Sheet metal stamping is fundamental to the automotive manufacturing industry. A vast array of different tool, die, and process combinations are employed to create an equally diverse array of components. Traditionally, identifying the optimum approach for each part has been a labor intensive and time-consuming task that requires engineering teams with high levels of skill and experience. This case study demonstrates how Altair Knowledge Studio, a general-purpose data analytics tool, can enable engineering managers and data analysts to deliver clear and quantifiable benefits in the manufacturing domain. For Ford, this is reflected in dramatic improvements in the speed and efficiency with which the best possible sheet metal stamping processes were selected.

Increase shop floor efficiency by identifying hidden indicators for future down times in your manufacturing assets. Explore how Altair enables enterprises to leverage operational data throughout the complete data lifecycle - from shop floor to top floor - for increased value and reduced risk.

By extracting real value from their data, manufacturers can make accurate predictions about component life, replacement requirements, energy efficiency, utilization, and other factors that have direct impacts on production capacity, throughput, quality, sales, customer acceptance, and overall efficiency.

The presentation will go through a scenario of a smart factory (along the lines of the Industry 4.0 initiative) where a chemical process within a pharmaceutical company produces a substance critical to the production of medications.