Altair > Case Studies > Developing a Customized IoT Solution to Reduce Pre-processing Activities in Consumer Goods Industry

Developing a Customized IoT Solution to Reduce Pre-processing Activities in Consumer Goods Industry

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Technology Category
  • Analytics & Modeling - Digital Twin / Simulation
  • Cybersecurity & Privacy - Identity & Authentication Management
Applicable Industries
  • Consumer Goods
  • Packaging
Applicable Functions
  • Procurement
  • Product Research & Development
Use Cases
  • Mesh Networks
  • Time Sensitive Networking
Services
  • Testing & Certification
About The Customer
Mabe is a Mexico-based company that designs, produces, and distributes appliances to more than 70 countries around the world. The company is focused on improving the performance and quality of their products, and conducts various analysis studies on its products, including refrigerators, washing machines, and dryers. Mabe operates in a fast-paced and highly competitive consumer goods industry, where the demand for “smarter” products is high and the timeline for production is shrinking. To remain competitive, Mabe must innovate and develop new products quickly.
The Challenge
Mabe, a Mexico-based company that designs, produces, and distributes appliances globally, was facing a significant challenge in its product development process. The company conducts various analysis studies on its products, including refrigerators, washing machines, and dryers, to improve their performance and quality. A critical part of these studies is the Refrigerator Door Foam Modeling (RDFM) process, which involves modeling the foam within the refrigerator that helps maintain the internal temperature and absorb shock during a drop situation. However, due to the complexity and time-consuming nature of this process, it was often overlooked or skipped entirely. This led to two major issues: the computer-aided engineering (CAE) results were not matching the actual results 100%, and the energy usage was not being measured appropriately. Mabe wanted to perform RDFM more routinely but needed a more efficient way forward.
The Solution
To address this challenge, Mabe collaborated with Altair ProductDesign, with whom they had a longstanding relationship. Altair ProductDesign proposed a highly customized solution based on its Impact Simulation Director. This solution would take the finite element (FE) models of the interior and exterior door components and fill the void automatically before taking the faces that contact the foam and extending those elements to fill the void. The process flow developed by the Altair ProductDesign team started with freezing the advanced geometry assembly of the refrigerator and cleaning the surfaces of the mesh. They used the Identification Parallel Gap function to create a solid joint in the gap areas, then started looking at the foam development and how it would interact with the doors and internal cabinets by creating a two-dimensional mesh. Once the areas where the foam would contact the doors were clearly identified, they could perform FE meshing of the product, the RDFM meshing, and the three-dimensional component meshing of the internal plastic and external steel, with the surfaces extended to minimize the void.
Operational Impact
  • The implementation of the customized RDFM solution allowed Mabe to rapidly create the foam volumes, readying the model for drop analysis. They could also perform the majority of the meshing of the foam volume with Hex mesh, take plastic parts into account when generating the foam volume, identify gaps and leakage in order to extract the foam volume and apply semi-automated tools to stitch gaps between door parts. This solution not only reduced the pre-processing time by 50% but also allowed for early detection of errors, helping Mabe’s design engineers to trim components and fill gaps properly and avoid meshing incorrect surfaces. The solution also helped them capture fine details in the models to create more advanced and accurate meshing forms. As a result, Mabe’s engineering team can now spend less time on pre-processing activities and more time on product improvement programs.
Quantitative Benefit
  • 50% reduction in foam pre-processing time
  • Potential to decrease pre-processing time to a few days for future projects
  • Early error detection in the design process

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