The program offers many opportunities for students interested in exploring hypotheses in Systems Engineering, which itself is a vast field with countless applications across industries. To further illuminate all that the ISEEM program has to offer by way of hands-on laboratory research, please visit our laboratory pages:

 

Complex Systems Integration Laboratory - CSIL

 

The UAH Complex Systems Integration Laboratory (CSIL) is located in Olin B. King Technology Hall N-106. The CSIL is a state-of-the-art facility for advanced systems engineering, focused on Model-Based Systems Engineering (MBSE) and Digital Engineering.

3 Students presenting in the CSIL lab with the screens in the background

 The CSIL hosts system models on platforms including Dassault Systèmes Cameo (MagicDraw) using the Systems Modeling Language (SysML). Parametric models are developed with tools such as MATLAB/Simulink/Simscape, ModelCenter, the Copernicus trajectory design and optimization system, Ansys Systems Tool Kit (STK), and lab's in-house Spacecraft Integrated System Model (SISM). Together, these tools enable high-fidelity mission modeling by integrating domain-specific engineering analyses with time-dynamic, three-dimensional simulations. The CSIL also maintains ontology development capability for semantic modeling and knowledge integration, using Protégé for OWL ontologies, Rosetta for OML ontologies, and OwlReady2 for programmatic interaction with OWL ontologies.

 

Current research in the CSIL includes:

  • Digital systems engineering methods and tools for NASA Marshall Space Flight Center's Advanced Concepts Office to improve early-phase design of advanced space systems and exploration campaigns;
  • Executable integrated systems models and digital twins for NASA's Space Nuclear Propulsion Program;
  • Applying a federated, open-architecture MBSE framework to regulatory gap analysis for Advanced Air Mobility (AAM) platforms, including an FMECA-based reliability assessment methodology that moves safety considerations earlier in the design lifecycle;
  • Mathematics as the foundation for AI-enabled systems engineering and project management.

 

Decision-making for Operations and Job Outcomes (DOJO) Lab

 

Dr. Nicholas Loyd and his students research the principles of strategic planning, Lean systems, and leadership development, specifically in their applications for manufacturing and engineering management. In the Decision-making for Operations and Job Outcomes (DOJO) Lab, research focuses on workstation design for human factors, process improvement for Lean value streams, and team dynamics in problem-solving scenarios. 

 

Digital X Lab – Tech Hall OKT N102

 

The Digital X Lab is dedicated to the advancement of smart manufacturing research and digital engineering and is directed by Dr. Ana Wooley and Dr. Cheng Chen, both assistant professors in the ISEEM department at UAH. This lab is equipped to support the development, integration, and validation of Digital Twin solutions across the manufacturing lifecycle, providing a robust physical and digital testbed to execute research on advanced manufacturing.  This lab supports full-stack DT development, from sensor integration and protocol implementation to simulation modeling and decision-support tool creation, including:digital x lab

  •  A manual assembly line for drone manufacturing that includes two workstations connected by a conveyor system. It currently can manufacture complete drone kits and is being enhanced with load cell sensors (for inventory control) and proximity sensors (for process timestamping), supporting data collection for digital twin implementation, sensor connectivity, and data integration. 
  • An automated assembly line that is built around the Lucas Nuelle CBP 44 Variant Production with Ejection system and integrates Siemens Simatic S7-1500 PLCs, robot arms, and autonomous workstations. This system supports cyber-physical manufacturing research through real-time communication and modular reconfigurability. Workpieces are created based on cloud-based order input and follow a conveyor system through programmable stations for processing and quality checks.
  • Capability to implement three core layers of DT architecture: Data Layer (Real-time sensor data of manufacturing process), Service layer (Open-source technologies such as MQTT (with secure TLS/SSL implementation), Node-RED, and InfluxDB support IIoT data transmission, storage, and visualization. Raspberry Pis, ESP32s, and LAN/Wi-Fi networks are used for secure, local deployment), and Model Layer (Simulation tools like Simio are used for discrete event modeling). This layer includes mechanisms for bidirectional communication between physical and digital systems and incorporates 2D/3D visual representations, data governance protocols, and system visualization dashboards (e.g., Grafana, Node red, ThingWorx). Unity 3D is also installed in the computers in the lab.