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Training / Education

Model-Based Systems Engineering (MBSE)

2020-10-16
As the complexity of products increases, traditional text-based systems engineering can no longer meet the needs. To solve the problem, Model-based Systems Engineering offers a unified communication platform among relevant staff by carrying out diagram-based unambiguous description, analysis and design for the demand, structure and behavior of complex systems in the form of a model. It, however, still remains a challenge to implement MBSE modeling and model-driven technology and application as well as its integration with the industry.
Magazine

Tech Briefs: April 2018

2018-04-01
Laser Detecting Systems Enhancing Survivability and Lethality on the Battlefield Designing With Plastics for Military Equipment Engine Air-Brakes Paving the Way to Quieter Aircraft Nett Warrior Enhancing Battlefield Connectivity and Communications XPONENTIAL 2018 - An AUVSI Experience Communications in Space: A Deep Subject First Air-Worthy Metal-Printed RF Filter Ready for Takeoff Validation of Automated Prediction of Blood Product Needs Algorithm Processing Continuous Non-Invasive Vital Signs Streams (ONPOINT4) Using a combination of non-invasive sensors, advanced algorithms, and instruments built for combat medics could reduce hemorrhaging and improve survival rates. Calculation of Weapon Platform Attitude and Cant Using Available Sensor Feedback Successful development of mobile weapon systems must incorporate operation on sloped terrain.
Training / Education

Introduction to Statistical Tolerance Stacks 1-day

This course is an introduction to statistical tolerance stacks, a crucial skill in today's competitive workplace. Utilizing the expertise of world-renowned GD&T expert Alex Krulikowski, the course includes a brief overview of several terms used in statistical stacks. It explains four methods for applying statistics to tolerance stacks and covers precautions about when and how to use statistics in stacks. Newly acquired learning is reinforced throughout the class with stacks that allow the student to practice applying statistical methods.
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