- Email: [email protected]
Skill-based Dynamic Task Allocation in Human-Robot-Cooperation with the Example of Welding Application
Available online at www.sciencedirect.com
ScienceDirect Procedia Manufacturing 11 (2017) 13 – 21
27th International Conference on Flexible Automation and Intelligent Manufacturing, FAIM2017, 27-30 June 2017, Modena, Italy
Skill-based dynamic task allocation in Human-Robot-Cooperation with the example of welding application Prof. Dr.-Ing. Rainer Müllera, Dipl.-Wirt.-Ing. (FH) Matthias Vette M. Eng.a, Aaron Geenen M. Eng.a* a ZeMA - Centre for Mechatronics and Automatisation gGmbH Gewerbepark Eschberger Weg 46, 66121 Saarbrücken, Germany
Abstract Due to technological and organizational boundary conditions, it is often difficult to solve the problem of automation for assembly processes. The development of such automation is subject to technological challenges and economical risks due to a high number of part variants as well as the complexity of reliably managed assembly processes. One solution for the flexible and skill-based automation of processes is represented in Human-Robot-Cooperation for the assembly of high quality machines for the medical industry. Instead of an inflexible, fully automated approach, a semi-automated method is being developed that can be easily controlled by the operator on the shop floor. Therefore, know-how gained from manual processes will be efficiently transferred into the assembly system. © by Elsevier B.V. by This is an open access article under the CC BY-NC-ND license © 2017 2017Published The Authors. Published Elsevier B.V. (http://creativecommons.org/licenses/by-nc-nd/4.0/). Peer-review under responsibility of the scientific committee of the 27th International Conference on Flexible Automation and Peer-review under responsibility of the scientific committee of the 27th International Conference on Flexible Automation and IntelligentManufacturing Manufacturing. Intelligent Keywords: Automation system, Robot technologie, Assembly station, Welding process, Human-Robot-Cooperation, Skill-based dynamic task allocation, Human-Maschine Interaction,
* Corresponding author. Tel.: +49 (0) 6 81 - 85 787 - 520; fax: +49 (0) 6 81 - 85 787 - 11. E-mail address: [email protected]
2351-9789 © 2017 Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). Peer-review under responsibility of the scientific committee of the 27th International Conference on Flexible Automation and Intelligent Manufacturing doi:10.1016/j.promfg.2017.07.113
14
Rainer Müller et al. / Procedia Manufacturing 11 (2017) 13 – 21
1. Introduction Numerous variations in combination with small part quantities represent a particular challenge in special machine and plant construction [1]. Companies, in particular smaller enterprises, often have a lot of experience regarding specific as well as manual processes. Due to high wages, however, small and medium-sized enterprises (SMEs) of the established special machine construction industry are under severe economic pressure. Furthermore, the knowhow in low-wage countries is increasing, causing considerable international competition [2]. Experience has shown that full automation of such production cycles is often inefficient due to the high variability of products paired with small batch quantities [3,4]. Moreover, the development and efficient operation of an assembly system are further complicated by low volumes of varying quantities. In addition to this, small enterprises lack the experience of operating with automated systems that can only be used to a limited degree. For the implementation of efficient automation, it is necessary to develop flexible and adaptable production systems that can be applied to a variety of tasks [3]. This ensures high efficiency of the production plants [3]. One solution approach for these flexible automation requirements is Human-Robot-Cooperation (HRC). This solution can be demonstrated in the example of a welding process for manufacturing filter units for hem purification (figure 1a). a b
Fig. 1. (a) Example of manufacturing filter units for hem purification (Woll Sondermaschinenbau) (b) Welding process by operator (4by3)
The filter unit machine is comprised of a solid metal frame with the addition of control components, actuators, and sensor modules. The metal frame can be built from a variety of assemblies. In these types of metal frame assemblies, welding is typically used as the joining procedure. Currently, these processes are completed manually by a skilled welding expert (figure 1b) [5]. The focus of this assignment includes the setting up the assembly cell, loading and unloading of the assembly parts, tacking the assembly section together, preparing the seams for welding, and welding the seam. The requirements of the medical industry are subject to high quality standards which pose a high degree of difficulty for automation. Any sub-assemblies which come into contact with organic liquids must be made out of stainless steel. Additionally, all welded joints of the assemblies must be pore-free and free of particles so that corroding of the assemblies can be avoided. Defective assemblies may not be returned to previous processes for rework. Rather, such assemblies must be thrown out. Other influencing factors for the automation of such a system come from the welding process itself. Skilled operators are able to weld complex and short welds quite easily, however, the welding of longer seams leads to an increase in the probability of weld defects. This is due to the limited motor abilities of humans. Another important factor of weld quality is ensuring an organized welding sequence. The ability to have one single welding sequence is very important for a product’s quality [5]. This sequence is determined by an experienced engineer during the planning phase of the assembly. If the welding sequence were to be performed out of order, irreversible warping may occur. Component warping such as this can often times only be detected using measuring technology during final inspection and causes expensive follow-up. Until now, there is no process that ensure the welding order is performed in a specific sequence. The idea of the automation system designed by ZeMA is to support the operator in the production process using HRC robot systems and innovative assistance systems to increase the efficiency and quality of the end product. These increases can be obtained using skill-based task planning to allocate various task to the human or the robots. Along with this, a semi-automated system is was chosen instead of full automation for its flexibility and versatility. This system will also have the ability to be controlled by the operator easily and intuitively on the shop floor. The
Rainer Müller et al. / Procedia Manufacturing 11 (2017) 13 – 21
technical know-how that the operator has gained from manual processes will be seamlessly transferred into these semi-automated production processes. Such a production system requires a methodology for innovative operation and a control approach that is able to economically produce a variety of goods in cooperation with the operator. This is why ZeMA has developed a Human-Machine Interface for the visualization and intuitive operation of such a system. The implementation of such a semi-automated welding processes in special machine production offers a large potential for efficiency improvements, lower costs of production, and increased process capability. 2. Spectrum of HRC Robot Systems There are many ways in which humans and robots can work together [7]. In order to choose a specific methodology for the automation system, it was important to understand the distinct advantages and disadvantages of each one. In conventional methods, robots are separated from the operators entirely, often using fences or other safety devices. Though this may seem to be the best method due to the assurance of safety, it can regularly cause difficulties if the manufacturing company has little factory floor space. Not only that, but the system also loses the ability to quickly change process parameters if the operator is fenced off from the robot at most times. Along with this, valuable time is lost transporting parts in and out of the work spaces by the operator. One way to relieve these complications is to remove the fences while still keeping the work spaces of the robot and operator separate [6,7]. This method is known as Autarkic or Coexistent [7]. To ensure the safety of the system, the robot uses certain safety devices which can, for example, detect the presence of an operator in the robot’s work space [7]. The difficulty that arises with this method is that the part must still be transported to and from the robot and human work spaces. Also, due to the safety features of this system, the robot is not allowed to perform any actions during the time that the operator is placing the part in the robot’s work space [6]. The transportation and placement procedures cost valuable time within the manufacturing process. To alleviate these time costs, the human and robot can choose to operate in a synchronized fashion (figure 2a) [7]. This method combines the two work spaces while allowing only the human or robot to operate inside at any given instance. In order to improve the efficiency of this system once again, the robot and operator must be able to work in the same area at the same time, shown in figure 2b. This can be achieved using the cooperation method. This method allows the operator and robot to work in the same work space at the same time on separate tasks [7]. When the operator needs to work on the same task as the robot, the collaboration technique must be used d [7]. ature a New technologies with special safety feature b enable cooperation and collaboration techniques such as these.
Manual welding seam
Configuration of the station
Fig. 2. (a) Human and robot in a cooperative work space (b) and in a synchronized work space
In a welding application for the filter units of this project, there are several HRC techniques which can be chosen for use. However, since the robot is handling the welding gun, a combination of several methods will be implemented. To start, the robot and human will work in cooperation during the configuration of the assembly station. This allows the operator to use Teach-in methods for the configuration of station locations and to perform additional process tasks while the robot executes other setup procedures. It is important to remember, however, that the primary concern during this welding process is the safety of the operator. During the welding process, large amounts of heat and light are produced. For this reason, the robot must wait until the operator is out of the work space to start the process, as defined by a synchronized system. The robot uses position sensors, such as safety shut-
15
16
Rainer Müller et al. / Procedia Manufacturing 11 (2017) 13 – 21
off mats, to detect whether the operator is within danger. These safety devices are placed around the affected work space and monitor if any humans are within it based on pressure sensors in the mats. HRC robot systems switch to different modes between cooperative and conventional control if human is in or out side of the work space. When nothing is detected, the robot is allowed to proceed with the welding process. 3. Characteristics of HRC Robot Systems It is important for ZeMA to understand all of the key features and characteristics of HRC robots and how they apply to current products in order to make the developed system flexible enough to allow for a wide range of uses and robot implementation. When it comes to defining the key characteristics of HRC robot systems, not all robot suppliers have the same strategy. Many suppliers go after different concepts, although, there are several key features regarding such robots which nearly all of them include. Among the most important of these features are mobility, the fast commissioning of the robot systems, intuitive operation concepts of the system, as well as safe and cooperative use in a process. [8] The comparison of different HRC robot concepts shows selected advantages and disadvantages of robots available on the market. Besides the classic parameters of a robot such as load-capacity, workspace, and reach, new technologies offer a variety of different features. These features include, but are not limited to, distinctive safety functions, integrated sensor technology, 7 axes of rotation, and integrated grippers. With all of these interesting capabilities in mind, it is important to note that HRC robot systems are not a solution for every automation need. The advantages and disadvantages of these systems can only be estimated after a thorough analysis of the individual requirements [8]. Once all the various parameters for different systems are analyzed, ZeMA can tailor the developed operation concept to the system which best fits the application. 3.1. Key characteristics of HRC robot system Different concepts such as platform systems, linear axis systems, and rapid clamping devices lead to a high mobility of the robots. HRC robot systems on a platform can be often times easily rearranged. The platforms don’t always have to be autonomous systems, rather, the robot can be moved manually or with simple tools such as rollers, forklifts, or air cushions. In the assembly process, dynamic forces during the motions of the robot often require one to set up weights on the platform and/or static clamping fixtures to the production ground or process station. Such a mobile platform includes the necessary robot control system which is integrated into the platform. The platforms are equipped with a higher level control system which can be used for the connection to external sensor systems. To use the mobility of the robot systems efficiently, they must be put into operation again quickly after reconfiguration. The fast identification of reference coordinate systems in the specific assembly station, the parts to be assembled, the robots base itself, and the tool are all functionally imperative. Various procedures with external measurement systems (e.g. Indoor GPS, laser tracker), integrated force monitoring, or optical sensors can be used for quick environment identification and calibration. Depending on the application, the optical sensors remain the most economical solution. These measuring methods allow for a rough positioning of the robot in the assembly area and the exact determination of the robot position in relation to the reference coordinate system of the specific station. HRC robot systems not only provide the quick setup of a robot cell, but also intuitive operation concepts which allow simplified use of the robot with little to no specialist knowledge. This enables the operator to create or adjust robot applications directly on the shop floor in a short amount of time. An example of this includes the direct adjustment of a path through manual guidance of the robot’s kinematics or gesture controlled programming [9]. To fully benefit from the advantages that result from direct human and robot cooperation, the boundaries between robot and human have to be eliminated. With integrated safety features, the HRC robot system enables a direct cooperation between human and robot without separation devices. This can all be accomplished while meeting the relevant norms and guidelines as well as a risk analysis [6]. The HRC robots available on the market distinguish themselves mainly by their safety strategies. Shown in figure 3, these HRC robot systems usually have a combination of safety features to allow for task sharing in an overlapping work space. In general, the security
Rainer Müller et al. / Procedia Manufacturing 11 (2017) 13 – 21
features can be divided into four categories. The first of which are internal sensors. Examples of internal sensors include joint current sensors or torque sensors which provide information about unexpected forces to prevent collisions. The next category, external sensors, describes all the safety elements that are integrated by a higher-level control in the robot system, e.g. a safety PLC. This includes the supplementary protective devices that can be separate from or a part of the robot such as tactile protection covers or laser detection systems. The physical features of the robot can also be designed to provide an inherent security for the humans through the safety feature of robot design. The safety feature known as process design reduces the risk of injury of human by cleverly adapting the process. This is usually done by reducing the degrees of freedom and/or reducing the velocity of the manipulator when human contact is anticipated. Another way to adapt the process is to specially encapsulate the process tools for additional safety. Additional sensors for the detection of the surrounding environment can be included as well [6].
Fig. 3. Overview of safety features according the HRC robot systems (DLR, Bosch, ABB, Automation trends)
Other than the safety stop of the robot when exceeding the force, torque, or power limits, the robot can monitor defined work space to ensure safe operation. This can be implemented through integrated sensors or external systems such as laser scanners and safety contact mats. One specific solution for the application of welding filter units is initiated if an operator enters the intended work space of a robot. Once something is detected within the work space, the sensor system lowers the speed of the robot or stops its motion entirely. Endangering the operator is therefore eliminated. After the work space is cleared, the program will continue automatically. These features of the robots allow new types of cooperation by combining the cognitive and locomotive abilities of the operator with the precision and consistent quality of the robot into one process [10]. Additionally, the new system developed by ZeMA allows for the integration of a large variety of HRC robots and can be easily used for countless processes such as the filter unit welding shown in this project. 4. Skill-based and Dynamic Task Allocation In order to achieve maximum efficiency, the operator must adapt his or her workload according to their abilities. If the operator is under loaded or overloaded, their ability to hold their attention to a task will suffer. Robots, on the other hand, are able to hold their attention to a task independent of how many operations they must perform. Within the same idea as attention, performance level can be fairly varied for an operator throughout the day. This is due to human error as well as other uncontrollable factors. Robots, on the other hand, are able to maintain a constant performance level throughout its entire work process. One advantage of humans, however, is that they have an automatic sense of touch, or sensitivity. In order for robots to have similar abilities, they must attach special and usually expensive sensors to the robot. Another advantage of humans is that they are highly mobile. They can change work space size and location relatively easily. For robots, however, this can be quite difficult due to the fact that robots are often fixed within their work space. Though humans have been shown to be quite adaptable, they are only able to operate within a limited accuracy without the use of tools or other forms of production equipment. Robots, however, are able to operate in a high accuracy range. In the category of strength as well, humans are easily outperformed by robots. This case is amplified when considering the way in which the operator must lift and hold certain loads. The process of welding requires a large range of skills in order to be efficiently and accurately completed. A human has many advantages when it comes to unique movements and tasks that would be difficult to program into a robot in short period of time. An example of this in the filter unit project is that an operator is able to set up a station or prepare a part for assembly by taping seams. Processes such as these pose a high degree of difficulty for robots in
17
18
Rainer Müller et al. / Procedia Manufacturing 11 (2017) 13 – 21
the case of single part production. An operator can also weld unique and inaccessible areas that would take a lot of programming for a robot to complete. Besides their movement capabilities, humans are also able to complete visual inspection tasks rapidly and effectively. In the case of welding, trained operators can quickly determine the quality of a weld by a simple examination. Another process which an operator can easily overcome is adjusting their welding style based on the orientation of the weld seam. For example, if the seam is vertical, the operator must compensate for the molten weld bead wanting to drip down the seam. A robot, on the other hand, is more suited for welds with constant parameters. An example of this is being able to weld long straight seam with ease. Because of the robot’s mobility, it is able to complete long welds without having to section them up. This ability poses a great advantage to the overall strength of the weld and takes little time to complete. Another advantage of a robot is that the parameters of the welding process can easily be changed. Along with this, the robot can provide consistent heat penetration into the material due to its ability to control the process accurately. Finally, the robot has exact control over its process. Speed, distance, and orientation can all be controlled very accurately and precisely to ensure the desired result. Due to the limitations and advantages of both workers and robots, ZeMA has allowed the operator to allocate tasks on the shop floor based on process efficiency evaluations. This real time task allocation is explained in further detail in the next section of this paper. The unique and versatile skill set of the operator aided by the precise and consistent operation of a robot is a combination that will change the future of welding processes (figure 4). It is because this combination of physical and mechanical advantages that ZeMA has approached this welding concept with a semi-automated system.
Fig. 4. Guideline for skill-based, dynamic task allocation in Human-Robot-Cooperation
5. Operation Concepts of HRC Robot System A key element for the successful operation of HRC systems is the Human-Machine Interface. This interface is where the operator can interact with the system and perform various tasks, such as programming. The term programming is defined as the definition of the movement and logical procedure of the user program during the production. The downtime during programming and reconfiguration of the robot application is an important influencer of the efficiency of the robot’s implementation. This is especially true if this process leads to a delay in the production flow or if the programming is unable to be performed in parallel with the production [11]. The complexity of the programming for HRC systems is often increased because of the demands of cooperation between humans and robots as well as the various abilities provided by robots. Because of this, programming is typically done in special languages and requires advanced programming knowledge. Therefore, the simplification for use on the shop floor is quite challenging. With the complexities of programming a system such as this in mind, custom control concept must be developed so the operator can control and program the robot quickly and intuitively. Luckily, the control concept developed in the 4by3 and TRSE projects provides a solution in the form of a hybrid programming method. This method enables the setup of a robot program through the combination of preprogrammed macros and online adjustments made by the operator. Using a graphic user interface, this approach automatically creates a robot program out of the macros
Rainer Müller et al. / Procedia Manufacturing 11 (2017) 13 – 21
and previously taught positions. This control concept, developed by ZeMA, distinguishes itself from other concepts through the use of a simple simulation environment, a universal robot interface, the inclusion of sensors, and a visual interface. Another advantage to the programming process is that it is written with CAD (Computer-Aided Design) data or with models generated from camera pictures. The integration of which is done via common data formats. This gives the user a very visual and intuitive work platform. Within this control concept (figure 5), CAD data can be used to directly program the robot system. For the filter unit project, this would be done by drawing seams on the model in a design program like SolidWorks and then adding a welding process to the program. Once the CAD-data and welding tasks are inputted, the virtual model can then be finalized. This model is a combination of process information according to WPS (Welding Procedure Specification), location and orientation data, and task information which the robot will use to complete its various responsibilities. The robot path and the orientation of the end effector are loaded from the virtual model and saved as macros. The completed virtual model can then be used to create a workflow for the robot and the operator. This process is completed by a trained professional before the work has begun. The tasks planned for the operator are marked in red while the tasks for the robot are marked in yellow. The specialist can also exchange tasks between the robot and the operator depending on which they find most efficient for each specific task. If a weld is fairly complex or inaccessible, for example, they can choose to switch this specific task to the operator’s workflow because the robot will most likely have a difficult time accomplishing it. This transfer of tasks is completed in the virtual model by simply selecting the task and altering its properties. When the final process is confirmed by the operator, the generated data is obtained from the robot via a universal interface. After the virtual model and workflow have been constructed, the user must run through a configuration phase. This phase is used to define the coordinate systems and boundary conditions for the robot system either using teach-in methods to save important locations or by using pre-programmed movements set to find these locations. Once the configuration is completed, the user can interface with the machine in order to confirm the correct task description. Examples of this could include the operator moving weld seam locations because the joint locations have been changed or correcting small details regarding the orientation of the process tool and the robot path. Movements such as this can be completed by simply clicking and dragging the task indicators in the virtual model to edit their positions. Next, the user must run through some final process definitions. This is done to assure the correct path and tasks of the robot. It is important to note that with this system developed by ZeMA, long hours spent on programming tasks are no longer required. All of the information needed by the robot is given through the pre-programmed macros designed into the software. Using these macros, any operator with little to no programming experience can set up a welding process. It is this aspect of the system that greatly increases the efficiency of the various process planning stages.
Fig. 5. Intuitive operating method for an HRC robot system
6. Projection System of HRC Robot Station By supporting the operator in the welding process using the previously described robotic systems, the quality and efficiency of work can be greatly improved. Additionally, the quality and efficiency can be further improved with the use of a combination of additional assistance systems. Visual assistance can be offered using digital or laser projection systems. These projection systems are currently used in many facilities to support the operator in manual
19
20
Rainer Müller et al. / Procedia Manufacturing 11 (2017) 13 – 21
tasks to ensure the quality of the products. In the assembly of special machinery, visual assistance systems are used to provide the operator with instructions as well as assembly information directly on the shop floor. [8] Depending on what information is being visualized, different systems are more suitable than others. A Laser projection system’s large projection distance offers high contrast images and detailed precision of the projection at the same time. These systems are suitable to display the position of a component and provide other information about an assembly process. However, a digital projector is particularly suited for high resolution images, colored visualizations, and displaying more complex work instructions. [8] At ZeMA, Human-Robot-Cooperation is advanced by combining existing technologies with self-developed user and programming applications. Alongside HRC robot systems, a visual assistance medium can be used as a communication device between human and robot. A digital projector is used on the shop floor to visually support the user during the intuitive programming process. Figure 7a and 7b shows the newly developed visualization system. The benefit of such a system is the added flexibility gained by being able to adapt to any changes in the current process. In this example, the operator needed to add a new weld seam due to a change in the process. The addition and adjustment of this new welding seam is easily performed online by the operator on the shop floor. The developed visual assistance system displays both the tasks for the robot and worker on the part in order for the worker to actively determine efficiency improvements for the process. The visualization system also notifies the operator whether the system has been appropriately calibrated or not. After modifying the process in any way, the operator must confirm the adjustments. In addition to the visualization of the robot’s weld path on the part, the developed assistance system can be used to provide the operator with instructions directly at the work space (figure 6a). An example of these instructions could be the visualization of the sequence of welding seams. With WPS in mind, the developed assistance system marks the dynamic task allocation between the human and robot on the part in each workflow (figure 6b). This helps the operator control the welding sequence of the product and simultaneously documents the workflow with the adjustment of the welding tasks. This system ensures minimal process errors will occur resulting in a higher quality product. a b
Fig. 6. (a) Easy addition and correction of a new welding seam (b) Visualization of the sequence of welding seams on the shop floor
Summary & Conclusion In the manufacturing of tailored machinery, automation can be challenging due to high variability and complexities. The automation of such systems is made much simpler, however, through the use of the process concepts developed at ZeMA. Due to the addition of skill-based process planning, different tasks can be efficiently completed by actively assigning them to the operator or the robot based on their individual skill sets. These skills can also be mapped dynamically with the use of this concept. The efficiency of automated systems can be further improved through the use of multiple cooperation methodologies. Using these methodologies, the operator can safely work with a variety of HRC enabled robots because of the system’s ability to adjust to different robots and safety mechanisms. The programming of such robots can often be complex and require comprehensive knowledge. However, this operation concept allows for easy and intuitive programming through the use of a graphic and Human-Machine Interfaces as well as pre-programmed macros. Since there is little to no programming knowledge required, nearly anyone can plan and operate a welding program using this system. This allows for an efficient and economical production process. By means of this user interface for intuitive robot control, easy and innovative
Rainer Müller et al. / Procedia Manufacturing 11 (2017) 13 – 21
opportunities for automation have been created in order to enable the development of flexible and economic processes. Processes like these will guarantee the competitive edge of high-wage countries in the future while at the same time giving smaller companies the ability to implement automation techniques without extensive experience. Using this concept, we have the chance to obtain a higher quality of manufacturing processes while at the same time increasing the productivity of the process. References [1] McKinsey&Company (Hrsg.): Zukunftsperspektive deutscher Maschinenbau. Erfolgreich in einem dynamischen Umfeld agieren. Berlin, 2014. [2] Deutsche Mittelstands Nachrichten: http://www.deutsche-mittelstands-nachrichten.de/2014/07/63764/; Maschinenbauer verlagern Produktion ins Ausland. Published 07.07.14. Last viewed on 09.02.17 [3] Juhani Heilala, Paavo Voho, (2001) "Modular reconfigurable flexible final assembly systems", Assembly Automation, Vol. 21, pp.20 – 30 [4] Müller, R.; et al. “Wandlungsfähiges Montagesystem für Großbauteile am Beispiel der Flugzeugstrukturmontage.“ Zukunftsfähige Montagesysteme. Wirtschaftlich, wandlungsfähig und rekonfigurierbar. Stuttgart: Fraunhofer Verlag 2013. [5] Deutscher Verlag für Schweißtechnik (DVS) GmbH (Hrsg.): Fügetechnik Schweißtechnik. Düsseldorf, 1987. [6] Hülke M.; Umbreit M.; Ottersbach H. “Sichere Zusammenarbeit von Mensch und Industrieroboter.“ Maschinenmarkt - Industriemagazin für das produzierende Gewerbe 33/2010. [7] Bauer M. (hRsg.), Bender M., Braun M., Rally P., Scholtz O., Leichtbauroboter in der manuellen Montage, E-Publishing, Stuttgart, 2016 [8] Mueller R., Vette M., Geenen A., SAE International, Potentials of Human-Robot-Cooperation in Aircraft Assembly Systems, Seattle 2015 [9] Feldmann, K.; Schöppner, V.; Spur, G. “Handbuch Fügen, Handhaben, Montieren.” Hanser München, 2014. Pp. 327-335. [10] Berndt D.; Sauer S. “Visuelle Assistenz – Unterstützung bei der Durchführung komplexer Montageaufgaben“ Werkstattstechnik online 102. [11] Deiterding, J.; Henrich, D. “Spezialisten überflüssig - Die Sensorik Integration.” Computer & Automation - Fachmagazin der Fertigungsund Prozesstechnik 2009.
21
ScienceDirect Procedia Manufacturing 11 (2017) 13 – 21
27th International Conference on Flexible Automation and Intelligent Manufacturing, FAIM2017, 27-30 June 2017, Modena, Italy
Skill-based dynamic task allocation in Human-Robot-Cooperation with the example of welding application Prof. Dr.-Ing. Rainer Müllera, Dipl.-Wirt.-Ing. (FH) Matthias Vette M. Eng.a, Aaron Geenen M. Eng.a* a ZeMA - Centre for Mechatronics and Automatisation gGmbH Gewerbepark Eschberger Weg 46, 66121 Saarbrücken, Germany
Abstract Due to technological and organizational boundary conditions, it is often difficult to solve the problem of automation for assembly processes. The development of such automation is subject to technological challenges and economical risks due to a high number of part variants as well as the complexity of reliably managed assembly processes. One solution for the flexible and skill-based automation of processes is represented in Human-Robot-Cooperation for the assembly of high quality machines for the medical industry. Instead of an inflexible, fully automated approach, a semi-automated method is being developed that can be easily controlled by the operator on the shop floor. Therefore, know-how gained from manual processes will be efficiently transferred into the assembly system. © by Elsevier B.V. by This is an open access article under the CC BY-NC-ND license © 2017 2017Published The Authors. Published Elsevier B.V. (http://creativecommons.org/licenses/by-nc-nd/4.0/). Peer-review under responsibility of the scientific committee of the 27th International Conference on Flexible Automation and Peer-review under responsibility of the scientific committee of the 27th International Conference on Flexible Automation and IntelligentManufacturing Manufacturing. Intelligent Keywords: Automation system, Robot technologie, Assembly station, Welding process, Human-Robot-Cooperation, Skill-based dynamic task allocation, Human-Maschine Interaction,
* Corresponding author. Tel.: +49 (0) 6 81 - 85 787 - 520; fax: +49 (0) 6 81 - 85 787 - 11. E-mail address: [email protected]
2351-9789 © 2017 Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). Peer-review under responsibility of the scientific committee of the 27th International Conference on Flexible Automation and Intelligent Manufacturing doi:10.1016/j.promfg.2017.07.113
14
Rainer Müller et al. / Procedia Manufacturing 11 (2017) 13 – 21
1. Introduction Numerous variations in combination with small part quantities represent a particular challenge in special machine and plant construction [1]. Companies, in particular smaller enterprises, often have a lot of experience regarding specific as well as manual processes. Due to high wages, however, small and medium-sized enterprises (SMEs) of the established special machine construction industry are under severe economic pressure. Furthermore, the knowhow in low-wage countries is increasing, causing considerable international competition [2]. Experience has shown that full automation of such production cycles is often inefficient due to the high variability of products paired with small batch quantities [3,4]. Moreover, the development and efficient operation of an assembly system are further complicated by low volumes of varying quantities. In addition to this, small enterprises lack the experience of operating with automated systems that can only be used to a limited degree. For the implementation of efficient automation, it is necessary to develop flexible and adaptable production systems that can be applied to a variety of tasks [3]. This ensures high efficiency of the production plants [3]. One solution approach for these flexible automation requirements is Human-Robot-Cooperation (HRC). This solution can be demonstrated in the example of a welding process for manufacturing filter units for hem purification (figure 1a). a b
Fig. 1. (a) Example of manufacturing filter units for hem purification (Woll Sondermaschinenbau) (b) Welding process by operator (4by3)
The filter unit machine is comprised of a solid metal frame with the addition of control components, actuators, and sensor modules. The metal frame can be built from a variety of assemblies. In these types of metal frame assemblies, welding is typically used as the joining procedure. Currently, these processes are completed manually by a skilled welding expert (figure 1b) [5]. The focus of this assignment includes the setting up the assembly cell, loading and unloading of the assembly parts, tacking the assembly section together, preparing the seams for welding, and welding the seam. The requirements of the medical industry are subject to high quality standards which pose a high degree of difficulty for automation. Any sub-assemblies which come into contact with organic liquids must be made out of stainless steel. Additionally, all welded joints of the assemblies must be pore-free and free of particles so that corroding of the assemblies can be avoided. Defective assemblies may not be returned to previous processes for rework. Rather, such assemblies must be thrown out. Other influencing factors for the automation of such a system come from the welding process itself. Skilled operators are able to weld complex and short welds quite easily, however, the welding of longer seams leads to an increase in the probability of weld defects. This is due to the limited motor abilities of humans. Another important factor of weld quality is ensuring an organized welding sequence. The ability to have one single welding sequence is very important for a product’s quality [5]. This sequence is determined by an experienced engineer during the planning phase of the assembly. If the welding sequence were to be performed out of order, irreversible warping may occur. Component warping such as this can often times only be detected using measuring technology during final inspection and causes expensive follow-up. Until now, there is no process that ensure the welding order is performed in a specific sequence. The idea of the automation system designed by ZeMA is to support the operator in the production process using HRC robot systems and innovative assistance systems to increase the efficiency and quality of the end product. These increases can be obtained using skill-based task planning to allocate various task to the human or the robots. Along with this, a semi-automated system is was chosen instead of full automation for its flexibility and versatility. This system will also have the ability to be controlled by the operator easily and intuitively on the shop floor. The
Rainer Müller et al. / Procedia Manufacturing 11 (2017) 13 – 21
technical know-how that the operator has gained from manual processes will be seamlessly transferred into these semi-automated production processes. Such a production system requires a methodology for innovative operation and a control approach that is able to economically produce a variety of goods in cooperation with the operator. This is why ZeMA has developed a Human-Machine Interface for the visualization and intuitive operation of such a system. The implementation of such a semi-automated welding processes in special machine production offers a large potential for efficiency improvements, lower costs of production, and increased process capability. 2. Spectrum of HRC Robot Systems There are many ways in which humans and robots can work together [7]. In order to choose a specific methodology for the automation system, it was important to understand the distinct advantages and disadvantages of each one. In conventional methods, robots are separated from the operators entirely, often using fences or other safety devices. Though this may seem to be the best method due to the assurance of safety, it can regularly cause difficulties if the manufacturing company has little factory floor space. Not only that, but the system also loses the ability to quickly change process parameters if the operator is fenced off from the robot at most times. Along with this, valuable time is lost transporting parts in and out of the work spaces by the operator. One way to relieve these complications is to remove the fences while still keeping the work spaces of the robot and operator separate [6,7]. This method is known as Autarkic or Coexistent [7]. To ensure the safety of the system, the robot uses certain safety devices which can, for example, detect the presence of an operator in the robot’s work space [7]. The difficulty that arises with this method is that the part must still be transported to and from the robot and human work spaces. Also, due to the safety features of this system, the robot is not allowed to perform any actions during the time that the operator is placing the part in the robot’s work space [6]. The transportation and placement procedures cost valuable time within the manufacturing process. To alleviate these time costs, the human and robot can choose to operate in a synchronized fashion (figure 2a) [7]. This method combines the two work spaces while allowing only the human or robot to operate inside at any given instance. In order to improve the efficiency of this system once again, the robot and operator must be able to work in the same area at the same time, shown in figure 2b. This can be achieved using the cooperation method. This method allows the operator and robot to work in the same work space at the same time on separate tasks [7]. When the operator needs to work on the same task as the robot, the collaboration technique must be used d [7]. ature a New technologies with special safety feature b enable cooperation and collaboration techniques such as these.
Manual welding seam
Configuration of the station
Fig. 2. (a) Human and robot in a cooperative work space (b) and in a synchronized work space
In a welding application for the filter units of this project, there are several HRC techniques which can be chosen for use. However, since the robot is handling the welding gun, a combination of several methods will be implemented. To start, the robot and human will work in cooperation during the configuration of the assembly station. This allows the operator to use Teach-in methods for the configuration of station locations and to perform additional process tasks while the robot executes other setup procedures. It is important to remember, however, that the primary concern during this welding process is the safety of the operator. During the welding process, large amounts of heat and light are produced. For this reason, the robot must wait until the operator is out of the work space to start the process, as defined by a synchronized system. The robot uses position sensors, such as safety shut-
15
16
Rainer Müller et al. / Procedia Manufacturing 11 (2017) 13 – 21
off mats, to detect whether the operator is within danger. These safety devices are placed around the affected work space and monitor if any humans are within it based on pressure sensors in the mats. HRC robot systems switch to different modes between cooperative and conventional control if human is in or out side of the work space. When nothing is detected, the robot is allowed to proceed with the welding process. 3. Characteristics of HRC Robot Systems It is important for ZeMA to understand all of the key features and characteristics of HRC robots and how they apply to current products in order to make the developed system flexible enough to allow for a wide range of uses and robot implementation. When it comes to defining the key characteristics of HRC robot systems, not all robot suppliers have the same strategy. Many suppliers go after different concepts, although, there are several key features regarding such robots which nearly all of them include. Among the most important of these features are mobility, the fast commissioning of the robot systems, intuitive operation concepts of the system, as well as safe and cooperative use in a process. [8] The comparison of different HRC robot concepts shows selected advantages and disadvantages of robots available on the market. Besides the classic parameters of a robot such as load-capacity, workspace, and reach, new technologies offer a variety of different features. These features include, but are not limited to, distinctive safety functions, integrated sensor technology, 7 axes of rotation, and integrated grippers. With all of these interesting capabilities in mind, it is important to note that HRC robot systems are not a solution for every automation need. The advantages and disadvantages of these systems can only be estimated after a thorough analysis of the individual requirements [8]. Once all the various parameters for different systems are analyzed, ZeMA can tailor the developed operation concept to the system which best fits the application. 3.1. Key characteristics of HRC robot system Different concepts such as platform systems, linear axis systems, and rapid clamping devices lead to a high mobility of the robots. HRC robot systems on a platform can be often times easily rearranged. The platforms don’t always have to be autonomous systems, rather, the robot can be moved manually or with simple tools such as rollers, forklifts, or air cushions. In the assembly process, dynamic forces during the motions of the robot often require one to set up weights on the platform and/or static clamping fixtures to the production ground or process station. Such a mobile platform includes the necessary robot control system which is integrated into the platform. The platforms are equipped with a higher level control system which can be used for the connection to external sensor systems. To use the mobility of the robot systems efficiently, they must be put into operation again quickly after reconfiguration. The fast identification of reference coordinate systems in the specific assembly station, the parts to be assembled, the robots base itself, and the tool are all functionally imperative. Various procedures with external measurement systems (e.g. Indoor GPS, laser tracker), integrated force monitoring, or optical sensors can be used for quick environment identification and calibration. Depending on the application, the optical sensors remain the most economical solution. These measuring methods allow for a rough positioning of the robot in the assembly area and the exact determination of the robot position in relation to the reference coordinate system of the specific station. HRC robot systems not only provide the quick setup of a robot cell, but also intuitive operation concepts which allow simplified use of the robot with little to no specialist knowledge. This enables the operator to create or adjust robot applications directly on the shop floor in a short amount of time. An example of this includes the direct adjustment of a path through manual guidance of the robot’s kinematics or gesture controlled programming [9]. To fully benefit from the advantages that result from direct human and robot cooperation, the boundaries between robot and human have to be eliminated. With integrated safety features, the HRC robot system enables a direct cooperation between human and robot without separation devices. This can all be accomplished while meeting the relevant norms and guidelines as well as a risk analysis [6]. The HRC robots available on the market distinguish themselves mainly by their safety strategies. Shown in figure 3, these HRC robot systems usually have a combination of safety features to allow for task sharing in an overlapping work space. In general, the security
Rainer Müller et al. / Procedia Manufacturing 11 (2017) 13 – 21
features can be divided into four categories. The first of which are internal sensors. Examples of internal sensors include joint current sensors or torque sensors which provide information about unexpected forces to prevent collisions. The next category, external sensors, describes all the safety elements that are integrated by a higher-level control in the robot system, e.g. a safety PLC. This includes the supplementary protective devices that can be separate from or a part of the robot such as tactile protection covers or laser detection systems. The physical features of the robot can also be designed to provide an inherent security for the humans through the safety feature of robot design. The safety feature known as process design reduces the risk of injury of human by cleverly adapting the process. This is usually done by reducing the degrees of freedom and/or reducing the velocity of the manipulator when human contact is anticipated. Another way to adapt the process is to specially encapsulate the process tools for additional safety. Additional sensors for the detection of the surrounding environment can be included as well [6].
Fig. 3. Overview of safety features according the HRC robot systems (DLR, Bosch, ABB, Automation trends)
Other than the safety stop of the robot when exceeding the force, torque, or power limits, the robot can monitor defined work space to ensure safe operation. This can be implemented through integrated sensors or external systems such as laser scanners and safety contact mats. One specific solution for the application of welding filter units is initiated if an operator enters the intended work space of a robot. Once something is detected within the work space, the sensor system lowers the speed of the robot or stops its motion entirely. Endangering the operator is therefore eliminated. After the work space is cleared, the program will continue automatically. These features of the robots allow new types of cooperation by combining the cognitive and locomotive abilities of the operator with the precision and consistent quality of the robot into one process [10]. Additionally, the new system developed by ZeMA allows for the integration of a large variety of HRC robots and can be easily used for countless processes such as the filter unit welding shown in this project. 4. Skill-based and Dynamic Task Allocation In order to achieve maximum efficiency, the operator must adapt his or her workload according to their abilities. If the operator is under loaded or overloaded, their ability to hold their attention to a task will suffer. Robots, on the other hand, are able to hold their attention to a task independent of how many operations they must perform. Within the same idea as attention, performance level can be fairly varied for an operator throughout the day. This is due to human error as well as other uncontrollable factors. Robots, on the other hand, are able to maintain a constant performance level throughout its entire work process. One advantage of humans, however, is that they have an automatic sense of touch, or sensitivity. In order for robots to have similar abilities, they must attach special and usually expensive sensors to the robot. Another advantage of humans is that they are highly mobile. They can change work space size and location relatively easily. For robots, however, this can be quite difficult due to the fact that robots are often fixed within their work space. Though humans have been shown to be quite adaptable, they are only able to operate within a limited accuracy without the use of tools or other forms of production equipment. Robots, however, are able to operate in a high accuracy range. In the category of strength as well, humans are easily outperformed by robots. This case is amplified when considering the way in which the operator must lift and hold certain loads. The process of welding requires a large range of skills in order to be efficiently and accurately completed. A human has many advantages when it comes to unique movements and tasks that would be difficult to program into a robot in short period of time. An example of this in the filter unit project is that an operator is able to set up a station or prepare a part for assembly by taping seams. Processes such as these pose a high degree of difficulty for robots in
17
18
Rainer Müller et al. / Procedia Manufacturing 11 (2017) 13 – 21
the case of single part production. An operator can also weld unique and inaccessible areas that would take a lot of programming for a robot to complete. Besides their movement capabilities, humans are also able to complete visual inspection tasks rapidly and effectively. In the case of welding, trained operators can quickly determine the quality of a weld by a simple examination. Another process which an operator can easily overcome is adjusting their welding style based on the orientation of the weld seam. For example, if the seam is vertical, the operator must compensate for the molten weld bead wanting to drip down the seam. A robot, on the other hand, is more suited for welds with constant parameters. An example of this is being able to weld long straight seam with ease. Because of the robot’s mobility, it is able to complete long welds without having to section them up. This ability poses a great advantage to the overall strength of the weld and takes little time to complete. Another advantage of a robot is that the parameters of the welding process can easily be changed. Along with this, the robot can provide consistent heat penetration into the material due to its ability to control the process accurately. Finally, the robot has exact control over its process. Speed, distance, and orientation can all be controlled very accurately and precisely to ensure the desired result. Due to the limitations and advantages of both workers and robots, ZeMA has allowed the operator to allocate tasks on the shop floor based on process efficiency evaluations. This real time task allocation is explained in further detail in the next section of this paper. The unique and versatile skill set of the operator aided by the precise and consistent operation of a robot is a combination that will change the future of welding processes (figure 4). It is because this combination of physical and mechanical advantages that ZeMA has approached this welding concept with a semi-automated system.
Fig. 4. Guideline for skill-based, dynamic task allocation in Human-Robot-Cooperation
5. Operation Concepts of HRC Robot System A key element for the successful operation of HRC systems is the Human-Machine Interface. This interface is where the operator can interact with the system and perform various tasks, such as programming. The term programming is defined as the definition of the movement and logical procedure of the user program during the production. The downtime during programming and reconfiguration of the robot application is an important influencer of the efficiency of the robot’s implementation. This is especially true if this process leads to a delay in the production flow or if the programming is unable to be performed in parallel with the production [11]. The complexity of the programming for HRC systems is often increased because of the demands of cooperation between humans and robots as well as the various abilities provided by robots. Because of this, programming is typically done in special languages and requires advanced programming knowledge. Therefore, the simplification for use on the shop floor is quite challenging. With the complexities of programming a system such as this in mind, custom control concept must be developed so the operator can control and program the robot quickly and intuitively. Luckily, the control concept developed in the 4by3 and TRSE projects provides a solution in the form of a hybrid programming method. This method enables the setup of a robot program through the combination of preprogrammed macros and online adjustments made by the operator. Using a graphic user interface, this approach automatically creates a robot program out of the macros
Rainer Müller et al. / Procedia Manufacturing 11 (2017) 13 – 21
and previously taught positions. This control concept, developed by ZeMA, distinguishes itself from other concepts through the use of a simple simulation environment, a universal robot interface, the inclusion of sensors, and a visual interface. Another advantage to the programming process is that it is written with CAD (Computer-Aided Design) data or with models generated from camera pictures. The integration of which is done via common data formats. This gives the user a very visual and intuitive work platform. Within this control concept (figure 5), CAD data can be used to directly program the robot system. For the filter unit project, this would be done by drawing seams on the model in a design program like SolidWorks and then adding a welding process to the program. Once the CAD-data and welding tasks are inputted, the virtual model can then be finalized. This model is a combination of process information according to WPS (Welding Procedure Specification), location and orientation data, and task information which the robot will use to complete its various responsibilities. The robot path and the orientation of the end effector are loaded from the virtual model and saved as macros. The completed virtual model can then be used to create a workflow for the robot and the operator. This process is completed by a trained professional before the work has begun. The tasks planned for the operator are marked in red while the tasks for the robot are marked in yellow. The specialist can also exchange tasks between the robot and the operator depending on which they find most efficient for each specific task. If a weld is fairly complex or inaccessible, for example, they can choose to switch this specific task to the operator’s workflow because the robot will most likely have a difficult time accomplishing it. This transfer of tasks is completed in the virtual model by simply selecting the task and altering its properties. When the final process is confirmed by the operator, the generated data is obtained from the robot via a universal interface. After the virtual model and workflow have been constructed, the user must run through a configuration phase. This phase is used to define the coordinate systems and boundary conditions for the robot system either using teach-in methods to save important locations or by using pre-programmed movements set to find these locations. Once the configuration is completed, the user can interface with the machine in order to confirm the correct task description. Examples of this could include the operator moving weld seam locations because the joint locations have been changed or correcting small details regarding the orientation of the process tool and the robot path. Movements such as this can be completed by simply clicking and dragging the task indicators in the virtual model to edit their positions. Next, the user must run through some final process definitions. This is done to assure the correct path and tasks of the robot. It is important to note that with this system developed by ZeMA, long hours spent on programming tasks are no longer required. All of the information needed by the robot is given through the pre-programmed macros designed into the software. Using these macros, any operator with little to no programming experience can set up a welding process. It is this aspect of the system that greatly increases the efficiency of the various process planning stages.
Fig. 5. Intuitive operating method for an HRC robot system
6. Projection System of HRC Robot Station By supporting the operator in the welding process using the previously described robotic systems, the quality and efficiency of work can be greatly improved. Additionally, the quality and efficiency can be further improved with the use of a combination of additional assistance systems. Visual assistance can be offered using digital or laser projection systems. These projection systems are currently used in many facilities to support the operator in manual
19
20
Rainer Müller et al. / Procedia Manufacturing 11 (2017) 13 – 21
tasks to ensure the quality of the products. In the assembly of special machinery, visual assistance systems are used to provide the operator with instructions as well as assembly information directly on the shop floor. [8] Depending on what information is being visualized, different systems are more suitable than others. A Laser projection system’s large projection distance offers high contrast images and detailed precision of the projection at the same time. These systems are suitable to display the position of a component and provide other information about an assembly process. However, a digital projector is particularly suited for high resolution images, colored visualizations, and displaying more complex work instructions. [8] At ZeMA, Human-Robot-Cooperation is advanced by combining existing technologies with self-developed user and programming applications. Alongside HRC robot systems, a visual assistance medium can be used as a communication device between human and robot. A digital projector is used on the shop floor to visually support the user during the intuitive programming process. Figure 7a and 7b shows the newly developed visualization system. The benefit of such a system is the added flexibility gained by being able to adapt to any changes in the current process. In this example, the operator needed to add a new weld seam due to a change in the process. The addition and adjustment of this new welding seam is easily performed online by the operator on the shop floor. The developed visual assistance system displays both the tasks for the robot and worker on the part in order for the worker to actively determine efficiency improvements for the process. The visualization system also notifies the operator whether the system has been appropriately calibrated or not. After modifying the process in any way, the operator must confirm the adjustments. In addition to the visualization of the robot’s weld path on the part, the developed assistance system can be used to provide the operator with instructions directly at the work space (figure 6a). An example of these instructions could be the visualization of the sequence of welding seams. With WPS in mind, the developed assistance system marks the dynamic task allocation between the human and robot on the part in each workflow (figure 6b). This helps the operator control the welding sequence of the product and simultaneously documents the workflow with the adjustment of the welding tasks. This system ensures minimal process errors will occur resulting in a higher quality product. a b
Fig. 6. (a) Easy addition and correction of a new welding seam (b) Visualization of the sequence of welding seams on the shop floor
Summary & Conclusion In the manufacturing of tailored machinery, automation can be challenging due to high variability and complexities. The automation of such systems is made much simpler, however, through the use of the process concepts developed at ZeMA. Due to the addition of skill-based process planning, different tasks can be efficiently completed by actively assigning them to the operator or the robot based on their individual skill sets. These skills can also be mapped dynamically with the use of this concept. The efficiency of automated systems can be further improved through the use of multiple cooperation methodologies. Using these methodologies, the operator can safely work with a variety of HRC enabled robots because of the system’s ability to adjust to different robots and safety mechanisms. The programming of such robots can often be complex and require comprehensive knowledge. However, this operation concept allows for easy and intuitive programming through the use of a graphic and Human-Machine Interfaces as well as pre-programmed macros. Since there is little to no programming knowledge required, nearly anyone can plan and operate a welding program using this system. This allows for an efficient and economical production process. By means of this user interface for intuitive robot control, easy and innovative
Rainer Müller et al. / Procedia Manufacturing 11 (2017) 13 – 21
opportunities for automation have been created in order to enable the development of flexible and economic processes. Processes like these will guarantee the competitive edge of high-wage countries in the future while at the same time giving smaller companies the ability to implement automation techniques without extensive experience. Using this concept, we have the chance to obtain a higher quality of manufacturing processes while at the same time increasing the productivity of the process. References [1] McKinsey&Company (Hrsg.): Zukunftsperspektive deutscher Maschinenbau. Erfolgreich in einem dynamischen Umfeld agieren. Berlin, 2014. [2] Deutsche Mittelstands Nachrichten: http://www.deutsche-mittelstands-nachrichten.de/2014/07/63764/; Maschinenbauer verlagern Produktion ins Ausland. Published 07.07.14. Last viewed on 09.02.17 [3] Juhani Heilala, Paavo Voho, (2001) "Modular reconfigurable flexible final assembly systems", Assembly Automation, Vol. 21, pp.20 – 30 [4] Müller, R.; et al. “Wandlungsfähiges Montagesystem für Großbauteile am Beispiel der Flugzeugstrukturmontage.“ Zukunftsfähige Montagesysteme. Wirtschaftlich, wandlungsfähig und rekonfigurierbar. Stuttgart: Fraunhofer Verlag 2013. [5] Deutscher Verlag für Schweißtechnik (DVS) GmbH (Hrsg.): Fügetechnik Schweißtechnik. Düsseldorf, 1987. [6] Hülke M.; Umbreit M.; Ottersbach H. “Sichere Zusammenarbeit von Mensch und Industrieroboter.“ Maschinenmarkt - Industriemagazin für das produzierende Gewerbe 33/2010. [7] Bauer M. (hRsg.), Bender M., Braun M., Rally P., Scholtz O., Leichtbauroboter in der manuellen Montage, E-Publishing, Stuttgart, 2016 [8] Mueller R., Vette M., Geenen A., SAE International, Potentials of Human-Robot-Cooperation in Aircraft Assembly Systems, Seattle 2015 [9] Feldmann, K.; Schöppner, V.; Spur, G. “Handbuch Fügen, Handhaben, Montieren.” Hanser München, 2014. Pp. 327-335. [10] Berndt D.; Sauer S. “Visuelle Assistenz – Unterstützung bei der Durchführung komplexer Montageaufgaben“ Werkstattstechnik online 102. [11] Deiterding, J.; Henrich, D. “Spezialisten überflüssig - Die Sensorik Integration.” Computer & Automation - Fachmagazin der Fertigungsund Prozesstechnik 2009.
21