Abstract
This article presents a Model-Based Systems Engineering (MBSE) methodology for the development of a Digital Twin (DT) for an Unmanned Aerial System (UAS) with the ability to demonstrate route selection capability with a Mission Engineering (ME) focus. It reviews the concept of ME and integrates ME with a MBSE framework for the development of the DT. The methodology is demonstrated through a case study where the UAS is deployed for a Last Mile Delivery (LMD) mission in a military context where adversaries are present, and a route optimization module recommends an optimal route to the user based on a variety of inputs including potential damage or destruction of the UAS by adversary action. The optimization module is based on Multiple Attribute Utility Theory (MAUT) which analyzes predefined criteria which the user assessed would enable the successful conduct of the UAS mission. The article demonstrates that the methodology can execute a ME analysis for route selection to support a user’s decision-making process. The discussion section highlights the key MBSE artifacts and also highlights the benefits of the methodology which standardizes the decision-making process thereby reducing the negative impact of human factors which may deviate from the predefined criteria.
Highlights
The 4th Industrial Revolution (I4.0), referred to as “Industry 4.0”, has changed the way many industries work across the world in recent years
We suggest that the Digital Twin (DT) environment, armed with the requisite data inputs, is able to support the mission planner and provide valuable insights into the benefits and trade-offs for each route that are being assessed
A DT is a virtual representation of a physical asset, based on onboard data generated within the asset and delivered to the DT, which assists stakeholders with maintenance, planning, and operational decisions among other activities
Summary
The 4th Industrial Revolution (I4.0), referred to as “Industry 4.0”, has changed the way many industries work across the world in recent years. One could understand I4.0 as the blurring of boundaries between the digital, biological, and physical worlds. This is made possible with rapidly increasing computing power and data transfer rates. Military operations enabled by I4.0 technologies may transpire so fast that it requires humans to be out of the decision-cycle [6]. In this regard, we expect I4.0 to drive rapid development and adoption of Digital Twin (DT) and Mission Engineering (ME) in a Model-Based Systems Engineering (MBSE) paradigm. Due to the lack of a standard definition, the ODTF generalized the definition of a digital twin to “a model that helps stakeholders answer specific questions by providing a readily available
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