SAP, together with a multi-national German auto manufacturer, is poised to contribute to the Industry 4.0 movement, which emerged under Internet of Things (IoT) technology as an advancement in digital data collection and analysis. Industry 4.0 will reshape manufacturing, and SAP is participating by creating high-tech data collection and design solutions to streamline CNC machines for a more connected, digitized future.
The Technical Problem
When engineers design production lines, there is an unavoidable tradeoff between quality and speed. Additionally, valuable historical data from CNC machines, which could be used to improve processes, are not accessible because they aren’t being captured.
SAP aims to create a solution that increases CNC machines’ capabilities by working to understand how the systems behave, which stems from making data readily available and easy to analyze. The solution, Machine Manufacturing Analytics (MMA), helps engineers better utilize CNC machines’ capabilities through high-tech data capture and analysis, without negatively impacting quality or performance.
MMA visualizes a large set of real-time data through a newly designed interface, which allows engineers to adjust production processes as they are happening, and to make better predictions moving forward. Ultimately, MMA helps design manufacturing processes and is scalable to monitor large-scale production in multiple locations.
Revolutionizing the Manufacturing Cycle at the Roots
CNC milling operations rely on three legs of the manufacturing process to be successful: production planning, execution, and quality inspection.
During the production planning phase, engineers configure production lines for the machines, which can take months of trial and error. Without precise data, engineers rely on their experience to fill in the gaps.
MMA alleviates roughly half of this time by providing digital access to historical data from past production processes, so engineers don’t have to constantly start over. For example, MMA can capture data from a single machine for each production session and also aggregate data from several machines at a factory level, to help formulate an efficient, error-free production plan.
Quality inspectors, who carry out the second leg of the process, traditionally must wait until the production process is over to assess quality and report errors. However, MMA analyzes and visualizes the information in real time, in an interactive 3-D environment, making it easy to identify errors that arise for immediate assessment.
For example, an airplane turbine blade may take 3 days to mill, plus additional time for quality testing. With MMA, instead of spending significant time on one blade before adjusting the process, engineers can catch errors when they occur and tweak the process. MMA, in this example, saves time, effort, and materials.
Ramping Up the User’s Benefits
Critical to the success of MMA was developing a supporting user interface. While MMA taps into massive amounts of data that were previously inaccessible, collected at a rate of 1 million data points every 30 seconds, the output needed to be visualized in a consumable way for engineers to recognize patterns of errors, identify, and fix problems efficiently.
To do this, SAP utilized design thinking to co-innovate a user-centric solution. The design team visited local manufacturers to observe, interview, and work with engineers, which allowed them to understand the user’s existing ways of thinking—vital to creating a successful user interface. The team learned how engineers think about the manufacturing process in the pre-IoT world and attempted to mimic their mental models digitally.
For example, a machine’s cutting tool is programmed to travel on a certain tool path in order to cut a block of metal into the final workpiece. The machine provides data about the actual tool path that the tool followed. While MMA could potentially provide engineers with data corresponding to the entire tool path, it is more useful to know which points of the actual tool path deviated too much to create a usable workpiece.
This is why the chosen data visualizations highlight critical regions, or instances where tolerance violations occurred, in red. Users can choose to dig deeper. But, at first glance, MMA alerts them if something went wrong, and where it went wrong, immediately.
SAP is helping to transform user’s physical experiences of analyzing data into a more efficient, yet intuitive, digital design that can be applied globally. SAP is partnering with the auto corporation as a pilot customer to accomplish this by iterating and adjusting MMA, to create data visualizations that are easy to understand.
Additionally, MMA was launched at Europe’s largest trade show, Hannover Messe, in 2016 to demonstrate how the team will step into the IoT space by bringing the technology into manufacturing to improve processes.
The team plans to explore applying MMA to other machines with similar characteristics, such as robots and 3D printers, which could open the door for more widespread global use. Ultimately, however, SAP wants to connect the data collected and utilized by MMA to SAP’s larger ecosystem as part of SAP Leonardo, the company’s new digital innovation system designed to intelligently connect people, things, and business.