Data analysis can help metal casting professionals get accurate, dependable information about overall productivity, process times, error detection and more. A case study with a BMW Group factory in Germany shows what’s possible.
The facility produced 4.3 million cast metal parts in a single year, including engine and vehicle body components. Using data analytics means the company stores thousands of details about processes, ranging from the storage times for sand cores to temperature and pressure specifics. The company also relies on 3D measurement data from castings to detect defects, such as blowholes and porosity.
Nelly Apfel, the plant’s data science officer, explained how the thousands of parameters within a single casting process allow for seeing connections. “Data transparency helps us to recognize causal relationships. This is important for component quality. And it enables our casting technologists to put together an optimum parameter set for the individual casting systems,” she said.
The company’s system also continually checks the real-life parameters against the ideal ones set in the system. When there is too much deviation between them, an alarm sounds and the casting process will automatically stop when necessary.
Reclamation and Recycling Efforts
Some metal casting trends relate to making processes less wasteful and better for the environment since many people are concerned about sustainability. Green sand casting is considered one of the most reliable casting methods. It involves creating a single-use mold from a sand aggregate and pouring molten brass into it.
Even though people only use the mold once, some metal casting companies have recycling programs to use the spent sand for other purposes. The green sand casting process relies on the consumption of bentonite and carbon, and much of it ends up in landfills. However, some metal casting facilities have dust collection methods to reclaim some of it.