Assembly cell for the manufacturing of flexible solar modules in building integrated photovoltaics

The current use of photovoltaics is often limited to the utilization of roof surfaces or ground-mounted systems. In particular, building integrated photovoltaics (BIPV) have enormous potential to make energy production more sustainable, because the energy is generated where it is used. However, most of these modules either do not meet the aesthetic requirements of the architects as well as the building owner or are uneconomical, since visually appealing building-integrated PV modules cost several times more than standard modules. In this article, an approach for a (semi) automated assembly line that allows geometry- and material-flexible manufacturing of PV modules is presented. The challenges in automating the flexible manufacturing processes include mainly the handling of limp components and the complexity of geometry variability. Appropriate gripper systems are required to ensure safe and reliable handling of the components. A gripper developed in this article offers the ability to flexibly deposit solar strings. Preliminary tests show that 66% of all conducted trials meet the accuracy requirements

Investigation of the potential for an automated disassembly process of BEV batteries

Current electric vehicle battery recycling processes often begin with the manual dismantling of the battery packs. In consideration of occupational safety and in view of the increasing sales of electric vehicles, an automated dismantling of batteries has to be investigated. Therefore, different manufacturers' battery pack designs are examined first and especially the common joining elements are determined and characterized. The results show a high diversity between the individual systems, which influences the potential for automation. Based on these investigations, a possible layout of an automated dismantling cell is developed

Intuitive robot programming using augmented reality

The demands on companies caused by the markets are becoming more and more fast-moving and complex. Reasons are the increasing number of variants of products as well as reduced product life cycle times. This is particularly relevant for assembly tasks, since a very high flexibility and adaptability to varying ambient condition must be ensured in this area. Therefore, a lot of steps are currently being carried out manually. However, if an automation is attempted in the field of assembly, companies are often facing a trade-off between a high degree of automation and flexibility of the production system. A concept to increase the automation rate in assembly tasks can be seen in the use of collaborative robots, so that the benefits of both, humans and robots, can be combined to accomplish the task. In doing so, one key issue is to simplify and thus to accelerate the programming process so that the necessary programming skills of employees can be reduced. Although some of today’s collaborative robots already offer good programming approaches like kinesthetic teaching, this article introduces a new and more intuitive programming method which is based on Augmented Reality. For this purpose, components of an assembly group are virtually linked with CAD models by using optical markers. The operator can then virtually assemble the components according to the assembly sequence. Results of first tests indicate, that once the assembly process is recorded, the robot can accomplish the assembly in reality. Finally, possibilities for future developments are presented

Adaptive aerodynamic part feeding enabled by genetic algorithm

Aerodynamic feeding systems represent one possibility to meet the challenges of part feeding for automated production in terms of feeding performance and flexibility. The aerodynamic feeding system investigated in this article is already able to adapt itself to different workpieces using a genetic algorithm. However, due to the operating principle, the system is susceptible to changes in environmental conditions such as air pressure and pollution (e.g. dust). To minimise the effect of ambient influences, the system must be enabled to detect changes in the feeding rate and react autonomously by adapting the system’s adjustment parameters. In this work, based on pre-identified factors interfering with the aerodynamic orientation process, a new approach is developed to react to changes of the ambient conditions during operation. The presented approach makes us of an alternating sequence of monitoring and corrective algorithms. The monitoring algorithm measures the ratio of correctly oriented parts to the total number of fed parts of the process and triggers the corrective algorithm if necessary. Simulated and experimental results both show that an increased feeding rate can be achieved in varying conditions. Furthermore, it is shown that integrating both known process and parameter information can reduce the time for re-parametrisation of the feeding system

Efficient Use of Human-robot Collaboration in Packaging through Systematic Task Assignment

The ageing workforce in Germany is a major challenge for many companies in the assembly and packaging of high-quality products. Particularly when individual processes require an increased amount of force or precision, the employees can be overstressed over a long period, depending on their physical constitution. One way of supporting employees in these processes is human-robot collaboration, because stressful process steps can be automated in a targeted manner. With conventional automation, this is currently not economically possible for many processes, as human capabilities are required. In order to achieve a balanced cooperation based on partnership, as well as to use additional potentials and to consider restrictions such as process times, it is necessary to ensure a good division of tasks between human and machine. The methodical procedure of allocation presented in this paper is based on the recreation of the process from basic process modules conducted by the process planner. Subsequently, these processes are divided according to the respective capabilities and the underlying process requirements. The company-specific target parameters, such as an improvement in ergonomics, are taken into account. The assignment procedure is described in a practical use case in the packaging of high-quality electronic consumer goods. Furthermore, the use case demonstrates the applicability of the approach. For these purposes, the parameters and requirements of the initial and result state of the workplace are described. The procedure and the decisions of the approach are shown with regard to the achievable goals

A Method to Distinguish Potential Workplaces for Human-Robot Collaboration

The high dynamics of globalized markets and their increase in competition, as well as the demographic changes in western countries causing an increasing shortage of skilled personnel are resulting in major challenges for production companies today. These challenges relate in particular to the processes of assembly forming the last process step in the value chain due to its high share of manual labor. Collaborative assembly, which is characterized by immediate interaction of humans and robots, utilizes the strengths of both partners and is seen as an opportunity to achieve a higher level of flexibility in assembly just as well to support and relieve people of for instance non-ergonomic tasks through automation at work. Although almost every robot manufacturer already has collaborative systems in its product portfolio, these are not yet widely used in industrial production. This might have a variety of reasons, such as the fear of a risky investment or the lack of expertise within the company related to collaborative systems. This article shows a conceptual method that helps companies implementing human-robot-collaboration in their production more quickly and with less implied risk, thus addressing the forthcoming challenges. As a first step, companies must be qualified to make a suitable selection for a possible collaboration scenario. To achieve this, they need a tool to analyze and to evaluate their production processes according to their suitability for human-robot-collaboration. An important feature for an easy and effective use is that the process is formalized so that employees of companies can quickly and easily analyze different processes. The necessary criteria and procedures are developed accordingly and are integrated into the selection method. The main goal is to give the company a recommendation which of their processes are most suitable for human-robot-collaboration, so that they can be used effectively in their production

Implementation and Testing of a Genetic Algorithm for a Self-learning and Automated Parameterisation of an Aerodynamic Feeding System

AbstractAn active aerodynamic feeding system developed at the IFA offers a large potential regarding output rate, reliability and neutrality towards part geometries. In this paper, the procedure of a genetic algorithm's into the feeding system's control is shown. The genetic algorithm automatically identifies optimal values for the feeding system's parameters which need to be adjusted when setting up for new workpieces. The general functioning of the automatic parameter identification is confirmed during tests on the convergence behaviour of the genetic algorithm. Thereby, a trade-off between the adjustment time of the feeding system and the solution quality is revealed

Gesture-Based Robot Programming Using Microsoft Kinect

Part 2: Human Robot Cooperation and Machine VisionInternational audienceCompanies have to face constantly changing framework conditions. Product lifecycles are reduced and the number of variants increase as a result of increasing product individualization. To ensure that production systems such as robots can achieve this flexibility, more and more programming procedures are being developed that do not require a high level of qualification. This thesis deals with an intuitive approach that can be used for programming adhesive joints. With the help of the simple pointing to surfaces, a path corresponding to the intersection line of the two planes is calculated. The required algorithm for fingertip recognition is implemented with the help of Voronoi diagrams. The recognition of the planes is based on a region growing algorithm. The accuracy of the whole process is limited by the current technical state of the art and does not yet meet the necessary requirements

Prediction of Disassembly Parameters for Process Planning Based on Machine Learning

The disassembly of complex capital goods is characterized by strong uncertainty regarding the product condition and possible damage patterns to be expected during a regeneration job. Due to the high value of complex capital goods, the disassembly process must be as gentle as possible and being adaptable to the varying und uncertain product's state. While methods based on data mining have already been successfully used to forecast capacity and material requirements, the determination of the product’s or component's condition has become apparent in the recent past. Despite the rapid increase in sensor technology on capital goods such as aircraft engines and their use for condition monitoring due to countless interfering effects, it is only possible to react spontaneously to the product’s condition. So far, we have concentrated on product condition-based prioritization of disassembly operations in a logistics-oriented sequencing strategy. In this article, we present an approach to predict disassembly process-planning parameters based on operational usage data using machine learning. With the prediction of disassembly forces and times, processes, tools and capacities can be efficiently planned. Thus, we can establish a component-friendly disassembly process adaptable to varying product conditions. In this article, we show the successful validation on a replacement model of an aircraft engine