IFOY Test Report: AGILOX ODM

In the run-up to the handing out of the IFOY Awards in Dortmund on June 22nd, we run through all the 2023 finalists and share the verdict from the IFOY test conducted during the evaluation by an expert jury in March. Our first entry (alphabetically speaking) is the AGILOX ODM from AGILOX.

Category: AGV / AMR

IFOY test verdict

Summary: The new AGILOX ODM omnidirectional dolly mover is an intelligent logistics robot for small load carriers. Thanks to the proven X-Swarm Technology by AGILOX integrated in the vehicle, it independently finds the fastest route through the production or logistics environment in real time.

Description: The new AGILOX ODM ensures the production supply with small parts. From now on, users can transport small load carriers such as containers or dollies with dimensions of 600x400mm and a maximum weight of 300kg from one station to the next and fill rails. As with other products in the AGILOX range, there is no need for additional infrastructure or navigation aids such as magnetic strips on the floor. Freely navigating and completely autonomous, the ODM enables production lines to be supplied flexibly. In this way, users set a new standard of agility in their production or logistics. With its omnidirectional travel system, even trips through the narrowest aisles are no problem for the AGILOX ODM.

Innovation: The new AGILOX ODM is part of an entire product group, which means that even driving with other vehicle types of the AGILOX family in combination is possible without any problems. Compared to similar products on the market, the AGILOX advantage is that it does not require additional infrastructure or navigation aids. Furthermore, our product innovation impresses with its omnidirectional drive system, which allows not only forward and backward movements, but also turning at a standstill or parallel movements. Numerous safety sensors ensure 360-degree personal safety.

Market relevance: The AGILOX ODM is particularly relevant for the pharmaceutical and electronics industries. Monotonous tasks no longer have to be performed by (over)qualified employees, but can henceforth be handed over to the intelligent logistics robot. The company is thus closing the gap from partial automation to full automation. AGILOX estimates the market potential for its own company at around €30 million.

Main customer benefits: AGILOX relies on the motto “Plug&Perform”. The first AGILOX can be put into operation in less than twelve hours, and each additional vehicle in just 15 minutes. Increasing demands should be child’s play for the intelligent intralogistics robot, which is unique in a market comparison, according to AGILOX.

The name says it all. AGILOX takes changing environmental or process conditions lightly.  Sounds exciting, and it is. After all, an AGILOX can also operate at different levels if it is connected via a lift. And even narrow aisles or oncoming traffic cannot harm the all-rounder. The advantage is obvious. Operating space costs money, and customers want to spend it on more sensible things.

IFOY Innovation Check

Market relevance: The new ODM vehicle developed by AGILOX automates the transport of floor rollers in the 400x600mm or 600x800mm format, on which stacked containers or comparable load carriers are transported. The market for this type of transport, correctly located by AGILOX itself in the pharmaceutical and electronics industries, is highly relevant there. However, transports with floor rollers and containers are by no means used in all companies, which is why the market relevance is only rated as balanced.

Customer benefit: The high manoeuvrability of the very compact vehicle and the software, which is designed to be easy to use, provide a high benefit for the user. The software demonstrates the provider’s extensive experience with autonomously operating vehicles, which are also well coordinated by the software as a fleet of different vehicle types from AGILOX on the same operating area.

Novelty / Innovation: In the vehicle class for transporting ground scooters with containers, solutions already exist, but the extremely compact design combined with the surface mobility of the ODM is definitely to be assessed as new. Since the technical solutions and the functions are already known from other vehicles of the same supplier and its market companions, an evaluation as extraordinarily innovative is not possible.

Functionality / Type of implementation: The presented vehicle offers relevant functions for the user, in particular autonomous functions for avoiding obstacles on the route or for reacting during load pick-up if load carriers are not precisely provided. A precise approach to the defined target positions is also possible during load delivery. In the demonstration, the functions mentioned were impressively and reliably demonstrated.

Verdict: Vehicles like the ODM have a market but transports with floor rollers in the 400x600mm or 600x800mm format are far from being used in all companies. The high manoeuvrability of the vehicle and the software, which is designed for easy operation, deliver a high benefit for users. In this extremely compact form combined with the surface manoeuvrability, the vehicle is new and offers relevant functions for the user.

Market relevance Ø
Customer benefit ++
Novelty / Innovation +
Functionality / Type of implementation ++
[KEY: ++ very good / + good / Ø balanced / – less / — not available]

IFOY FINALIST FOCUS: Pallet Classification System from SICK

The next in our look at all of the IFOY Award nominated finalists ahead of the winners announcement on 30th June at BMW World is a focus on the PACS (Pallet Classification System) from SICK.

IFOY Category: Special of the Year

Description

SICK’s deep learning-based pallet identification system PACS is used for automated recognition of pallet types. The automated recognition simplifies the process of automatically tagging different pallet types and can be easily integrated in many locations due to its compact design and small footprint.

The hardware of the system consists of two colour cameras for image acquisition, a light barrier array for triggering, and a controller for processing the data and executing the trained neural network. Optionally, other SICK sensors (e.g. barcode scanners) can be integrated to realize additional tasks.

The software tools SICK Appspace and dStudio enable image recording, training, classification and execution of the trained network even without in-depth knowledge of programming or machine learning. Optionally, further SICK sensors can be integrated, which can take over additional tasks..

Innovation
Unlike conventional image processing solutions, the use of deep learning technology in the SICK solution does not require detailed programming knowledge, as the system learns from concrete examples. This has enabled SICK to make pallet identification comparatively simple for the customer. Where the use of trained neural networks would normally require in-depth machine learning knowledge, SICK developed dStudio, a training software that includes a guided process flow. This has made it possible to reduce the large number of setting options of conventional solutions to a minimum. This simplification allows users to focus on their specific application – and not on the technology.

In interaction with SICK Appspace and SICK’s know-how in the field of sensor applications, the deep learning-based pallet identification system was developed – a complete solution with maximum customer benefit from a single source..

Market relevance
Customers from various industries lose a lot of money every year because deposit pallets are incorrectly assigned in incoming goods. The SICK system helps them avoid losses, save resources, and significantly increase their process quality. A previously resource-intensive and error-prone manual process can be automated in this way. Higher reliability, increased efficiency, and transparency are just some of the benefits ensured by pallet identification from SICK.

With this innovative solution, customers from all industries and across all sectors can optimize their pallet handling and relieve the strain on their incoming goods resources.
Moreover, the market may be significantly larger from the user’s point of view: The technologies used not only lend themselves to pallet type identification applications but can also offer significant benefits in many other areas.

Main customer benefits
The advantages of deep learning-based pallet identification PACS are evident in the creation, deployment and maintenance of the solution.

Time and complexity can be saved in the creation of the solution compared to the use of traditional image processing. By using trained neural networks, it is possible to identify the branding of pallet types with a high success rate, even if the quality is subject to large deviations. These deviations are taken into account in the training process and are learned, thus increasing the robustness of the evaluation.

The use of the solution not only enables an increase in efficiency and throughput, but also an increase in process quality and traceability. Employees are relieved and can concentrate on processes with higher added value.

The space-saving design means that the system can also be integrated in tight assembly positions. The use of standard sensor technology makes maintenance and servicing of the system very cost-effective.

Summary

One of SICK’s customers was faced with the problem that its employees in goods receipt had to manually determine whether incoming pallets belonged to a pallet pool and were pawned accordingly. Until now, this was an additional task in goods receiving that was resource-intensive and error-prone.

With deep learning-based pallet identification PACS (Pallet Classification System) from SICK, customers are given the opportunity to automate a previously laborious and manual process based on a modular kit of hardware and software.

The building block is based on SICK Appspace and dStudio. Appspace is an innovative approach for the realization of powerful apps on SICK sensors, dStudio is a web-based tool for the classification of images based on artificial neural networks, which can be used on SICK sensors. The construction kit can also be used for other tasks in the field of image processing.

IFOY TEST REPORT

Is it a Euro, a Chep, a UIC or perhaps a completely different pallet? Wrong deposit pallets, which are wrongly regarded as “real” deposit pallets at goods receipt and are accepted without complaint, cost companies thousands of euros every year. The PACS application from Sick now wants to put an end to this by enabling the automatic deposit of different pallet types.

PACS – this acronym stands for “Pallet Classification System”, i.e. a recognition system that uses images to identify the type of pallet. Four pictures of the pallet feet are necessary for this, the fifth picture is taken from above and shows what is on the pallet. The whole thing is usually integrated into the stationary conveyor system directly in the goods receiving area; for the test setup in Dortmund, a Sick employee still had to manually feed the incoming pallet onto the camera technology for demonstration purposes. The aim of the event is to provide companies from industry and trade with full transparency in goods receiving and consequently in the flow of goods. Because wrong deposit pallets cost companies a lot of money.

Until now, employees had to manually determine whether a pallet was “good” or “bad” when it entered the factory gate – an additional task that was error-prone and resource-intensive. With the PACS deep-learning pallet identification system, customers are given the opportunity to automate this process on the basis of a modular system of hardware and software. The financial aspect is the direct benefit of this classification system. But there is also an indirect effect, in fact several, that make this solution so interesting. Because incorrect pallets in the system also lead to damage and expensive downtimes of the conveyor system more often than average. Another, even more valuable aspect is more transparent processes by connecting the goods to the load carrier. And finally, no specialised personnel is required to operate the PACS system.

How does PACS work? The hardware of the system consists of one or more cameras with which the images for the system are taken, a light barrier arrangement for triggering and a controller for processing the recorded data and for executing the trained neural network. Even without in-depth knowledge of programming or machine learning, the software tools AICK Appspace and dStudio enable image recording, training, classification and execution of the trained network. Optionally, even further Sick sensors can be integrated, which can take over additional tasks. No programming knowledge is required because the system learns from concrete examples. In this way, Sick was able to make pallet identification comparatively simple for its customers.

Because Sick uses trained neural networks for its solution, the brandings of the individual pallet types can be recognised with a high success rate – even if their quality is subject to large deviations. The training process takes these deviations into account, learns them and thus increases the robust evaluation. Due to its space-saving design, the PACS system can also be integrated in narrow assembly positions. Because Sick uses standard sensor technology for its solution, the system is very cost-effective to maintain and service.

IFOY Test Verdict

With an estimated 500 million Euro pallets in circulation, not to mention the other types, the savings potential through PACS is in the tens of millions. But also companies that regularly use, for example, mesh pallets or small load carriers in their intralogistics can use PACS. The application range of the very reliable pallet classification system covers a broad spectrum: retail, freight forwarding, automotive, mechanical engineering and many other industries.

IFOY INNOVATION CHECK

Market relevance: Given the enormous quantity of goods of all kinds handled on different types of pallets, the Pallet Classification System from Sick is expected to have a very high market relevance. Optimising pallet handling can be beneficial in many areas for a large number of customers. The savings potential in terms of the automation of a former manual work process and the controlled labelling lead us to expect a high level of interest.

Customer benefit: Users ultimately benefit from the cost savings. Pallets do not have to be recorded manually when goods are received and can be automatically recognised and classified with the system. Deposit pallets can be assigned with high accuracy, which brings further cost-saving potential for companies. The expandability of the artificial neural network (ANN)-based system with regard to defect detection should also be emphasised. Faulty pallets can be detected in time, which allows one to take action before subsequent work processes and avoid possible downtimes.

Novelty: Image processing by means of ANNs is not new in itself, but here in practical application it represents an innovative solution for pallet classification. The system is well equipped for the future and can be extended for new pallet types up to the digital pallet (e.g. iPAL). Additional characteristic data can be integrated into the registration and passed on for the customer-specific systems.

Functionality / type of implementation: The system appeared very well implemented and can be flexibly positioned on the conveyor system. The image capture is limited to the lateral capture of the pallet. The detection accuracy depends on the trained ANN in the system, which can be retrained at any time, e.g. for new pallet types.

Verdict: The Pallet Classification System from SICK is undoubtedly a nominee for the IFOY AWARD that promises high savings potential for many areas.

market relevance ++
customer benefit ++
novelty +
functionality / type of implementation +
[++ very good / + good / Ø balanced / – less / – – not available]

For an overview of all the finalists, visit www.ifoy.org

CLICK HERE to find out more about SICK.

IFOY FINALIST FOCUS: Extension of Hase Safety Gloves’ automated warehouse by STILL

Our second finalist in the Integrated Warehouse Solution category of the IFOY Award – which we are showcasing ahead of the winners announcement on 30th June at BMW World – is the extension of the automated warehouse of Hase Safety Gloves GmbH by intralogistics expert STILL.

IFOY category: Integrated Warehouse Solution

Hase Safety Group sets course for growth: Automated industrial trucks are also very flexible in combination with variable goods transfer. One example is the expansion of the automated warehouse at Hase Safety Gloves GmbH. There, the STILL industrial trucks were replaced by new automated, more powerful vehicles with telescopic forks. Newly programmed route optimisations also contribute to the increase in performance. STILL expanded the racking system to a total of 10,000 pallet spaces.

Customer: Hase Safety Gloves GmbH

Realisation Phase:
From: 2021-05-31
To: 2021-10-30

Description

For more than 70 years, the production of work gloves has been the core business of Hase Safety Group AG in the Frisian town of Jever. In 2013, the German company celebrated 75 years of company history. Due to the growth of the Hase Safety Group, the existing space and handling capacities were no longer sufficient. The task was therefore to achieve greater storage and transport efficiency. One particular challenge was the conversion during ongoing operations. Until today, the course is clearly set on growth. That is why an extension was recently built. It houses new logistics areas, an innovation centre for customer training, product development and product presentation.

Theodor Wagner, CEO of Hase Safety Group AG, emphasises: “This is the only way we can meet the growing demand for new products. More turnover of goods for our Europe-wide customer business also requires more storage capacity as well as efficient and economical warehousing.”

More productivity through more automation
To keep distances short, the various glove articles are packed in cartons and stored neatly by type on pallets in the narrow-aisle warehouse according to the ABC analysis. For safe and independent movement of the vehicles, all AGVs (Automated Guided Vehicles) navigate with rotating laser scanners that constantly measure the distances to the installed reflectors. Three MX-X very narrow aisle trucks and six EXV-SF high lift stackers of the latest generation were each equipped with STILL’s iGo Systems automation kit.

At the goods receipt of an overseas container, the cartons with new goods are palletised by Hase employees using a telescopic conveyor belt and a vacuum lifting aid and distributed to the goods receipt locations according to type. Maximilian Engels, project manager and IT administrator at Hase Safety, explains: “We largely automated the processes in the goods receiving area. By manually scanning the storage locations as well as the articles, the automated storage processes are now triggered in our IT system.”

EXV high lift stackers pick up the finished pallets and drive them through the contour check. There, the pallet is measured to see if it is too long, too wide or too high. If successful, an EXV moves the pallet to the transfer rack in the narrow-aisle warehouse. There it is picked up by one of the automated MX-X high-bay stackers and stored in the assigned storage location.

In the case of a retrieval, an MX-X transports the respective pallet to the transfer station. The pallet is then picked up by the EXV and transported either to the transfer rack of the manual picking warehouse or directly to the shipping lanes of the trucks. Once the storage and retrieval operations have been completed, the AGVs automatically move to their waiting positions. All MX-X are equipped with telescopic forks, as the aisles at Hase are significantly narrower and thus not suitable for high bay stackers with swivel traverse forks. By using telescopic forks, both the storage density and the storage capacity are higher.

Identical components, controls and interfaces turn the trucks into high-performance AGVs. “One effect of the route optimisations is a lower number of transport orders and, as a result, less movement of the AGVs. This has also significantly improved safety in the warehouse. Thanks to the close cooperation between our team and the STILL project managers, we were able to successfully reorganise both the software and the hardware of our automated warehouse despite the Corona pandemic. Now we are well prepared for the challenges that lie ahead in the near future,” emphasises Maximilian Engels.

Autonomous charging of the vehicle batteries
The state-of-the-art photovoltaic system on the more than 10,000 quare metre-sized roof supplies green electricity to charge the forklift batteries. Lars Lemke, project manager from STILL’s Bremen branch points out: “To charge the batteries, the AGVs move to their charging stations independently. Without having to connect a cable, the battery is charged simply by contact with the ground. This is another highlight: because now the AGVs can charge their batteries autonomously at night and without additional personnel.”

One-shift operation still possible
The overseas containers from Bremerhaven are not only delivered during the day, but also in the evening. The experienced entrepreneur Theodor Wagner clarifies: “With the reorganisation of our automated warehouse, we can now also carry out automated storage in the evenings or overnight without the need for staff. This is an important requirement for the new processes. Even with constantly increasing demands on the market, we can continue to maintain our one-shift operation with the new system.”

Maximum flexibility in the scalable automated warehouse
Due to the scalability of the automated warehouse, it is possible to react quickly and flexibly to larger capacity requirements with additional AGVs. For the demand in the near future, a total of 10,000 pallet storage locations are now available. The fact that the AGVs can also be operated manually for special storage processes underlines the flexibility of the automated warehouse.

Summary

With the iGo automated warehouse from STILL, the modern distribution centre is ideally equipped to meet the future requirements, including those of other medium-sized companies. Customer requests and the requirements of major customers are thus fulfilled and the products are delivered across Europe, promptly and in a timely manner. “The first wave of logistics automation started back in 2010, and in recent years we have steadily expanded our automated warehouse and brought it up to date with the latest project. For more than 30 years, we have had a reliable partner at our side in STILL, who very quickly turns our ideas into reality,” summarises Theodor Wagner. Once again it shows that automation is an issue for companies of all sizes and has now finally arrived in the SME sector too.

CLICK HERE to watch a video.

IFOY TEST REPORT

With the help of Still, Hase Safety Gloves has expanded the system of its automated warehouse and made the processes more efficient – during ongoing operations. Although four to five jobs were replaced by automating the system, 15 new jobs were created at the same time by expanding the warehouse by 200%.

80 employees, 70 of them at the headquarters in Jever, take care of incoming and outgoing work safety clothing at Hase Safety Gloves, which mainly arrives by container from the Far East. Of the 12,000 square metres of warehouse space at Hase, around 7,000 square metres alone are now automated, and of the total 13,000 storage spaces in the warehouse, just under 7,000 spaces can be attributed to automation. A 10,000 square metre photovoltaic system on the roof is also used to charge the forklifts used in the warehouse. Speaking of forklifts: Hase successfully operates according to the “mixed operations” principle: Forklifts and staff can meet each other, and the use of protective fences has been deliberately dispensed with.

When employees place a filled pallet on a place in the staging lane after goods receipt, this simultaneously means a transport order for a still unit – it goes off to the warehouse or cross-docking directly to goods issue. At Hase, there is automatic whole stock removal, but also manual order picking. Until this happens, the pallet first goes through a so-called contour check: a gate with a laser curtain that eliminates tolerances of the pallet so that the automatic warehouse does not store a “brake block” – otherwise the system stops. If an error is detected, the pallet is immediately forwarded to the “not right” location and the problem is eliminated. Hase uses three automated MX-X narrow-aisle stackers and six EXV-SF high-lift trucks of the latest generation, all of which are equipped with Still’s iGo Systems automation kit. The EXVs pick up the sorted palletised goods at the goods-in location and take them to the transfer rack in the narrow-aisle warehouse, where they are picked up by one of the automated MX-X units and stored in the assigned bin location. For retrieval, this process happens in reverse order. Once the AGVs have done their work, they automatically move to their waiting position.

A novelty for Hase: a changeover aisle in the middle of the system, which, together with a spray wall, replaces the otherwise necessary firewall, enables the forklifts to move simultaneously from one racking aisle to another without having to return to the beginning of the racking. In the manual area, the forklifts always run in single-shift operation. Overnight, they are then autonomously recharged according to the “opportunity charging” principle, using lead-acid batteries, which are more economical than lithium-ion batteries in this application. The racking aisles at Hase can be much narrower than is normally the case: compared to the use of high-rack forklifts with swivel reach forks, the MX-Xs equipped with telescopic forks require significantly less space, which has a beneficial effect on storage density and capacity.

Because the overseas containers from Bremerhaven are not only delivered during the day, but also in the evening, it is an advantage for Hase that with the reorganisation of the automatic warehouse, goods can now be stored automatically in the evening hours or at night without the need for personnel. This means that the existing single-shift operation can continue to be maintained.

IFOY Test Verdict

With its automation solution, Still has brought Hase up to the state of the art and made it fit for the future. With the iGo automated warehouse solution implemented at Hase, other medium-sized companies can also streamline their processes and bring them up to date. Automation, and this has been impressively demonstrated by Still, is a topic for (almost) any size of company.

IFOY INNOVATION CHECK

Market relevance: The expansion of existing warehouse locations is a frequent case in practice. Changes in the company’s own products or production processes, but perhaps even more so the changed behaviour of customers with a focus on product availability and short-term delivery, often make changes necessary. Both the structure and the processes can be affected by changes. The example at the Hase company shows a special case, as the possibilities for adjustments in the layout were very much limited by the available floor space for extensions. In addition, the owner put the unconditional will to automate first, whereas the economic efficiency of an application is the highest priority for most users. For the above reasons, the market relevance can therefore be rated as good, as the solution cannot be transferred to most extension cases without restrictions.

Customer benefit: Measured against its own objectives, the customer Hase has certainly achieved its goals to a high degree. With regard to the general case, however, a limitation to a good customer benefit results from the previously mentioned reasons.

Novelty: The specific expansion of the warehouse at Hase is well solved and the implementation with state-of-the-art vehicles is also at the current level of available technologies. The innovation results from the appropriate combination of the known well-functioning trades in a very limited environment. However, similar solutions could be achieved before with available equipment.

Functionality / type of implementation: The many limitations of the extension in the existing building were well taken into account in the realisation of the solution. The solution offers many functions for the operator and provides him with alternative uses of the vehicles as redundancy or to absorb power peaks.

Verdict: The expansion in the existing stock is impressive and the implementation with state-of-the-art vehicles is well solved. The innovation results from the good combination of the known well-functioning trades in a very limited environment.

market relevance +
customer benefit +
novelty Ø
functionality / type of implementation +
[++ very good / + good / Ø balanced / – less / – – not available]

For an overview of all the finalists, visit www.ifoy.org

CLICK HERE to find out more about STILL.

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