Armin Lechler

Making existing production systems Industry 4.0-ready

AbstractThis paper presents an approach to how existing production systems that are not Industry 4.0-ready can be expanded to participate in an Industry 4.0 factory. Within this paper, a concept is presented how production systems can be discovered and included into an Industry 4.0 (I4.0) environment, even though they did not have I4.0-interfaces when they have been manufactured. The concept is based on a communication gateway and an information server. Besides the concept itself, this paper presents a validation that demonstrates applicability of the developed concept.

Glocalized cyber physical production systems

Current developments in automation technology deal with “cyber physical systems”. These cyber physical systems have sensors and actors and can make decisions based on their own intelligence as well as partially adapt to changing conditions. For a versatile and networked production cyber physical systems are of limited value. Precisely where the available sensors and actuators have to be combined flexibly due to ever new conditions, these systems find their limits because of their insularity. Limited computing hardware resources and lacking interfaces confine the possibilities of cyber physical systems in production environment. This paper explains how cyber physical systems need to be developed further in order to meet the requirements of a versatile and networked production plant.

Defect reduction in the production of electric drives by downstream compensation and space-resolved inspection

Improving the material efficiency in the production of electric drives is necessary as the electric automotive sector is growing very fast. Here, a method for early defect identification and downstream compensation, which allows defect reduction and consequently waste reduction, is presented. This reduces the waste motor parts (rotor stacks) and decreases the amount of rare earths to be recycled. A new inspection device was developed that allows a space-resolved in-line inspection of single rotor stacks as well as assembled rotors, in the same inspection station. This inspection device was realized as a demonstrator system, which is explained in detail in this paper. The inspection results are used as input for the downstream compensation methods, selective and sequential rotor assembly. Both methods combine stacks that are out of tolerances in such a way that the final rotor is within the specified limitations. Thus, low quality parts form a high quality assembly without having to scrap stacks and magnets.

Control-integrated consumption graph-based optimisation method for energy reduction of machine tools with automated parameter optimisation

With the focus of industrial manufacturing on energy efficiency, machine tools offer energy-saving modes and the new controls have the potential to reach those or even switch off the machine. The switching to these energy-saving states is most commonly executed after a predefined time interval or just manually by the machine tool operator. To enable an automated and energy-optimal switching sequence of energy-minimal operating states of machine tools, a control-integrated consumption graph-based optimisation method is proposed. This uses energy prediction through a consumption graph and calculates operating state trajectories using a graph-based optimisation theory. These trajectories allow an energy-minimal spending of unproductive times. To ensure a widespread application, an automated parameter optimisation is proposed to adapt the consumption graph to the machine tool it is optimising automatically. The saving potential of the approach is demonstrated by a usage scenario from an industrial shop floor setup.

Properties of electrically preloaded rack-and-pinion drives

Ball screw drives are very common in industrial applications and, therefore, thorough analyses of their characteristics exist. Rack-and-pinion drives are a good alternative, if large travel ranges and high dynamics are required. However, they are not scientifically and systematically analysed. Nowadays, either constant mechanical or electrical preload is often used in industrial applications to reduce the backlash of a drive train (Weck and Brecher in Werkzeugmaschinen 3: Mechatronische Systeme, Vorschubantriebe, Prozessdiagnose, 6th edn. Springer, Berlin, 2006). This paper describes the investigation of an electrically preloaded rack-and-pinion drive in an experimental rack. The focus is on backlash, stiffness, friction losses and bandwidth of the examined feed axis dependent on the preload. An open controller allows online variations of the drive system’s preload. The resulting effects are investigated experimentally. The paper shows that increasing preload reduces backlash and increases stiffness and bandwidth, but friction losses raise as well.

Cloud-based control for downstream defect reduction in the production of electric motors

Classical computing is shifted gradually into the cloud, offering completely new possibilities in information usage, computing power and application of learning algorithms. In this paper, a cloud-based architecture of control systems is investigated showing the benefit for multi-stage production systems. All sequential manufacturing and assembly processes are connected via a cloud-based architecture, which allows using information from a previous production step in one of the subsequent steps for downstream deviation compensation. This strategy is applied to the rotor production of electric motors in the automotive industry, as the current production shows high defect rates due to the lack of adequate sensor signals and optimization algorithms. The magnetization process of permanent magnets is executed in saturation, so that the generation of deviations cannot be avoided by process control or process optimization. Instead, the variance in the magnetization signal must be compensated in a downstream process, here the rotor assembly stage. Project results show how such a cloud-based architecture can increase the product quality while decreasing the amount of scrap parts in a real industrial scenario, consequently saving valuable resources like energy and raw materials. Reduction of deviations is crucial for this emerging industrial sector as electric motor production for vehicles is moving towards mass production.

Productivity Increase through Joint Space Path Planning for Robot Machining

Machine tools realize tool movements with high accuracy mainly due to highly developed computerized numerical controls (CNCs). As articulated industrial robots are used more and more for machining, robot controllers (RC) have to be equipped with additional path planning capabilities, similar to machine tools. A RC is very similar to a CNC from a software and hardware point of view, but with one major difference, the RC has an additional transformation stage, the transformation from Cartesian space to joint space. Machining with robots is a field intensely researched in the last years. CNC systems for robots are commercially available, furthermore, more and more CAM systems have extensions for machining with robots. Most of these offer a simulation of the machining process using a robot model, in order to solve the inverse kinematic problem and, additionally, to take into consideration axis motion limits (maximum angular amplitudes) and singularities. Moreover, path planning for machining robots is done in exactly the same way as for machine tools, with the mentioned additional transformation stage. This paper describes the advantages and challenges which result from the integration of the kinematic transformation in the path planning stage.

Communication extension for cloud-based machine control of simulated robot processes

Flexibility and mutability are key features of Industry 4.0 solutions. Current machine controls are monolithic systems connected to local actors and sensors by a field bus. Cloud architectures can be used to develop scalable machine controls with generic interfaces and transmit data via computer networks. This paper presents a communication extension for machine controls to enable manufacturing within cloud-based architectures.

A planning system for generating manipulation sequences for the automation of maintenance tasks

The adaption of autonomous robots to complex assignments like automating maintenance tasks, requires the study of novel planning systems for task generation which use a priori and sensor-based data. This paper presents an approach to disassembly and assembly planning for automating maintenance tasks in production systems. The planning system combines CAD data with visual data from an RGB-D sensor. This allows the creation of a consistent environmental model, which can be used to plan a (dis)assembly task for an autonomous robot. The proposed method allows to compute manipulations directly in the task space of the robot. The algorithm uses a geometric and semantic reasoning concept to compute a relational graph which describes the individual degrees of freedom in-between the components. The proposed algorithm is highly time efficient, thus being particularly suited for the automation of maintenance tasks. With the additional integration of visual data, it is possible to compensate environmental uncertainty from the CAD data as well. This paper describes the planning architecture and algorithms in detail and concludes with an experimental validation.

EcoBotics: Advantages and challenges of building a bamboo robot arm

Sustainability and sustainable development concepts are frequently the driving force for research related to optimizing energy consumption and material use in order to reduce the carbon footprint for different products. EcoBotics aims to analyse the question of sustainability in the area of robotics. In this paper, as a first example of EcoBotics, it is examined what are the advantages and challenges of exchanging the aluminium structure of lightweight robot arms with a sustainable material. Bamboo is used in order to exemplify a sustainable material, but the challenges and the proposed solutions for open problems are valid for any material causing a robot structure with low stiffness.