Master Thesis: Overcoming Challenges in Integrating Process Engines in Engineering Processes
In today's rapidly evolving engineering landscape, process management and automation are critical components for ensuring product quality and efficiency by collecting contextualized data for innovations e.g., Product Lifecycle Data from various software applications. However, challenges often arise during the implementation of process engines, such as missing satisfaction of users or increased complexity compared to manual application, eventually leading to obstacles hindering the successful application. This master's thesis aims to identify these barriers at a global leader in developing lighting solutions, develop strategies to address these issues, and ultimately lead to greater success in process automation.
Definition of a representative Use Case in Engineering: To enable project evaluation, an existing process in the global leading company must be documented and understood. Means of process notation such as BPMN might be relevant.
Obstacle Identification: Use various research methods such as questionnaires and focus group studies or Systematic Literature Review (SLR) to comprehensively identify barriers to the application of currently implemented or planned processes using process engines within Product Lifecycle Management (PLM), considering issues such as change management. The result of this step shall report metrics, success criteria and hindering obstacles for the implementation of workflow engines.
Metric Development: Derive meaningful metrics and other non-quantitative criteria for evaluating the successful implementation and integration of process engines using insights from survey results, best practices from the literature, and insights from the industry.
Proof of Concept Implementation: Translation of theoretical insights into practical solutions by designing and implementing a proof of concept using the Cloud Process Execution Engine (CPEE), targeting the documented PLM process in the first step. This hands-on phase of the thesis will allow for the evaluation of the previously defined metrics/criteria and enable the planning of further tasks to improve the integration of process engines.