loading operations to be decoupled from the measurement phases, ensuring continuous use of the control equipment while reducing manual handling.

A robotic mandrel gripper, integrated by KOCH Robot Systems, ensures the precise and controlled transfer of rolls to the RoRo StretchPack packaging machine for the wrapping process. This combination of robotics and horizontal stretch hood wrapping technology provides stable and precise control, for wrapping rolls with significant variations in diameter (up to ø850 mm) and length (up to 700 mm).

Designed for controlled and accurate roll wrapping

The robotic mandrel gripper transfers each roll from a conveyor and positions it inside a five-sided stretch hood film prepared in the RoRo StretchPack packaging machine, and carries the roll through the packaging machine, placing it on the output conveyor. The mandrel is released and returned before the final welding of the film end for complete sealing of the roll packaging.

This solution is especially beneficial in cases where conventional belt conveyors are unsuitable or when products type require precise positioning.

Flexible packaging solution for sealed packaging

A key feature of RoRo StretchPack is the delivery of fully sealed packaging, with welded film ends providing reliable protection against external contamination. This capability is crucial for sensitive products such as paper, hygiene materials, and nonwoven rolls, ensuring product integrity during storage and transport.

The flexible design of the RoRo StretchPack packaging machine integrates seamlessly with a wide range of input and output systems, including robotic mandrel grippers. This adaptability allows for tailored packaging lines that meet specific customer requirements.

In modern aircraft production, precision is everything. Every hole and every fixing point must be precisely positioned to ensure safety and quality. As part of the DiCADeMA project (Digital Cabin Architectures and Design for Manufacturing) led by the German Aerospace Centre (DLR), a novel, fully digitally networked process has been developed.

Through intelligent automation, this approach elevates aircraft cabin manufacturing to a new level. A key component in this process is an Ensenso 3D camera from IDS Imaging Development Systems, which ensures highly precise detection and alignment of drilling positions.

Digital process chain from design to production

The aim of the project is to establish a continuous digital thread from design to production. Changes to the cabin design, such as seat spacing and the associated new position of the luggage compartments, are recorded directly in the digital design data and automatically transferred to production planning. Simulations allow these variants to be validated before any physical component is manufactured. Once digital validation is complete, production can begin immediately.

To make this digital process tangible, an automated system for marking drilling positions was developed on a mock-up of an aircraft frame structure. Several networked systems work together in this setup: An autonomous mobile robot (AMR) approaches the frame and positions itself near the target area. Mounted on the AMR is a lightweight robot that moves the marking unit, including the 3D camera, into the acquisition position. At this point, the Ensenso camera takes over the fine alignment. An integrated Manufacturing Execution System (MES) controls all sub-processes.

The role of the 3D camera

The camera used, an Ensenso N36, captures the environment as a three-dimensional point cloud and matches it against the CAD data of the aircraft frame. In this way, even the smallest deviations between the target model and the actual geometry can be detected. The system uses this data to calculate precise correction values, which are transmitted to the higher-level MES.

Communication takes place via a standardised OPC UA interface, ensuring reliable and secure data exchange between the camera, the robot and the control system. The MES translates the acquired data into concrete control commands for the robot, which then performs the marking of the drilling position.

The autonomous robot achieves a positioning accuracy of around five millimetres. This allows the camera to reach the acquisition position without risk of collision.

The Ensenso camera becomes a key link between digital design and real-world manufacturing: It recognises local geometries, in this case several rivets and the surface on which they are set and compares the captured point clouds with the reference data from the CAD. This comparison is made possible, among other things, by hand–eye calibration and an iterative minimisation process. The result is a transformation matrix that precisely describes the correction required for the drilling position. By applying this correction value, the drilling position can be set precisely.

An operator follows the vehicle and drills the hole immediately afterwards at the marked spot. This process is repeated for each installation point, while robots and humans can work safely in close proximity to one another.

For this application in aircraft manufacturing, a compact camera with a very short working distance is required in order to keep the path from the acquisition position to the drilling position as short as possible. This helps to maintain high accuracy and avoids excessive robot movements. The Ensenso N36 meets these requirements. The Ensenso N series has been specially developed for use in demanding environmental conditions.

Thanks to its compact design, the camera can be installed in a space-saving manner, either in a fixed position or mounted on a robot arm. This makes it equally suitable for 3D capture of both moving and stationary objects. The integrated projector ensures high-contrast texture even under challenging lighting conditions: It projects additional structures onto the object surface using a pattern mask with a random dot pattern, thereby supplementing missing or weak features. All cameras are pre-calibrated at the factory and can therefore be put into operation quickly and easily.

Benefits for manufacturing

The digital process offers the DLR several advantages. Camera-based alignment significantly increases precision and repeatability. At the same time, continuous data acquisition enables complete documentation and traceability of all process steps. Assembly personnel are relieved, as the robot takes over the time-consuming task of position determination, allowing skilled workers to focus on the actual assembly operation. In addition, production times are significantly reduced, as manual measurements or readjustments are no longer necessary.

The demonstration on the mock-up clearly illustrates the potential that lies in combining the digital process chain, robotics and 3D image processing. In further project steps, the accuracy of the system and the performance of the evaluation algorithms will be examined in greater detail. This will involve not only the camera itself, but also the optimisation of the mathematical methods used to align nominal and actual point clouds.

What is currently being tested in aircraft manufacturing may also be applied in other industries in the future. The system impressively demonstrates how optical sensor technology and intelligent software are paving the way for a new era in manufacturing: networked, efficient and precisely on target.

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Capable of handling up to 14 bundles of flour per minute across two production lines, the equivalent of between 56 and 168 individual bags of flour every minute, the new system is already playing a key role in supporting increased production volumes and future growth.

Designed to work alongside an existing Endoline palletiser dedicated to one of the site’s two production lines, the upgrade forms part of a broader automation strategy at the facility. The mill operates two filling lines producing both individual 1-2kg bags and larger 18kg shrink-wrapped bundles. The original system, installed five years ago, manages the individual bags from Line 1. This left Line 2’s individual bags, together with the bundles from both lines, requiring a more flexible palletising solution.

Engineered to accommodate both product formats, the system also incorporates the automatic handling and placement of wax paper interlayer sheets. Bundles are conveyed from both lines at speeds of up to 14 per minute per line, equating to a combined throughput of up to 28 bundles per minute. In addition, individual 1-2kg bags from Line 2 are presented at rates of up to 70 bags per minute.

Driving flexibility to support business growth

The replacement project was driven by the need to overcome limitations within the previous palletising operation, which lacked the flexibility to efficiently handle varying bundle sizes and evolving product formats. As the mill expanded its product range and customer requirements for bundle sizes became more diverse, a more adaptable solution was required to support continued growth.

Combining advanced palletising technology with a fully engineered conveyor network, the system enables both bundled flour products and individual packs to flow seamlessly from packing through to pallet build. By automating what were previously labour-intensive and physically demanding tasks, the flour mill has improved operational efficiency, consistency and working conditions across the site.

Integrated palletising and conveyor system

At the heart of the system is a palletising solution capable of managing product streams from the two filling lines. Bundles and individual packs are transferred via a series of accumulation and transfer conveyors, designed to buffer product flow and maintain a continuous feed into the palletising area without disrupting upstream packing operations.

Operating across the two bundling lines, the palletising system can handle up to 14 bundles per minute per line, delivering high-volume throughput while maintaining precise pallet builds and load stability ready for downstream handling and distribution.

While the palletiser can manage the simultaneous pick-up of bundled products from both lines, it requires a straightforward re-tooling process when switching to palletising individual packs of flour, which are fed down the middle conveyor. This quick-change capability allows the mill to move efficiently between product formats in line with production schedules and changing customer requirements.

To minimise downtime during product changeovers, the tooling transition is carried out automatically via the system HMI. The robot docks its current end-of-arm tool, releases it and automatically connects to the alternative tool, ensuring rapid and controlled transitions between bundle and individual pack handling.

Replacing legacy systems with adaptable automation

“Our customer needed a solution that could replace their existing palletising system with something far more adaptable and capable of supporting long-term growth,” comments Suraj Patel, UK Sales Manager, Endoline Robotics. “By integrating high-speed palletising with a tailored conveyor layout, we’ve delivered a flexible operation that can handle different product formats, varying bundle sizes and increasing volumes.”

While enabling the site to move away from manual-intensive tasks, flexibility has been a central design principle throughout the installation. The modular conveyor layout allows for future expansion and capacity increases, while the palletising system can be easily adapted to accommodate new pack sizes, bundle formats and pallet configurations as the business continues to evolve.

“Modern food manufacturers need automation that delivers both performance and adaptability,” Suraj adds. “This project shows how replacing legacy systems with flexible technology can improve efficiency today while providing the capacity to grow tomorrow.”

Building on a long-term partnership

Although the latest installation represents a major upgrade, it builds on an established partnership between the flour milling business and Endoline. In 2020, Endoline delivered a robotic palletising system at the company’s UK-based mill to support a sharp increase in retail demand during the pandemic, enabling production of more than 167,000 bags of flour per week and improving pallet quality and operational continuity.

That earlier project helped shape the company’s wider automation strategy and demonstrated the long-term benefits of palletising technology within the milling environment. With a long-established milling heritage, the business continues to invest in modern manufacturing solutions to remain competitive in a rapidly changing food production landscape.

The palletising and conveyor upgrade reflects this industry trend, providing the flour mill with a future-proof solution that supports current operations while enabling continued growth.

A long-standing automation partnership between a Swiss machine builder and one of the world’s leading manufacturers of industrial robots is aiming to help transform the pharmaceutical supply chain in Europe with the launch of what is believed to be the ‘smallest’ automated palletising cell for vials and pre-filled syringes.

Swiss-based Robotronic has partnered with Mitsubishi Electric’s Factory Automation EMEA division for more than two decades. Now, the two organisations are collaborating together on a new low-footprint cell to help the pharmaceutical industry overcome record-high shortages across Europe in recent years for medicines ranging from children’s cough syrups through to antibiotics and even cancer treatments.

The growing demand, which has impacted patient treatment and quality of life, has led the European Medicines Agency to increasingly focus on one of the main causes of shortages – manufacturing and quality issues – with the aim of ultimately strengthening the fragile pharmaceutical supply chain.

Mike Weber, founder of Robotronic, says faster production is required to shorten lead times and cope with the ever-increasing demand. “We are a Swiss company concentrating on machine building with robotic applications for the pharmaceutical industry, including everything from de-nesting and re-nesting, through to de-traying, re-traying, and palletising. We have specific expertise in vial and pre-filled syringe handling, offering solutions that deliver maximum efficiency with a small footprint, and enabling pharmaceutical manufacturers to rise to the challenges in their supply chain.”

One of the key challenges for Robotronics is compliance. “Pharmaceutical consistency is about more than quality,” says Mike. “It is also about regulatory compliance and safety.

“To get the required productivity, we need two robots working very closely together at high-speed, but we also need the assurance that the delicate products being handled will not be damaged in the process.”

The Robotronic choice is Mitsubishi Electric, specifically the FR series, a highly flexible robot with compact arm sizes that is equipped with SoftTouch technology.

The result is a small footprint automation solution with increased productivity for handling pallets as small as 120cm x 80cm. Most importantly, the FR series has built-in compliance control that offers soft touch capability that delivers zero product damage with no glass-to-glass contact, no broken glass and is easy-to-clean.

“The challenge was to have two robots operating side by side in a confined environment without compromising speed or precision,” says Mike. “With Mitsubishi Electric’s help, we have two robots driving at full speed within millimetres of each other with no possibility of collision. This enables our cells to process up to 600 products a minute, without really challenging the robots.”

He concludes: “The relationship between Robotronic and Mitsubishi Electric is a true technological partnership – a combination of deep pharmaceutical process expertise allied to best-in-class robotic technology. Together, we believe we can develop machines that can shorten lead times and create a more robust pharmaceutical supply chain.”

Stefan Knauf, Division Manager at Mitsubishi Electric Factory Automation – German Branch, adds: “The biggest challenge was enabling Robotronic to safely and continuously operate two robots side-by-side in a confined environment, without compromising speed or precision. Our FR series robots with additional servo axis perfectly matched their requirements to deliver high throughput from a small footprint.

“The unique, built-in compliance control also allows the robots to gently handle glass vials without the risk of damage. Ultimately, in pharmaceutical production, consistency isn’t just about quality, it is about regulatory compliance and safety. Our relationship with Robotronic is a true technological partnership. Mike and his team bring deep pharmaceutical process expertise and we bring robotics innovation.”

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Like many other industries, the woodworking sector faces a variety of challenges. These include quality assurance, untapped efficiency potential, and a shortage of skilled workers. One possible response is further automation. Automation can reduce errors, improve quality, and increase efficiency. In addition, production can be increased and accelerated because machines can operate 24/7 and perform quality control faster and more precisely than humans. Finally, the increasingly scarce human resources can be deployed more purposefully by automating monotonous and physically demanding tasks.

HOMAG Bohrsysteme has developed an automated solution that addresses these challenges. The company is part of the HOMAG Group and provides customers in the woodworking industry with a wide range of support options through its high-tech machines and systems. Its product portfolio includes CNC machining centres, through-feed drilling machines, drilling and dowel-insertion machines, as well as machines for drilling and fitting insertion technology.

The newly developed solution focuses on fully automated loading of a vertical CNC machining centre. At the literal centre of the system is a robot that picks wooden workpieces from a stack, feeds them into the CNC machine, and removes and places them after processing. The key feature is that the workpieces are all individual and their shape and size are not known in advance. In addition, they are arranged chaotically on the stack. Furthermore, not only are the workpieces different from one another, but each must also be drilled individually. The relevant information is stored in a barcode on the workpiece.

Machine vision enables processing to take place completely autonomously despite these challenges. With the help of the machine vision software MVTec HALCON, the robot can recognise the different workpieces and grasp them safely. The software executes numerous algorithms and also reads the barcode information on the workpieces, forwarding it to the CNC machine. Based on this information, the required, different drilling operations are carried out.

Fully automating a labour-intensive process step

Such a fully automated cell developed by HOMAG is in operation at the carpentry workshop of MAB Möbel AG. The company from Muotathal, Switzerland, has been producing quality furniture since 1951 based on ecological and design-oriented principles.

“We want to continue developing with solutions that truly make sense. The further development of the cell with laser scanning and chaotic stacking was the function we had been waiting for. This allows the cell to meet our goal of batch size 1 production – and only then does automation make sense for us,” explains Luca Zingg, member of the management board responsible for corporate development at MAB.

Until now, an employee handled the loading of the CNC machining centre. This involved picking up the workpieces, scanning the attached barcode, placing them into the CNC machine, and depositing them on another pallet after processing. After several hours, this monotonous task becomes physically demanding and is not particularly efficient in terms of profitability.

Tobias Schwarz, Senior Director Product Development at HOMAG Bohrsysteme, explains the goal of the automation: “MAB has set itself the objective of increasing productivity, deploying employees more effectively – and above all in less physically demanding workplaces – and thereby reducing costs.

Another advantage of a fully automated production process is that the workpieces no longer need to be sorted before processing, since the application can also handle chaotically arranged stacks. This saves time in the upstream process step, which further increases productivity.”

The challenge during implementation was to develop a completely new solution, as nothing like this previously existed on the market. The task is also not easy for the machine vision system. This is due, firstly, to the enormous variety of workpieces – different surface decors must also be processed. Secondly, the image processing must function under ambient light. Because not every area is fully illuminated, less powerful vision systems may have difficulty determining the exact position of the workpieces. Finally, it is technically demanding to separate the surfaces of relatively flat boards.

“Despite these challenges, it was clear that such a fully automated solution had to be based on machine vision. We had to teach the robot to see. With other technologies, such as sensors, practical implementation would be virtually impossible – particularly in terms of speed,” explains Schwarz.

Enabling the robot to recognise individual workpieces

The application consists of several hardware components. At its core is a six-axis robot. A vacuum surface gripper system is used as an end effector. A 3D laser scanner is also mounted on the robot’s gripper arm. The drilling operations take place in the DRILLTEQ V-310 CNC machining centre from HOMAG. The machining centre offers a wide range of options for precise processing of wooden workpieces.

For the machine vision software, HOMAG chose MVTec HALCON. “We have been working with MVTec’s software for some time. HALCON has a huge pool of machine vision operators that allow virtually all machine vision applications to be implemented robustly. In addition, the software is flexible when it comes to combining different hardware components. And if technical questions arise, you can simply contact MVTec’s customer service,” explains Schwarz regarding the decision.

At MAB, the production process proceeds as follows: An employee places wooden workpieces onto an unknown and chaotic stack in the work area. The robot then moves over the stack so that the 3D laser scanner can scan it from above. The laser scanner then creates a 3D point cloud – a highly precise three-dimensional representation of objects consisting of numerous individual data points.

After image acquisition, the machine vision software MVTec HALCON extracts the top layer of wooden workpieces from the 3D point cloud and determines the spatial position of each individual workpiece. A stacking algorithm then calculates the optimal order in which the robot should remove the workpieces. This is an important detail because an unevenly unloaded stack could collapse. The robot then begins its work, removing the wooden workpieces according to the calculated order and transferring them to the CNC machining center. Before this, the 3D laser scanner captures a 2D image of the code. MVTec HALCON reads the code and transmits the information to the machine.

The workpiece is then processed according to this information. Afterward, the robot picks up the workpiece again and places it on the target stack.

Multiple image processing tasks

“We are seeing machine vision becoming increasingly popular in the woodworking industry and among carpentry workshops. Our software, MVTec HALCON, offers numerous methods – for example for inspection tasks or for collaboration with robots – that can sustainably support automation and digitalisation in this sector,” says Jan Gärtner, Product Manager HALCON at MVTec.

For the robot in the MAB system to work autonomously and grasp the workpieces precisely, the machine vision software must perform several tasks. First, MVTec HALCON converts the 3D point cloud into information for further processing. For this purpose, HALCON uses 3D object models. This central container forms the starting point for creating a coordinate system within the machine vision software, which is then transmitted to the robot.

Various HALCON operators first determine the distance from the gripper to the pallet, then calculate the top layer of workpieces, and finally determine the precise position of each individual workpiece. These positions are integrated into the coordinate system of the HALCON machine vision software and transferred to the robot.

During the 3D scanner’s capture of the top layer of the pallet, it also records 2D images. HALCON uses these images to read the information from the barcode attached to each workpiece. The challenge here is that the captured image is quite large, while the barcode region is correspondingly small. Reading such small barcodes is a major challenge for any industrial image processing software.

“The image-processing part of the implementation was not entirely trivial. Because of the flat boards, we had to combine 2D and 3D methods. This was possible with HALCON and significantly simplified the implementation,” explains Schwarz.

The system went into operation at MAB Möbel AG in summer 2025. “Thanks to the close coordination with the partners involved, we were able to achieve very good results right from commissioning. The system is now operating very reliably, which makes us very satisfied and gives us confidence for the future,” explains Luca Zingg.

“The increased level of automation significantly relieves MAB, as the employees who previously carried out this task can now focus on other, more important activities. At the same time, this solution represents an important development for us, because it allows us to significantly increase the automation level of our core machines and thus offer customers additional added value,” adds Tobias Schwarz, continuing: “Machine vision plays an important role here, because the technology acts as an automation enabler. In our collaboration with MVTec, we see the opportunity to offer our customers first-class and reliable solutions.”

In one application, SMC’s customer was using hundreds of metres of cabling to control cobots on a 40 metre production line, resulting in complex looms. These were time-consuming to build, added weight to the robot armature, created additional costs for maintenance and unplanned downtime due to cable failures through wear and tear.

By adopting SMC wireless systems the customer successfully eliminated the cable looms – cutting costs and improving cobot build time. SMC also converted all other manifolds on the line to wireless, further improving the benefits.

The customer is enjoying significantly lower costs for build time, labour and materials, improved commissioning time as well as reduced maintenance and downtime.

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The automation programme began in 2018, when Hanover introduced its first collaborative robot to improve the accuracy and efficiency of testing electronic boards used in its LED passenger display systems. Working with automation integrator Absolute Robotics, Hanover deployed Techman collaborative robots to automate the repetitive and highly precise testing process.

Since then, the system has expanded significantly. Today, 11 Techman robots are installed at Hanover’s Lewes manufacturing facility, including TM5-900 and TM12 models, supporting continuous inspection and testing operations across multiple lines.

Automating quality control

Hanover Displays manufactures passenger information and LED destination displays used by transport operators worldwide. As the company brought PCB production back in-house, it needed a reliable way to test and inspect thousands of circuit boards each year. Previously, this process required manual handling and constant operator attention.

The introduction of collaborative robots transformed the testing workflow. Equipped with integrated vision systems, the robots load boards, operate test equipment, verify LED sequences and record the results of each test. This automation enables consistent cycle times and supports unmanned operation, including overnight production runs. The introduction of the cobots has gained significant data and insights to help improve their first-time pass rate from 94% to 99.5%, strengthened department collaboration, and enhanced how Hanover design and test new products.

Proven reliability over eight years

One of the most significant findings of Hanover’s cobot deployment has been the proven reliability of the Techman robots in daily production.

Reece Mills, Sales and Operations Control Manager at Hanover Displays, commented: “Since installing the first Techman robot in 2018, the reliability has been exceptional. In eight years of operation across our cobots, we have only experienced a single joint failure. That level of performance really demonstrates the quality and robustness of the TM robots.”

The collaborative robots have allowed Hanover to maintain extremely high testing accuracy while freeing skilled employees from repetitive tasks and enabling them to focus on higher-value production activities.

Partnership driving automation success

The automated testing solution was delivered by Absolute Robotics, an automation specialist and integration partner for LG Motion. Together, the companies developed a flexible system capable of handling the wide variety of board sizes and configurations produced by Hanover.

By combining collaborative robotics with custom tooling and automated test equipment, Hanover achieved significant gains in productivity and quality assurance, including improved traceability and the ability to run automated tests around the clock.

Reaching one million automated PCB board tests represents a major milestone for Hanover Displays and highlights the long-term value of collaborative robot automation in electronics manufacturing.

The project demonstrates how advanced robotics can deliver consistent quality, improved efficiency and long-term reliability in demanding industrial environments.

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The food industry is experiencing a transformative shift in quality control, due in part to advances in artificial intelligence (AI). When combined with rule-based machine vision, AI is enabling automation of processes that were previously impossible, unlocking new levels of productivity and quality assurance.

Cheese consumption is booming globally, and producers are facing increasing challenges as they scale production. Labour shortages, particularly in Europe, are pushing dairies to adopt automation to increase efficiency. Meanwhile, sustainability is becoming a central concern, with an increased focus on reducing waste and conserving resources. Additionally, consumers are demanding higher-quality products with more variety, further intensifying pressure on producers.

As Eberle’s Machine Vision Engineer, Dorian Kopfle, explains: “The cheese-ripening process, which can last up to 14 months, requires constant monitoring to avoid mold and ensure quality. Manually inspecting thousands of cheese wheels is virtually impossible, which is why Gebr. Baldauf, a traditional dairy, turned to us for an automated solution.”

Automation with machine vision and AI

Gebr. Baldauf, located in the Allgau region, commissioned Eberle to solve these challenges. The result is a fully automated monitoring system, that combines a mobile care robot, cameras, and onboard image processing.

The process begins with the inspection of cheese wheels for defects, such as mold spots or blemishes. A 4K camera captures high-resolution images, which are analysed using advanced machine-vision algorithms from MVTec HALCON. The software uses deep-learning methods to detect anomalies earlier, minimising process deviations and waste. The data is stored and made available via a web interface, enabling remote monitoring and control. Simultaneously, the mobile care robot performs its task of treating the cheese wheels, ensuring proper rind formation and removal of unwanted smear layers.

This system not only increases efficiency by reducing manual inspection but also improves the consistency and quality of the final product.

Key outcomes and business impact

The deployment of this automated system has provided several key benefits for Gebr. Baldauf, including:

• Increased efficiency: The mobile care robot operates autonomously, reducing manual labour while ensuring that each cheese wheel is inspected and treated thoroughly.
• Waste reduction: Early detection of mold or defects allows for timely intervention, preventing rejected cheese and minimising waste.
• Improved quality control: The system ensures more consistent and less subjective inspection results by replacing manual methods with AI. As a result, the process achieves a 100% inspection rate, applying the same inspection criteria throughout.
• Full traceability: The integration of industrial image processing ensures complete product traceability. All inspection results are stored digitally for easy access, enabling better decision-making and long-term process optimisation.

Overcoming technical challenges with AI

A significant challenge in developing this system was the natural variability of cheese. Every wheel looks different and undergoes significant changes during the ripening process, which makes rule-based machine vision methods less effective. To overcome this, Eberle utilized AI and deep learning to create a system that could adapt to the unique characteristics of each cheese wheel.

The MVTec HALCON software was instrumental in this process. By training a deep-learning network with a large dataset of cheese images, the system is able to reliably detect defects such as cracks, mold, and discoloration, while ignoring the natural variations inherent to the process. This technology ensures that even subtle anomalies are spotted, allowing for earlier intervention and better quality control.

Eberle’s goal was not only to automate the inspection process, but to fully integrate AI into the cheese-ripening workflow. Currently, the system is capable of performing real-time inspections and autonomous care, with minimal human involvement. However, the company is working on refining the system further to handle all types of cheese and stages of ripening, with the long-term goal of creating a fully automated, AI-driven system that requires no human input.

The system also provides a solid foundation for future digitalisation efforts, with the potential for integration into larger digital platforms, such as ERP systems and the cloud, to further optimise the production process.

Scaling and further digitalisation

Building on the success of this project, Eberle is now focused on scaling the solution to meet the needs of the entire cheese industry. The company plans to standardise the system and integrate it into both mobile and stationary care robots for cheese production worldwide.

Furthermore, the system’s AI capabilities are continually evolving. Eberle aims to refine the deep-learning models to handle different cheese types and ripening stages, enabling fully automated classification and inspection. This will allow producers to further reduce human involvement while maintaining the highest standards of quality.

As Christoph Muxel of Eberle summarises, “Our machine vision-based solution demonstrates how automation can sustainably improve quality, efficiency, and competitiveness in the food industry. This project is just the beginning, and we’re excited to take these innovations to a global scale.”