Marcus Grum

Determining the optimal level of autonomy in cyber-physical production systems

Traditional production systems are enhanced by cyber-physical systems (CPSs) and Internet of Things. As kind of next generation systems, those cyber-physical production systems (CPPSs) are able to raise the level of autonomy of its production components. To find the optimal degree of autonomy in a given context, a research approach is formulated using a simulation concept. Based on requirements and assumptions, a cyber-physical market is modeled and qualitative hypotheses are formulated, which will be verified with the help of the CPPS of a hybrid simulation environment. Big Data Analytics can be used to extract influence factors which explain the optimal degree of autonomy.

Integration of Augmented Reality Technologies in Process Modeling - The Augmentation of Real World Scenarios With the KMDL

The integration of powerful technologies in traditional domains realizes promising potentials but mostly rises complexity and shrinks comprehensibility of underlying processes. With the aim to rise comprehensibility of non-transparent processes, a process modeling language has been transfered in 3-D and prepared to augment the real world. Definitions for a methodological proceeding have been created and were mapped to a software tool. Three scenarios then have been realized as demonstration and proof the working of drawn AR integrations. Focusing non-transparent processes, scenarios visualize tacit knowledge transfers (1), complex coordination mechanisms (2) and process simulations (3) in the domain of cyber-physical production systems.

A decision maxim for efficient task realization within analytical network infrastructures

Abstract Faced with the increasing needs of companies, optimal dimensioning of IT hardware is becoming challenging for decision makers. In terms of analytical infrastructures, a highly evolutionary environment causes volatile, time-dependent workloads in its components, and intelligent, flexible task distribution between local systems and cloud services is attractive. With the aim of developing a flexible and efficient design for analytical infrastructures, this paper proposes a flexible architecture model, which allocates tasks following a machine-specific decision heuristic. A simulation benchmarks this system with existing strategies and identifies the new decision maxim as superior in a first scenario-based simulation.

Process Modeling Within Augmented Reality

The collaboration during the modeling process is uncomfortable and characterized by various limitations. Faced with the successful transfer of first process modeling languages to the augmented world, non-transparent processes can be visualized in a more comprehensive way. With the aim to rise comfortability, speed, accuracy and manifoldness of real world process augmentations, a framework for the bidirectional interplay of the common process modeling world and the augmented world has been designed as morphologic box. Its demonstration proves the working of drawn AR integrations. Identified dimensions were derived from (1) a designed knowledge construction axiom, (2) a designed meta-model, (3) designed use cases and (4) designed directional interplay modes. Through a workshop-based survey, the so far best AR modeling configuration is identified, which can serve for benchmarks and implementations.

A Visionary Way to Novel Process Optimizations

Modern process optimization approaches do build on various qualitative and quantitative tools, but are mainly limited to simple relations in different process perspectives like cost, time or stock. In this paper, a new approach is presented which focuses on techniques of the area of Artificial Intelligence to capture complex relations within processes. Hence, a fundamental value increase is intended to be gained. Existing modeling techniques and languages serve as basic concepts and try to realize the junction of apparently contradictory approaches. This paper therefore draws a vision of promising future process optimization techniques and presents an innovative contribution.