Automated Modeling with Abstraction for Enterprise Architecture (AMA4EA):Business Process Model Automation in an Industry 4.0 Laboratory

The transformation towards the Industry 4.0 paradigm requires companies to manage large amounts of data. This poses serious challenges with regard to how effectively to handle data and extract value from it. The state-of-the-art research of Enterprise Architecture (EA) provides limited knowledge on addressing this challenge. In this article, the Automated Modeling with Abstraction for Enterprise Architecture (AMA4EA) method is proposed and demonstrated. An abstraction hierarchy is introduced by AMA4EA to support companies to automatically abstract data from enterprise systems to concepts, then to automatically create an EA model. AMA4EA was demonstrated at an Industry 4.0 laboratory. The demonstration showed that AMA4EA could abstract detailed data from the Enterprise Resource Planning (ERP) system and Manufacturing Execution System (MES) to be relevant for a business process model that provided a useful and simplified visualization of production process data. The model communicated the detailed business data in an easily understandable way to stakeholders. AMA4EA is an innovative and novel method that contributes new knowledge to EA research. The demonstration provides sufficient evidence that AMA4EA is useful and applicable in the Industry 4.0 environment

Business Capability Mining - Opportunities and Challenges

Business capability models are widely used in enterprise architecture management to generate an abstract overview of an organization’s business activities to reach its business objectives. The creation and maintenance of these models are associated with a huge manual workload. Research provides insights into opportunities for automated modeling of enterprise architecture models. However, most models address the application and technology layer and leave the business layer largely unexplored. Particularly, no research has been conducted on the automated generation of business capability models. This research paper uses 19 semi-structured expert interviews to identify possible automated modeling opportunities of business capabilities and related challenges and to jointly develop a business capability mining approach. This research benefit both, practice and research, by describing a situation-based business capability mining approach and identifying appropriate implementation scenarios