Master Thesis: Integrated Engineering Data Transformation using AutomationML

🔧 Tools & Technologies:

AutomationML (AML), PPR Methodology (Product-Process-Resource), Python, Enterprise Architect, Systems Engineering

📄 Overview

This project focused on developing a tool-supported modeling approach for efficient engineering data transformation and integration across multiple engineering domains within the production system design process. The work was carried out within the framework of the DIAMOND project, aiming to overcome data exchange inefficiencies using the AutomationML (AML) standard and the Product-Process-Resource (PPR) methodology.

🎯 Objectives

• Analyze current engineering data exchange workflows and identify inefficiencies

• Develop a concept-based modeling approach to enable seamless engineering data transformation

• Utilize AutomationML (AML) for structured, standardized, and cross-domain data exchange

• Support modular production system design and digitalization of engineering data logistics

🧠 What I Did

• Conducted a state-of-the-art analysis on PPR methodology, engineering data logistics, and AML standards

• Analyzed abstract use cases modeling production systems using PPR structure in AML

• Designed a tool-supported methodology for engineering data integration based on stakeholder requirements and literature

• Developed a prototype application enabling transformation and integration of engineering data across different domains

• Validated the approach with test cases and received feedback from domain experts

• Evaluated and benchmarked the proposed solution against existing methods, highlighting its potential for adoption in manufacturing data logistics