Digital transformation projects are crucial to maintaining the competitiveness of industrial companies. The handling of data is a frequent weak point in companies. Digital data logistics deals with the definition and technical implementation of processes to make data available and usable. However, the requirements that must be met to implement such digital data logistics are not generally defined, although they are essential in order to successfully carry out budgeted transformation projects. This paper focuses on the requirement gathering for data logistics processes. The most important requirements are identified and documented. In this way, a method for requirements gathering is presented that enables the process to be as objective, complete and efficient as possible using performance indicators as well as proven techniques and tools. The processes and results described in this paper are part of a team work as part of the industrial project DIAMOND (Digital Plant Modeling with Neutral Data Formats).

The assembly of control cabinets is highly affected by manual processes. For reasons such as the shortage of skilled workers, there is a considerable need to automate the production steps. The automated wiring of prefabricated wires, which is a mayor process step in the manufacturing, is not automated yet. Besides different sensor technologies, a reliable tool for assembly must be developed. This article discusses the challenges and criteria for the development of such a tool. The most important functions of the tool include the handling of wires with different lengths, cross-sections, and colors as well as the consideration of close mounting positions. Based on a morphological box, a tool concept is derived and validated via tests on a demonstrator.

The digital twin (DT) is used as a tool for digital verification of the phases of construction as well as a bidirectional connection between the product and the digital dependent in the production phase. It can be used to predict and control the behavior of a product during virtual commissioning. Due to the increasing number of product variants, the complexity of the necessary data structure is rising. A product configurator can be used to master the data structure. The product configurator creates digital product twins (DPT) of components. To implement cross-project product components consistently, a generic product component template is required. This paper presents a method for creating such models. The model of the product components is based on two modeling approaches that are applied in AutomationML (AML). Finally, the model is verified in a concrete application.

Speed and separation monitoring (SSM) as well as power and force limiting (PFL) are two of the four permissible collaborative operations in human-robot interaction (HRI). Current standards and guidelines provide users and system integrators with a simple basis to calculate permissible separation distances between human workers and robots. However, problems occur in practical implementations, as the safety zones are oversized due to various simplifications and corresponding path velocities have to be significantly reduced. This leads, for example, to cycle time losses and wasted space within the respective HRI application. The present paper describes an approach to combine the SSM and PFL collaborative operations and to exploit the optimization potential for robot motion planning and the design of collaborative workstations. To localize the necessary human body regions, we integrate a method from the field of machine learning. Using an exemplary HRI scenario with the PILZ lightweight robot PRBT, we validate the approach presented here and discuss initial results.

One of the next steps in factory automation might not exclusively be an automation issue, but instead combining robot and human skills to further improve industrial work processes. For various reasons, there is still a low dissemination of hybrid work processes characterized by direct human robot interaction. For instance, it is very difficult to decide which manual work processes are eligible for a transformation to a human-robot interactive process. Thus, the research project MANUSERV delivers a tool to support this decision process. Here, the central concept is a task planning system capable of generating automated as well as hybrid human-robot solutions. Therefore, a structured description of manual work processes forms the input to the planning system. Subsequently, a simulation system verifies and evaluates the proposed solutions and generates the necessary information for a transformation of the planning results to a real application scenario.

The number of industrial applications where a robot needs to unload disordered parts is increasing substantially. The usage of robot vision is highly preferred to obtain reliable results. In the past different algorithms for localizing objects as well as for motion planning to avoid collisions between gripper, object and environment were presented and even some commercial Bin-Picking systems are available. Nevertheless a realistic simulation taking account of various vision and robot systems and path planning strategies to predict cycle times is still not possible. In this paper a universal software framework with the focus on virtual Bin-Picking is presented. Utilizing a generic approach this framework enables the integration of various algorithms for object recognition, motion planning, different types of robots, grippers and vision systems. Thus an efficient simulation of different (virtual) Bin-Picking setups including equipment such as sensor devices or robot controllers within a virtual environment is possible. Furthermore the use of such a system allows the prediction of cycle times, percentage of tangible objects or testing of different Bin-Picking setups.