SPS IPC Drives Hall 7, 391 Stand
How far the coordination of production and MES / ERP world on the way to the industry 4.0 is already realizable, shows the common IoT solution of SAP and Mitsubishi Electric, Customers of the automation specialist can directly contact the cloud platform of the eF @ ctory Alliance Partners connect SAP.
The tools and applications available there can leverage their production and plant data. Predictive maintenance and service engineer support through augmented reality are just two examples of the many ways to increase efficiency that comes with integration. On the part of the plant manufacturer, the new view of user usage data opens up innovative concepts for value creation in the service sector.
The showcase of the collaboration between Mitsubishi Electric and SAP is a Mitsubishi Electric robot with a digital image of the physical product in the SAP Cloud Platform. The digital twin enables the comprehensive analysis and use of all plant and process data by both the manufacturer and the operator.
IT and production have to find each other
A huge obstacle for the industry of 4.0 and the Internet of Things (IoT), which should make previously inaccessible data useful, is still the historical separation of the IT world and production technology or "Operational Technology" (OT). While data protection puts data protection and confidentiality first, availability is the nuts and bolts of production. With the integration of previously closed production systems to the Internet and the new responsibility of IT to manage and secure the means of production, both sides need to come together to be productive and efficient in the era of IoT.
Also on the IT side and Mitsubishi Electric on the OT side, SAP first had to agree on common definitions to connect the Mitsubishi Electric automation world with its PLCs, robots, motion controllers and CNC controls to the SAP Cloud Platform realize.
Centralized data transfer
The Mitsubishi Electric automation platform provides device-wide visibility. This means that all data can be accessed from a central point in production. It is also very easy to exchange data with other automation components such as RFID readers, sensors or other control systems. All data is transferred centrally to the SAP IoT Services of the SAP Cloud Platform.
The SAP Cloud Platform stores the data for storage in a big data lake and then makes it available to all applications and services of the Cloud Platform. Short-term data, for example, the time series of the past four weeks, are stored in an in-memory database to allow quick access. The historical data is managed in lower cost classic big data storage. The management of large amounts of data is provided via the SAP Cloud Platform as a service (PaaS), ie the user does not have to set up and operate a big data architecture in his own data center.
Immediate IT connection of production
The special feature and significant simplification of the automation solution is the direct connection of the production without the use of additional gateways. The automation's proprietary technology and bypassing of Windows-based systems ensures a high degree of security (cyber security) for the systems. Alternatively and with other manufacturers, the connection is made with a software gateway via OPC UA.
For the connection to SAP is on the Programming platform "iQ WorksMitsubishi Electric defines a data structure for the data to be sent to the SAP Cloud Platform. For the showcase 1000 measurements were given; however, the size of the data structure is freely selectable. Now only the IP address of the Cloud Platform IoT Services and the login data (name, password) must be parameterized at the communication interface C Application Server. Thereafter, the data is continually exchanged, typically all 500 ms. Of course, further data structures with different transmission intervals can be defined. The event-driven transmission of individual data is possible in parallel.
In the cloud, this information is distributed among the different applications. The services offered here include analytical tools for evaluating error codes, machine learning services, development services for cross-device development of your own applications, and integration services for the local SAP ERP systems. Subsequently, the evaluated data are simply transferred back into a predefined data structure to the automation world.
The data structures for sending and receiving are defined jointly by the IT and OT teams. In the case of the robot cell, only a sufficiently large data space was defined and gradually filled with life. The definition of the measured values and properties was carried out by means of a data table divided in the cloud. The exchanged values can be checked and visualized directly with the tools of IoT Services. You distribute the data to the immediate-use remote monitoring, predictive maintenance, dashboard, and more.
Digital twin opens up business models
The Digital Twin is the point at which all information about an asset is merged from the CAD data to the live cycle information. Parameters, programs and libraries via the automation devices can also be stored here. This enables automated data exchange from design to simulation. "Actually, Digital Twin is old hat," says Adrian Langlouis, Solution Architect, Discrete Industries at SAP. "Manufacturers of smart devices use the digital image from their service module for service, and plant operators use their maintenance module to define maintenance intervals." So far, manufacturers and operators have a one-sided view of what's happening in their own modules; in the future they should share their contents with each other.
Modern digital twin
"A modern digital twin is created when information about the physical product is exchanged between all parties on a cloud platform such as the SAP Asset Intelligence Network. Manufacturers, service partners and plant operators each receive an individualized view of the plant, "explains Adrian Langlouis.
For the manufacturer, using the digital twin in the asset network is a service portal where he can provide documentation, 3D models, maintenance instructions or health scores of the asset, and set up self-service capabilities for the customer, such as ordering directly Spare parts by selection on the 3D model.
Plant operators receive a uniform view of the digital machine file and, if required, can create a service ticket directly in the customer portal and order spare parts from the original manufacturer or via a connected 3D print marketplace from SAP. Optimization potential opens up by waiving the stockpile of printable slow-movers.
Optimization of maintenance with predictive maintenance
By analyzing historical machine data from the control and sensor systems, deviations and error patterns can be detected and used to monitor systems or optimize maintenance cycles. The SAP Predictive Maintenance and Service solution delivers the necessary data models and algorithms to model and monitor assets through regularly calculated and visualized health scores and integration with SAP maintenance and service solutions.
Manufacturers with a variety of identical machines at the customer's sample size can deliver a particularly solid data for the Health Score and either offer self-monitoring and predictive maintenance as a service or facilitate the maintenance of the customer. In any case, maintenance cycles can be optimized and, in some cases, considerable cost savings. As far as the database is concerned, maintenance on the part of the operator and service on the manufacturer side are nothing more than two sides of the same coin.
With industry skills shortages, service organizations or maintenance departments find it difficult to retire or retire with experience. One way out of this dilemma is to use Augmented Reality (AR) for maintenance. Visualizing maintenance instructions step-by-step through an 3D model with data glasses allows more complex maintenance tasks to be carried out even for inexperienced employees. But if support is needed, an experienced technician can be videoed in to help colleagues on the job.
At the SAP and Mitsubishi Electric showcase, the technician can place a mobile device, such as an industrial tablet, directly on top of the robot, and get the 3D model in front of the physical product. The 3D model shows him which part to swap and how to do it. AR technology can greatly simplify and optimize the work of the service technician.
Equipment as a Service (EaaS)
With full connectivity to device data and remote monitoring, plant builders can position themselves as full-service providers, providing their entire services in service-level agreements and assuming responsibility for plant maintenance and availability. While manufacturing companies can outsource such unproductive activities and focus on value-added activities, the manufacturer benefits from customer loyalty and better continuity and sustainability of its sales streams.
On the basis of universal data transparency, it is possible to consistently develop new business models away from device sales and towards service offerings such as "pay-per-use". In doing so, the machine or plant remains the property and responsibility of the manufacturer, who calculates the performance or the output on the basis of a metric to the customer. Existing examples from the industry include the number of printed pages for printing presses, operating hours for construction equipment and the amount of compressed air in compressors.
"I see a very clear business model in the fact that customers may not buy the system anymore, because the investment is too high for them. Instead, they use the service, which is billed according to a pay-per-use model, where the customer generates added value. This is an enormous potential for us, our customers and their customers to set up new business models, "says Thomas Lantermann, Senior Solution Consultant at Mitsubishi Electric, describing his vision. The customer receives an all-inclusive package with guaranteed availability under Service Level Agreements (SLAs).