The market gives directions

The robot density, i.e. the key figure for robot installations per 10,000 employees, increases each year. With currently 113 robots per 10,000 employees, the robot density has reached a new global record. Germany is in fourth place worldwide with 346 units (robots) and leads Europe’s rankings, ahead of Sweden and Denmark.^[1] Currently, the majority of all installations can still be assigned to the manufacturing industry, but logistics is catching up.

In fact, this development is also increasingly finding its way into intralogistics processes. Whether depalletizing, palletizing or picking, high-performance robot technology has become indispensable in many warehouses and is essential for high performance rates.

Picking technologies by SSI Schaefer

SSI Schaefer offers piece picking as well as case picking solutions. Case picking is usually applied in distribution centers that supply retailers with store-friendly pallets. Depending on the application, tried-and-tested gripping principles are used together with intelligent object recognition – for all temperature ranges (including deep-freeze at minus 28° C) and all performance rates.

Another, very frequent use is piece picking, i.e. picking individual pieces into a shipping bin. Piece picking is one of the most costly processes and requires particular attention for highly efficient processing. The two main challenges are: safe and gentle product handling and optimum use of intelligent software technologies.

Piece picking – smart and flexible

Machine learning and particularly optimized, extremely high-performance algorithms are the essential factors for the productivity of picking robots. Robots using current algorithms can not only repeat more predefined motion sequences, but also take on more complex tasks, thanks to artificial intelligence (AI) and 3D image processing. They are now able to respond and act depending on the situation, which increasingly qualifies them for even more complex intralogistics application scenarios. In intralogistics, every single delivery is unique and the result of an individual picking process. In addition to increasing efficiency, automatic and semi-automatic solutions focus on ergonomic relief of the operators, particularly in repetitive activities that are detrimental to health. Thanks to these solutions, individual processes can be smoothly meshed with one another. When it comes to performance, robustness and quality, robots have some advantages compared to manual solutions – provided there is a suitable range of shipping items and they are used in the corresponding automated environment. In this context, significant development steps were taken because today special algorithms enable what was unthinkable a couple of years ago. Robots are suitable for gripping a wide variety of shapes, such as cylindrical, cubic, conical, etc.

Integrator competence as factor for success

Standardized piece picking robotics applications not only meet the requirements of different order structures, but they can also be applied across various sectors of industry. SSI Schaefer piece picking applications can be seamlessly integrated into existing systems. Depending on the area of application and the process environment, high-performance picking robots achieve a performance of up to 1,000 picks per hour.

The aim of every application is always the same: achieving maximum performance – of course, maximum process reliability must always be guaranteed. En route to this ambitious goal, we primarily rely on the following success factors: comprehensive integrator competence for piece picking applications such as AI vision (image recognition in production and logistics), tried-and-tested scanning technologies and the detailed analysis of robot cells using real-time system visualization with our software WAMAS^® Lighthouse. The latter is able to calculate the necessary maintenance intervals by gathering important operating data. This Predictive Maintenance method makes maintenance projectable, calculable and helps to prevent downtimes.

The resulting benefits are clear:

• Smart robotics solutions for high system availability with constant performance.
• Seamless integration of the warehouse management system WAMAS into the existing infrastructure.

• Maximum performance due to high process reliability through optimized gripping and product-specific robot accelerations that cope with both peak times and seasonal fluctuations.
• Flexible and scalable solutions.

The world through the eyes of software

The software of the SSI Schaefer piece picking applications can be operated as a fully integrated component of a WAMAS installation. However, it can be also seamlessly coupled as a self-sufficient stand-alone system with merchandise management and material flow systems from third-party providers. The core element of the piece picking software is the software module WAMAS^® Vision. It detects the items in a bin and identifies the ideal gripping area. For this purpose, state-of-the-art image processing algorithms as well as smart AI methods are applied. The eyes of the software into the “real world” are 3D camera systems that depict the contents of the bin. To be able to interact with the “real world”, WAMAS Vision transmits the data to the robot control. There, the data are processed under consideration of mobility as well as the physical properties of the gripper for optimal picking. The software is integrated into a highly complex system consisting of sensor and robot technology. SSI Schaefer has gained valuable experience in dealing with camera and sensor technologies thanks to the Schäfer Case Picking. SSI Schaefer strengthens this unique technological know-how of automated picking through their process competence, which is always required in these areas of application – i.e. the knowledge of the surrounding processes in which the automated picking cell has to be integrated.

Tailor-made solutions applied in practice

The first SSI Schaefer piece picking cells have been in operation at a pharmaceutical wholesaler in North America since 2020. The cells are supplied by a bin conveying system. They have a multi-order design, in which the robot picks several orders from two source bins into three target bins at the same time. The first installation of the cell is used to pick drugstore products. In the meantime, seven other instances of this cell type to pick for picking medication, have already gone into operation. Although the two projects seem to be similar, the focus of the development shifts based on the product range. The design of drugstore products is based on the expectations and demands of end customers in the store. Packaging that is intended to attract the consumer’s attention poses a considerable challenge for many systems. However, the AI-based system installed by SSI Schaefer masters such challenges with flying colors.

Compared to drugstore products, medication is usually sold in less sophisticated packaging. These may lead to optical pitfalls, but the difficulty with medication is completely different – namely zero-error tolerance during picking. The selection of the gripping position considerably affects the process safety in picking. A large number of sensors is used for additional monitoring. Sophisticated statistics and in-depth analysis tools make the processes in the robot cell transparent. Simulations and machine learning procedures optimize the processes in the product range.

Piece picking robot cells by SSI Schaefer offer standardized solutions for small parts picking in bin conveying systems as well as for pouch loading systems. The highly flexible WAMAS Vision software is also applied in other logistics contexts.

About the author:

Armin Grüb completed his studies in electrical engineering/automation technology at the University of Applied Sciences Würzburg-Schweinfurt. He worked for a long time in the field of automating crane and intralogistics systems and then developed software for warehouse management, image processing and visualization as an independent entrepreneur. Since 2006, Armin has been responsible for developing case picking and piece picking systems. Together with his team, he develops practical product solutions in the fields of image processing, packing pattern calculations and the integration of robotics into complex intralogistics systems.

[1] https://ifr.org/…