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VR-EA: Virtual Reality Visualization of Enterprise Architecture Models with ArchiMate and BPMN
(2019)
The digital transformation occurring throughout enterprises results in an increasingly dynamic and complex IT landscape. As the structures with which enterprise architecture (EA) deals become more digital, larger, complex, and dynamic, new approaches for modeling, documenting, and conveying EA structural and relational aspects are needed. The potential for virtual reality (VR) to address upcoming EA modeling challenges has as yet been insufficient- ly explored. This paper contributes a VR hypermodel solution concept for visu- alizing, navigating, interacting with ArchiMate and Business Process Modeling Notation (BPMN) models in VR. An implementation demonstrates its feasibil- ity and a case study is used to show its potential.
A complex and dynamic IT landscape with evermore digital elements, relations, and content presents a challenge for Enterprise Architecture (EA). Disparate digital repositories, including Knowledge Management Systems (KMS), Enterprise Content Management Systems (ECMS), and Enterprise Architecture Tools (EAT), often remain disjointed. And even if integrated, insights remain hindered by current visualization limitations, making it increasingly difficult to analyze, manage, and gain insights into the digital enterprise reality. This paper contributes our nexus-based Virtual Reality (VR) solution concept VR-EA+TCK that enhances and amalgamates EAT with KMS and ECMS capabilities. By enabling visualization, navigation, and interaction in VR with dynamically-generated EA diagrams, knowledge/value chains, and KMS/ECMS digital entities, it sets the groundwork for stakeholder-accessible grassroots enterprise modeling/analysis and future collaboration in a metaverse. An implementation shows its feasibility, while a case study demonstrates its potential using enterprise analysis scenarios: ECMS/KMS coverage in the EA, business processes, knowledge chains, Wardley Maps, and risk analysis.
Today’s Industry 4.0 Smart Factories involve complicated and highly automated processes. Nevertheless, certain crucial activities such as machine maintenance remain that require human involvement. For such activities, many factors have to be taken into account, like worker safety or worker qualification. This adds to the complexity of selection and assignment of optimal human resources to the processes and overall coordination. Contemporary Business Process Management (BPM) Systems only provide limited facilities regarding activity resource assignment. To overcome these, this contribution pro- poses a BPM-integrated approach that applies fuzzy sets and rule processing for activity assignment. Our findings suggest that our approach has the potential for improved work distribution and cost savings for Industry 4.0 production processes. Furthermore, the scalability of the approach provides efficient performance even with a large number of concurrent activity assignment requests and can be applied to complex production scenarios with minimal effort.