Abstract

We introduce a web-based platform (CAE-web) for CAE attribute leaders, CAE engineers, and design engineers in automotive R&D. The aim is to aid problem-solving and reduce the time in the development phase. The concept is a web-oriented user interface that enables project members from different teams to access the CAE results, understand the design performance limitations, or compare simulations. In the traditional workflow, design engineers and attribute leaders rely on CAE engineer reporting. This static reporting restricts the independent exploration of the data. The limitation arises from the company's dependency on available software and the required skills to use CAE tools. In the current workflow, multi-disciplinary collaboration is more ensured only if the attribute leader has CAE expertise or the design engineer has a background with that discipline requirement. Such a lack of multi-disciplinary collaboration degrades efficient problem-solving. Moreover, CAE model size limits the number of simulations that a CAE engineer can simultaneously load in post-processing software. CAE-web suggests the idea of multi-disciplinary collaboration by utilizing the advantages of web standards that make it "use it without how to". Consequently, we propose a platform that auto-generates and organizes results in a middle level and presents it as a web page on the company server. CAE-web envisions document segmentation, where it is connecting simulation results to attribute requirements and design limitations. The interconnection of documents will increase the learning rate between different disciplines. Another remarkable advantage is the availability of an additional tool for simulation comparison besides the post-processing tool. As an example, we will present a summary of an industrial implementation for pedestrian analysis. The number of simulations increases enormously for each design in pedestrian analysis. We will illustrate how CAE-web visualizes this big data. The visualization provides two groups of visualization: zoom-out and zoom-in views. Zoom-out views consider the assessment of many simulations, for example, development trees, status tables of safety performance, or embedded results from machine learning. However, zoom-in views contain single/multiple simulation assessments and comparisons. Additionally, the user has a multi-view functionality to combine zoom-in and zoom-out views. In multi-view, zoom-out views are selection inputs for updating zoom-in views.