Computer Numerically Controlled (CNC) machines are responsible for crafting objects the world relies on daily, including everything from jet engines to mobile phones. Capable of mass producing objects with near exact precision through programmed actions, the machines have increased production speed and efficiency within the manufacturing sector. However, industry leaders are on the cusp of harnessing even greater promise.

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, SAP Machine Manufacturing Analytics, helps engineers better utilize CNC machines’ capabilities through high-tech data capture and analysis, without negatively impacting quality or performance.

SAP Machine Manufacturing Analytics 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, SAP Machine Manufacturing Analytics helps design manufacturing processes and is scalable to monitor large cereal 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.

SAP Machine Manufacturing Analytics 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, SAP Machine Manufacturing Analytics 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.

Real time visualization of parameters and critical regions over a 3D canvas of the workpiece and the machine’s commanded toolpath. 

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, SAP Machine Manufacturing Analytics analyzes and visualizes the information in real time, identifying 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 SAP Machine Manufacturing Analytics, instead of spending significant time on one blade before adjusting the process, engineers can catch errors when they occur and tweak the process. SAP Machine Manufacturing Analytics, in this example, saves time, effort, and materials.

Ramping Up the User’s Benefits

Critical to the software solution success was developing a supporting user interface. While SAP Machine Manufacturing Analytics 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 toolpath in order to cut a block of metal into the final workpiece. The machine provides data about the actual toolpath that the tool followed. While SAP Machine Manufacturing Analytics could potentially provide engineers with data corresponding to the entire toolpath, it is more useful to know which points of the actual toolpath deviated too much to create a usable workpiece.

A 3D render displaying a workpiece and the commanded toolpath.

3D render displaying the commanded toolpath (blue), actual toolpath (black), tolerance tube (green) and critical region (red).

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, SAP Machine Manufacturing Analytics alerts them if something went wrong, and where it went wrong, immediately.

Implementation

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 SAP Machine Manufacturing Analytics, to create data visualizations that are easy to understand.

Additionally, SAP Machine Manufacturing Analytics 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 SAP Machine Manufacturing Analytics 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 SAP Machine Manufacturing Analytics 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.


Customer Facts

Automotive

  • Multi-national German auto corporation and manufacturor
  • Has production facilities on five continents

Results at a glance

  • Brings machine learning to the manufacturing sector
  • Production time roughly cut in half
  • Patents pending

About SAP Design and the SAP Design AppHaus

SAP Design leads with its user-centric design to the intelligent enterprise experience. This strong focus brings customers a design mindset about the entire SAP portfolio, including the SAP Fiori UX design system and language, SAP Intelligent Suite, and SAP CoPilot, the digital assistant using conversational UX. All of this serves our vision to help improve people’s lives by making work delightful. For more information, visit the SAP Design webpage.

As part of SAP Design, the SAP Design AppHaus team collaborates with customers by focusing first on users and their experiences. We guide customers and SAP to apply design methodologies in daily business and establish a collaborative spirit while optimizing the usage of SAP solutions for the end user.​ ​Our approach is grounded in fostering creativity in three key pillars: people, process, and place. We help organizations drive innovative cultures by designing and establishing processes that remove obstacles to creativity. We also support our customers through the creation of innovative spaces, which enable people to do their best work. This focus has led to the successful design and implementation of 800 customer projects across a variety of industries.​

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