BMW’s production software and hardware system, referred to as the Edge Ecosystem, which allows for predictive maintenance among other things, has been recognized with Microsoft’s Intelligent Manufacturing Award in the Envision category for 2021. The advantages boasted by the Edge Ecosystem are numerous, and a few highlights include the use of a cloud-based software suite for global device management, a central app catalog rolled out in the BMW production network, and zero-touch device deployment which requires no input from a user for automated setup.
One example of how BMW makes practical use of the Edge Ecosystem is that of quality assurance, in which the system employs specialized deep learning models along with physical cameras to perform inspections. Another is that of the press shop, where rolls of sheet metal are transformed into familiar surfaces like doors, trunk lids, roofs, hoods, and fenders. The process of pressing sheet metal into a desired form requires oil as a lubricant, but the amount of oil necessary varies depending on factors such as how long the sheet metal has been in storage. To optimize output, BMW uses the Edge Ecosystem, which relies on unique deep learning models to determine the correct lubrication application and parameters for each piece of sheet metal, and to control the system in real time. This model has been subsequently rolled out to BMW press shops around the world to ensure only the necessary amount of oil is used in the stamping process.
The Edge Ecosystem is described as a core element of the digitalization of BMW. In addition to enhancing the efficiency of production, it also allows for the minimization of downtime thanks to devices being hot-swappable in the case of failure, thus eliminating the need for backup management in the process.
Another benefit of the Edge Ecosystem is that it can be retrofitted to existing systems, in turn allowing them to work with a modern suite of cloud-based applications. This is accomplished by way of a special gateway software on a device in the system which subsequently converts outgoing data into a format that can be accepted by the cloud. An example is that of loading machines and fire door, which are being integrated into the network of autonomous logistical transport systems.—Alex Tock
[Photos courtesy BMW AG.]