Wilhelm Dangelmaier

Virtual and augmented reality support for discrete manufacturing system simulation

Nowadays companies operate in a difficult environment: the dynamics of innovations increase and product life cycles become shorter. Furthermore products and the corresponding manufacturing processes get more and more complex. Therefore, companies need new methods for the planning of manufacturing systems. One promising approach in this context is digital factory/virtual production-the modeling and analysis of computer models of the planned factory with the objective to reduce time and costs. For the modeling and analysis various simulation methods and programs have been developed. They are a highly valuable support for planning and visualizing the manufacturing system. But there is one major disadvantage: only experienced and long trained experts are able to operate with these programs. The graphical user interface is very complex and not intuitive to use. This results in an extensive and error-prone modeling of complex simulation models and a time-consuming interpretation of the simulation results. To overcome these weak points, intuitive and understandable man-machine interfaces like augmented and virtual reality can be used. This paper describes the architecture of a system which uses the technologies of augmented and virtual reality to support the planning process of complex manufacturing systems. The proposed system assists the user in modeling, the validation of the simulation model, and the subsequent optimization of the production system. A general application of the VR- and AR-technologies and of the simulation is realized by the development of appropriate linking and integration mechanisms. For the visualization of the arising 3D-data within the VR- and AR-environments, a dedicated 3D-rendering library is used.

A humanitarian supply chain process reference model

Humanitarian operations comprise a wide variety of activities. These activities differ in temporal and spatial scope, as well as objectives, target population and with respect to the delivered goods and services. Despite a notable variety of agendas of the humanitarian actors, the requirements on the supply chain and supporting logistics activities remain similar to a large extent. This motivates the development of a suitably generic reference model for supply chain processes in the context of humanitarian operations. Reference models have been used in commercial environments for a range of purposes, such as analysis of structural, functional, and behavioural properties of supply chains. Our process reference model aims to support humanitarian organisations when designing appropriately adapted supply chain processes to support their operations, visualising their processes, measuring their performance and thus, improving communication and coordination of organisations. A top-down approach is followed in which modular process elements are developed sequentially and relevant performance measures are identified. This contribution is conceptual in nature and intends to lay the foundation for future research.

Reconfiguration of assembly lines under the influence of high product variety in the automotive industry–a decision support system

In this paper we consider the mixed model assembly line reconfiguration problem in the context of auto production which is characterised by a make-to-order production process and a huge product variety. Starting from a given line balancing solution the goal is to minimise production costs in the short term for a largely known production program by reassigning and shifting tasks between workstations. We present a mathematical optimisation model that aims at minimising the costs incurred by overload situations, regular workers and reconfiguration measures. Due to the models complexity, lack of data and acceptance issues it is hardly possible to fully automate the solution process in an industrial environment. Therefore, we present a decision support approach that consists of visualisation components, new numerical indicators and an integrated heuristic optimisation procedure to semi-automate the reconfiguration process. In particular, reconfiguration costs can be taken into account and no complete precedence graph is required. Finally, we show on the basis of two industrial case studies that our approach can be successfully applied in a practical environment where it was capable of drastically reducing the occurrence of overload situations.

Integriertes Supply Chain Management — ein koordinationsorientierter Überblick

Die Rahmenbedingungen in der Logistik haben sich in den letzten Jahren stark verandert. Steigende Komplexitat durch Teile-, Varianten-, Kunden-, Lieferanten- und Distributionskanalvielfalt beeinflussen das Wettbewerbsumfeld. Verkurzte Produktlebenszyklen und technologischer Fortschritt verscharfen den zunehmend globalen Wettbewerb. Mit Hilfe der effektiven Vernetzung logistischer Prozesse zeigen Innovationsfiihrer auf, wie man den geanderten Bedingungen in unterschiedlichen Branchen begegnen kann. Durch unternehmensubergreifende Geschaftsprozessintegration erschliesen sie bisher ungenutzte Erfolgspotenziale und starken ihre Wettbewerbsposition.

Optimal Stock Relocation under Uncertainty in Post-Disaster Humanitarian Operations

The number of world-wide emergencies and disasters which trigger humanitarian operations is ever-increasing. Although general research contributions to supply chain management in the context of humanitarian operations have risen significantly, operations research techniques have not yet comprehensively been applied in this context. A literature review categorizes existing approaches in the pre- and post-disaster phases. Filling an identified gap in current literature, a model for optimal stock relocation under uncertainty in risk-prone post-disaster scenarios is formulated. The model is solved with an optimal and a heuristic approach. It is found that overall costs can be significantly reduced compared to a benchmark model when the uncertainty of demand in post-disaster scenarios is taken into account.

Supply chain management: a multi-agent system for collaborative production planning

The need for coordinated material flow in supply chains is essential for the competitiveness of manufacturing firms. A hierarchical coordination is not applicable for each supply chain. A collaboration between entities is required to meet future challenges. Besides appropriate planning concepts an IT solution is a major challenge. Multi-agent systems (MAS) are an enabler for a decentralized coordination process. The evolvement of appropriate planning methods makes MAS interesting for collaborative supply chain management (SCM). Nevertheless, the user should be seen as the supply chain engineer, holding the knowledge to create the collaborative supply chain processes. Therefore, the user has to be integrated in the IT solution. A configurable MAS, based on generic components, satisfies this requirement so that MAS can easily be adapted to the changing processes and environment by the user. This paper presents a concept of a configurable MAS and a prototype of a MAS-Editor for collaborative production planning.

Knowledge-based event control for flow-shops using simulation and rules

The requirements on production systems and their planning and control systems are constantly growing. Systems have to be flexible and provide viable solutions at the same time. Different planning and control approaches, such as optimization, simulation and combination of techniques etc., that attempt to solve the scheduling problems are available. Mathematical solutions which can be found in literature didn¿t solve the real-world problems in an appropriate way. Current knowledge based solutions did not give any value about decision reliability as well as their decision attributes are not differentiate enough. We are developing a new rule based approach by using a combination of simulation and a knowledge generation within a dynamic production planning and -control for flow-shops. Ideas of how knowledge can be trained by simulation are presented. Furthermore which kind of rules and attributes can be used and how decisions about the rule selection can be made are shown.

Using dynamic multiresolution modelling to analyze large material flow systems

The interactive, simulation-aided analysis of material flow systems is often done with the help of virtual reality. If a user wants to influence the simulation run, the simulation and the visualization have to be computed simultaneously. Large, detailed simulation models, which can not be calculated fast enough, can not be analyzed interactively. This paper presents a method which only computes those parts of simulation models that are visited by the user. If a user shifts its attention, the area being simulated in detail is updated. Since the major part of the simulation is not detailed, the necessary calculating complexity is reduced. On the basis of models allowing a multiresolution simulation methods are introduced which regulate the level of detail based on the evaluation of the users attention. Changing the levels of details leads to the exchange of models with different level of details.

Towards a science of logistics: cornerstones of a framework of understanding of logistics as an academic discipline

The mission of BVL, the nonprofit German Logistics Association, is to act as an integrative platform to promote the awareness for the importance of logistics in industry, science, and the public arena. It aims to represent the entire spectrum of logistical issues, to develop methods and processes to contribute to the solution of these issues, and to promote and continuously optimise the application of relevant solutions. BVL’s Scientific Advisory Board is supporting BVL’s mission by promoting the dialogue between logistics practice and the academic community. Its members come from many different academic backgrounds. While there is no longer any disagreement about the enormous practical relevance of logistics and its steadily growing impact upon day-to-day economic activities, the members of BVL’s Scientific Advisory Board are aware that there still is no widely shared understanding of the identity of logistics as a scientific and academic discipline. Against this backdrop, and following a strategic discussion which the Scientific Advisory Board initiated some time ago, the idea of developing a framework of understanding for logistics as an academic discipline emerged. For this purpose, a working group was set up comprising the authors of this paper. It reflects the broad spectrum of disciplinary backgrounds and perspectives on the essence of science represented on the Advisory Board. Five key points, as outlined below, were agreed upon as the cornerstones of an understanding of logistics as an academic discipline. They were arrived at as the result of an extremely exciting sequence of discussions which took place in the group’s workshop sessions. The cornerstones are designed to serve as a point of reference for continuing indepth, discussions about the ‘‘science of logistics’’ within BVL, and—hopefully—with academics and logistics practitioners all over the world. A further aim is to contribute to a better understanding of the depth and relevance of the science of logistics among those ‘‘outside’’ the discipline. The paper starts out with a statement summarising the nature of logistics as a science. This statement is followed by five cornerstone points elaborating the essential characteristics of the discipline. The authors are members of a working group of the Scientific Advisory Board of German Logistics Association (BVL).

Adaptive flow control in flexible flow shop production systems: a knowledge-based approach

Today simulation is essential when researching manufacturing processes or designing production systems. But in the field of manufacturing, simulation can not only be used for purposes of research or design, it can also be utilized by flow control systems in order to make better and faster decisions. In this paper we focus on real-time scheduling in a special kind of flexible flow shop systems. These consist of production stages, which represent groups of machines doing the same work, but working at different speeds. Flow control in these flexible flow shop environments with uniform machines is exceedingly complex and it is even more complex when uncertainties are taken into consideration. For this reason we develop an adaptive scheduling heuristic, utilizing both simulation and artificial intelligence in order to make globally good decisions without causing noticeable manufacturing delays.