Business capability-centric management of services and processes models
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With the advent of Industry 4.0, more and more companies are actively working on digitising their assets (i.e., services, processes, etc.) for better control, collaboration, modularity, analysis, etc. By 2020 more than 80% of companies will have digitised their business processes and value chains. This creates more services and processes, making their indexing, discovery, configuration, etc. more challenging. Thus, digitising assets needs a data model to describe them together with algorithms for indexing, discovery and configuration. This thesis details a concept model for describing the business capability of services and business processes from a functional perspective in terms of what do they achieve together with related business properties. Furthermore, this work proposes the aggregation, indexing, discovery and configuration of services and business processes using the concept of business capability. The first contribution of this thesis is a conceptual model for describing Business Capabilities. The model is implemented as a set of ontologies that can be used for creating semantic annotations of business process models or services. This model is verified using ontological evaluation by mapping its constructs with ontology constructs and verifying there is not an overload or semantic ambiguity. This method has been used for the assessment of relationships in the entity-relationship model. A feature comparison to existing models is performed with respect to three requirements: expressiveness, support for inferencing, use of ontologies and ability to model configuration options. Finally, interviews with domain experts were carried out revealing that the model is simple, easy to adopt and flexible enough to be extended for user requirements. The second contribution is an abstraction technique that allows moving from an entire process model to its functional description by aggregating the business capabilities of the process elements into a single one. The idea of the algorithm is to traverse the model from an initial node to a final node. Each intermediate node introduces changes to the propagated business capability. The propagation steps are validated using formal semantics of process elements in Petri Nets. The third contribution of this thesis is to explore the use of Formal Concept Analysis for providing efficient indexing and discovery of business capabilities described using the proposed model. This contribution is validated in a real world scenario for indexing sensor capabilities. A quantitative evaluation is conducted with synthetic sensor capabilities for indexing and discovering 5000 entities. The results show that the indexing and discovery time are less than 200 ms. The fourth contribution of this thesis is to reduce the business process modelling effort when using configurable process models via an algorithm for creating business capability-annotated configurable business process models that captures configuration options in terms of business capability features. The merging operation realises a compression rate of 50% (by computing the number of nodes before and after the merging).
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