How Inconsistencies Between Multiple Conceptual Modeling Scripts Affect Readers’ Understanding

IS professionals often use multiple conceptual modeling scripts to develop an understanding of a domain. However, using multiple scripts introduces potential inconsistencies between scrips which can reduce script readers’ cognitive ability to develop an understanding. While there are computational methods to avoid or detect inconsistencies, there is a lack of studies on how individuals deal with inconsistencies when they are performing different tasks. We developed a 2x2 between-subject experimental design to investigate the effects of syntactic vs semantic inconsistency on two different systems analysis and design tasks. We expect to contribute to conceptual modeling research, by investigating the effect of inconsistencies, comparing the effects of two tasks, and by elaborating on the role of a pragmatic factor, domain familiarity

BPMN+I to support decision making in innovation management for automated production systems including technological, multi team and organizational aspects

A joined interdisciplinary approach from systems engineering, organizational sociology and psychology is introduced using an enriched Business Process Model and Notation (BPMN+I) based modeling approach to support decision making on a management level for both mid-term decisions such as in-/outsourcing and short-term decisions such as fixing a weakness on site during start-up of a plant abroad or involving the design offices. This approach focusses on the actual collaboration between interdisciplinary teams within an organizational context by enriching BPMN with checklists applicable to all interfaces along the projects’ workflow. Our contribution aims at supporting innovation management for automated Production Systems which depends on successful interdisciplinary collaboration

Modeling 4.0: Conceptual Modeling in a Digital Era

Digitization provides entirely new affordances for our economies and societies. This leads to previously unseen design opportunities and complexities as systems and their boundaries are re-defined, creating a demand for appropriate methods to support design that caters to these new demands. Conceptual modeling is an established means for this, but it needs to be advanced to adequately depict the requirements of digitization. However, unlike the actual deployment of digital technologies in various industries, the domain of conceptual modeling itself has not yet undergone a comprehensive renewal in light of digitization. Therefore, inspired by the notion of Industry 4.0, an overarching concept for digital manufacturing, in this commentary paper, we propose Modeling 4.0 as the notion for conceptual modeling mechanisms in a digital environment. In total, 12 mechanisms of conceptual modeling are distinguished, providing ample guidance for academics and professionals interested in ensuring that modeling techniques and methods continue to fit contemporary and emerging requirements

A Novel Graph-Based Modelling Approach for Reducing Complexity in Model-Based Systems Engineering Environment

Field of systems engineering (SE) is developing rapidly and becoming more complex, where multiple issues arise such as overcomplexity, lack of communication or understanding of the design process on different stages of its lifecycle. Model-based systems engineering (MBSE) has been introduced to overcome the communication issues and reduce systems complexity. A novel approach for modelling interactions is proposed to enhance the existing MBSE methodologies and further address the identified challenges. The approach is based on graph theory, where pre-defined rules and relationships are substituted and reorganised dynamically with graphical constructs. A framework for reducing complexity and improving logic modelling in MBSE with metagraph object-oriented approach is presented. This framework is tested in use cases from literature, where the model-based systems approach is applied to design an automobile system to match the acceleration requirements, and to improve a CubeSat nanosatellite communication subsystem. Through the use case scenarios, it has been proven that the methodology framework meets all the identified functional and design requirements and achieves the aim of the research. This work may be viewed as a step forward towards more consistent and automatic modelling of interactions among subsystems and components in MBSE. Automation techniques have multiple applications in systems engineering field as engineers always aim to produce higher quality and cost-effective products in less time and that is achieved by integrating knowledge on every stage of a development lifecycle. In addition to those advantages for SE field, the research provides basis for potential research proposals for future work in various engineering fields such as knowledge based engineering or virtual engineering

Fundamental Approaches to Software Engineering

This open access book constitutes the proceedings of the 23rd International Conference on Fundamental Approaches to Software Engineering, FASE 2020, which took place in Dublin, Ireland, in April 2020, and was held as Part of the European Joint Conferences on Theory and Practice of Software, ETAPS 2020. The 23 full papers, 1 tool paper and 6 testing competition papers presented in this volume were carefully reviewed and selected from 81 submissions. The papers cover topics such as requirements engineering, software architectures, specification, software quality, validation, verification of functional and non-functional properties, model-driven development and model transformation, software processes, security and software evolution

User Experiment Data for: Managing Inter-Model Inconsistencies in Model-based Systems Engineering: Application in Automated Production Systems Engineering

Results of small user experiment within the articleTHIS DATASET IS ARCHIVED AT DANS/EASY, BUT NOT ACCESSIBLE HERE. TO VIEW A LIST OF FILES AND ACCESS THE FILES IN THIS DATASET CLICK ON THE DOI-LINK ABOV

User Experiment Data for: Managing Inter-Model Inconsistencies in Model-based Systems Engineering: Application in Automated Production Systems Engineering

Results of small user experiment within the articl