Simplifying and Scaling FEA Post-Processing with Altair Compose at Northrop Grumman Systems Corporation
Technology Category
- Sensors - Barcode Readers
- Sensors - Level Sensors
Applicable Industries
- Aerospace
Applicable Functions
- Product Research & Development
Use Cases
- Time Sensitive Networking
About The Customer
Northrop Grumman Systems Corporation (NGSC) is an American multinational corporation that is a global leader in innovation and technology for aerospace and defense. The company's marine systems division, located in Sunnyvale, CA, is a leader in the design, development, and production of advanced naval systems. NGSC is known for its commitment to technological innovation and its significant contributions to the aerospace and defense sectors.
The Challenge
Northrop Grumman Systems Corporation (NGSC), a global leader in aerospace and defense technology, was facing a significant challenge in their post-processing workflow. The process involved manually calculating combined stresses from NASTRAN results, which was particularly time-consuming due to the presence of hundreds of 1D beam elements with varying cross-sections in some system level models. Each type of 1D beam required its own set of calculations. The challenge was to automate this workflow to save time, minimize errors with simple user inputs, and scale the process to allow a variety of models, such as different cross-sections, to be post-processed.
The Solution
Altair and NGSC engineers collaborated to address this challenge by first discussing the current workflow, identifying pain points, and sharing necessary materials like equations, sample NASTRAN model, and results. Altair Compose was chosen as the solution due to its extensive library of FEA results readers, developed for Altair HyperView and Altair HyperGraph, and the community's familiarity with the Open Matrix Language. A 'template' script was provided to the NGSC team, which read in their model and results files, modified the data as per the provided engineering equations, and output a custom results file that could be visualized in HyperView. With further collaboration, NGSC engineers were able to modify, expand, and apply the script to their production level post-processing.
Operational Impact
Case Study missing?
Start adding your own!
Register with your work email and create a new case study profile for your business.
Related Case Studies.
Case Study
Airbus Soars with Wearable Technology
Building an Airbus aircraft involves complex manufacturing processes consisting of thousands of moving parts. Speed and accuracy are critical to business and competitive advantage. Improvements in both would have high impact on Airbus’ bottom line. Airbus wanted to help operators reduce the complexity of assembling cabin seats and decrease the time required to complete this task.
Case Study
Aircraft Predictive Maintenance and Workflow Optimization
First, aircraft manufacturer have trouble monitoring the health of aircraft systems with health prognostics and deliver predictive maintenance insights. Second, aircraft manufacturer wants a solution that can provide an in-context advisory and align job assignments to match technician experience and expertise.
Case Study
Aerospace & Defense Case Study Airbus
For the development of its new wide-body aircraft, Airbus needed to ensure quality and consistency across all internal and external stakeholders. Airbus had many challenges including a very aggressive development schedule and the need to ramp up production quickly to satisfy their delivery commitments. The lack of communication extended design time and introduced errors that drove up costs.
Case Study
Developing Smart Tools for the Airbus Factory
Manufacturing and assembly of aircraft, which involves tens of thousands of steps that must be followed by the operators, and a single mistake in the process could cost hundreds of thousands of dollars to fix, makes the room for error very small.
Case Study
Accelerate Production for Spirit AeroSystems
The manufacture and assembly of massive fuselage assemblies and other large structures generates a river of data. In fact, the bill of materials for a single fuselage alone can be millions of rows of data. In-house production processes and testing, as well as other manufacturers and customers created data flows that overwhelmed previous processes and information systems. Spirit’s customer base had grown substantially since their 2005 divestiture from Boeing, resulting in a $41 billion backlog of orders to fill. To address this backlog, meet increased customer demands and minimize additional capital investment, the company needed a way to improve throughput in the existing operational footprint. Spirit had a requirement from customers to increase fuselage production by 30%. To accomplish this goal, Spirit needed real-time information on its value chain and workflow. However, the two terabytes of data being pulled from their SAP ECC was unmanageable and overloaded their business warehouse. It had become time-consuming and difficult to pull aggregate data, disaggregate it for the needed information and then reassemble to create a report. During the 6-8 hours it took to build a report, another work shift (they run three per day) would have already taken place, thus the report content was out-of-date before it was ever delivered. As a result, supervisors often had to rely on manual efforts to provide charts, reports and analysis.