TY  - GEN
A1  - Grum, Marcus
A1  - Gronau, Norbert
T1  - Process modeling within augmented reality
BT  - the bidirectional interplay of two worlds
T2  - Business Modeling and Software Design, BMSD 2018
N2  - 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.
KW  - Augmented reality
KW  - Process modeling
KW  - Simulation process building
KW  - Generalized knowledge constructin axiom
KW  - Meta-model
KW  - Use cases Morphologic box
KW  - Industry 4.0
KW  - CPS
KW  - CPPS
KW  - Internet of things
Y1  - 2018
SN  - 978-3-319-94214-8
SN  - 978-3-319-94213-1
U6  - https://doi.org/10.1007/978-3-319-94214-8_7
SN  - 1865-1348
VL  - 319
SP  - 99
EP  - 115
PB  - Springer
CY  - Berlin
ER  - 
TY  - GEN
A1  - Hesse, Günter
A1  - Matthies, Christoph
A1  - Sinzig, Werner
A1  - Uflacker, Matthias
T1  - Adding Value by Combining Business and Sensor Data
BT  - an Industry 4.0 Use Case
T2  - Database Systems for Advanced Applications
N2  - Industry 4.0 and the Internet of Things are recent developments that have lead to the creation of new kinds of manufacturing data. Linking this new kind of sensor data to traditional business information is crucial for enterprises to take advantage of the data’s full potential. In this paper, we present a demo which allows experiencing this data integration, both vertically between technical and business contexts and horizontally along the value chain. The tool simulates a manufacturing company, continuously producing both business and sensor data, and supports issuing ad-hoc queries that answer specific questions related to the business. In order to adapt to different environments, users can configure sensor characteristics to their needs.
KW  - Industry 4.0
KW  - Internet of Things
KW  - Data integration
Y1  - 2019
SN  - 978-3-030-18590-9
SN  - 978-3-030-18589-3
U6  - https://doi.org/10.1007/978-3-030-18590-9_80
SN  - 0302-9743
SN  - 1611-3349
VL  - 11448
SP  - 528
EP  - 532
PB  - Springer
CY  - Cham
ER  - 
TY  - GEN
A1  - Bender, Benedict
A1  - Grum, Marcus
A1  - Gronau, Norbert
A1  - Alfa, Attahiru
A1  - Maharaj, B. T.
T1  - Design of a worldwide simulation system for distributed cyber-physical production networks
T2  - 2019 IEEE International Conference on Engineering, Technology and Innovation (ICE/ITMC)
N2  - Modern production infrastructures of globally operating companies usually consist of multiple distributed production sites. While the organization of individual sites consisting of Industry 4.0 components itself is demanding, new questions regarding the organization and allocation of resources emerge considering the total production network. In an attempt to face the challenge of efficient distribution and processing both within and across sites, we aim to provide a hybrid simulation approach as a first step towards optimization. Using hybrid simulation allows us to include real and simulated concepts and thereby benchmark different approaches with reasonable effort. A simulation concept is conceptualized and demonstrated qualitatively using a global multi-site example.
KW  - production networks
KW  - geographical distribution
KW  - task realization strategies
KW  - Industry 4.0
KW  - simulation
KW  - evaluation
Y1  - 2019
SN  - 978-1-7281-3401-7
SN  - 978-1-7281-3402-4
U6  - https://doi.org/10.1109/ICE.2019.8792609
SN  - 2334-315X
PB  - IEEE
CY  - New York
ER  -