Rudolf Reinhard

Virtual production intelligence: a contribution to the digital factory

The usage of simulation applications for the planning and the designing of processes in many fields of production technology facilitated the formation of large data pools. With the help of these data pools, the simulated processes can be analyzed with regard to different objective criteria. The considered use cases have their origin in questions arising in various fields of production technology, e.g. manufacturing procedures to the logistics of production plants. The deployed simulation applications commonly focus on the object of investigation. However, simulating and analyzing a process necessitates the usage of various applications, which requires the interchange of data between these applications. The problem of data interchange can be solved by using either a uniform data format or an integration system. Both of these approaches have in common that they store the data, which are interchanged between the deployed applications. The datas storage is necessary with regard to their analysis, which, in turn, is required to obtain an added value of the interchange of data between various applications that is e.g. the determining of optimization potentials. The examination of material flows within a production plant might serve as an example of analyzing gathered data from an appropriate simulated process to determine, for instance, bottle necks in these material flows. The efforts undertaken to support such analysis tools for simulated processes within the field of production engineering are still at the initial stage. A new and contrasting way of implementing the analyses aforementioned consists in focusing on concepts and methods belonging to the subject area of Business Intelligence, which address the gathering of information taken from company processes in order to gain knowledge about these. This paper focusses on the approach mentioned above. With the help of a concrete use case taken from the field of factory planning, requirements on a data-based support for the analysis of the considered planning process are formulated. In a further step, a design for the realization of these requirements is presented. Furthermore, expected challenges are pointed out and discussed.

A Framework Enabling Data Integration for Virtual Production

Due to the increasing complexity of modern production processes, the use of tools providing their simulation is getting more and more common. The simulation of a production process in its entirety, depending on the level of detail, often requires the coupling of several, specialised simulation tools. The lack of uniform structures, syntax and semantics among the considered file formats, the special simulation context and the typical accumulation of huge data volumes, complicates the use of established enterprise application integration solutions. Thus, the need for a tailor-made framework for simulation integration purposes arises. The implementation of such a framework is requested to be easy adaptable, so that changes in virtual production circumstances causes only little efforts in the infrastructure, and at the same time taking care about domain specific purposes. This paper presents such a framework.

Simulation and Interoperability In The Planning Phase of Production Processes

Interoperability is a progressive issue in the development of holistic production process simulations that are based on stand-alone simulation interconnections. In order to tackle the problem of missing interoperability, the standardization of simulation and model interfaces and transfer protocols can be taken into account. This procedure is endorsed by many organistaions like DIN ISO, IEEE, ASME or SISO and one of the most effective proceedings if a new simulation is developed and if the source code of the used simulations is available as well as changeable. However, as most simulations for a holistic production simulation already exist and as those simulations are usually isolated, high precisely solutions, which have no common interfaces for interconnection, a different approach is needed. The contribution at hand focuses on a framework that provides adaptive interfaces to establish interoperability of stand-alone simulations.

How Virtual Production Intelligence Can Improve Laser-Cutting Planning Processes

The complexity of modern production conditions demands integrative approaches in the fields of simulation and analysis to improve product quality and production efficiency. Existing concepts of virtual production meet this need to some extent. However, problems of application interoperability and data compatibility remain. One approach is the definition of a standardized file format, which is costly to create and to maintain. Other approaches avoid the need for a uniform standard by mapping data structures onto a canonical data model. Although these methods allow for simulation and examination of individual elements, the analysis of the integrated process remains a challenge. Here, the data analysis solutions from the field of the so-called intelligence-solutions can prove useful. Within this paper, a use case scenario taken from the field of laser cutting is presented. Herein, the planning for laser cutting is conducted in a modular format. A new concept is presented that addresses the requirements aforementioned and that conforms to the principles of the integration and examination of data. The new concept, called Virtual Production Intelligence, is formed by combining the concept of virtual production with “intelligence solutions” or the goal of gaining knowledge through the analysis of already completed processes.

flapAssist: How the integration of VR and visualization tools fosters the factory planning process

Virtual Reality (VR) systems are of growing importance to aid decision support in the context of the digital factory, especially factory layout planning. While current solutions either focus on virtual walkthroughs or the visualization of more abstract information, a solution that provides both, does currently not exist. To close this gap, we present a holistic VR application, called Factory Layout Planning Assistant (flapAssist). It is meant to serve as a platform for planning the layout of factories, while also providing a wide range of analysis features. By being scalable from desktops to CAVEs and providing a link to a central integration platform, flapAssist integrates well in established factory planning workflows.

The Contribution of Virtual Production Intelligence to Laser Cutting Planning Processes

In order to facilitate the improvement in product quality and production efficiency, many companies use simulation applications. In turn, they face the challenge of making these applications interoperable. Once the interoperability is established, the challenges of understanding and improving the processes arise. They can be overcome by modeling and analyzing the processes in question. This paper presents a use case scenario from laser cutting. A new concept is introduced addressing the challenges aforementioned. It conforms to the principles of the integration and examination of data and combines virtual production with the goal of gaining knowledge through the analysis of simulated processes.

Virtual Production Systems

The use of simulation systems is of significant importance for companies in high-wage countries as the requirements of product- and process quality are generally higher than in low-wage countries due to conditions of the market. Since the implementation of simulation tools is not value-adding in the first place, the performance of virtual product development chain must therefore be continuously increased in terms of greater planning efficiency. Research in the field of virtual production systems therefore addresses the following issue.

Virtual Production Intelligence (VPI)

The research area Virtual Production Intelligence (VPI) focuses on the integrated support of collaborative planning processes for production systems and products. The focus of the research is on processes for information processing in the design domains Factory and Machine. These processes provide the integration and interactive analysis of emerging, mostly heterogeneous planning information. The demonstrators (flapAssist, memoSlice und VPI platform) that are information systems serve for the validation of the scientific approaches and aim to realize a continuous and consistent information management in terms of the Digital Factory. Central challenges are the semantic information integration (e.g., by means of metamodeling), the subsequent evaluation as well as the visualization of planning information (e.g., by means of Visual Analytics and Virtual Reality). All scientific and technical work is done within an interdisciplinary team composed of engineers, computer scientists and physicists.

Performance Indicators for Factory Planning on the Basis of the Virtual Production Intelligence Approach

Production companies in high-wage countries face growing complexity in their production conditions due to increasing variance and shorter product lifecycles. Solutions that provide an integrated view of the planning processes are needed to achieve increasing production quality and efficiency. One approach for managing this complexity is the use of simulation applications to design digital models. Using the approach of “Virtual Production”, e.g. factory planning scenarios can be evaluated in advance by simulation. A new integrative concept called Virtual Production Intelligence (VPI) has been developed that applies solutions of different intelligence approaches to the field of virtual production by means of integration and analysis of data aggregated along the simulated processes. In this paper, performance indicators are presented for monitoring factory planning processes using the VPI approach. Hence, critical stages can be simulated in advance to support factory planning projects.

IT-Infrastructure for an Integrated Visual Analysis of Distributed Heterogeneous Simulations

Computational simulations are used for the optimization of production processes in order to significantly reduce the need for costly experimental optimization approaches. Yet individual simulations can rarely describe more than a single production step. Hence, a set of simulations has to be used to simulate a contiguous representation of a complete production process. Besides, simulated results have to be analyzed by domain experts to gather insight from the performed computations. In this paper, an IT-infrastructure is proposed that aims at a rather non-intrusive way of interconnecting simulations and domain expert’s knowledge to facilitate the collaborative setup, execution and analysis of distributed simulation chains.