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Optimizing CAE with IoT: A Case Study of BASF Engineering Plastics
Technology Category
- Infrastructure as a Service (IaaS) - Virtual Private Cloud
- Sensors - Chemical Sensors
Applicable Industries
- Chemicals
- Plastics
Applicable Functions
- Product Research & Development
- Quality Assurance
Use Cases
- Transportation Simulation
- Virtual Reality
The Challenge
BASF Engineering Plastics, a division of the world's leading chemical company, BASF, is tasked with providing superior engineering design, simulation, and testing support during all phases of the development cycle. The group's primary goal is to provide superior engineering design, simulation, and testing support during all phases of the development cycle. However, the support of various customers in the application of modern materials often demands new concepts that make the advantages of the material applicable. This challenge is further compounded by the need to continually develop modern virtual methods to meet the needs of its customers, as the company believes that mathematical part optimization will broadly gain acceptance as the method of choice in the next few years.
About The Customer
BASF is the world’s leading chemical company, with a portfolio that ranges from oil and gas to chemicals, plastics, performance products, agricultural products, and fine chemicals. BASF helps its customers in virtually all industries to be more successful through its high-value products and intelligent solutions. The company plays an important role in finding answers to global challenges such as climate protection, energy efficiency, nutrition, and mobility. BASF has more than 95,000 employees and posted sales of almost €58 billion in 2007. The Engineering Plastics division's design capabilities reside in its Application Development Engineering Group, which employs leading-edge technologies and methods in their activities.
The Solution
To address this challenge, BASF Engineering Plastics has been increasingly focusing on Mathematical Part Optimisation within the framework of BASF’s CAE activities. This method not only allows for the design of optimum parts on the computer but also fills a gap in virtual part development. Altair OptiStruct is the initial tool in this process. Mathematical optimization methods provide significant support in virtual CAE part development. In the early phases of the project, topology optimization provides valuable clues to the design of the geometry of the part. Subsequent questions about the precise dimensions can be effectively answered by parameter optimization runs. The use of morphing methods for this purpose has to be given particular emphasis.
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