SAP Leonardo System Supports Innovative Solutions for Process Manufacturers

Author photo: Valentijn de Leeuw
ByValentijn de Leeuw
Category:
ARCView

SAP held its “Leonardo Live” event in Frankfurt, Germany in July to further familiarize the customers, partners, media, and analysts with the company’s SAP Leonardo brand. SAP Leonardo provides an approach to develop and implement innovative processes, applications, and business models. This includes a design approach dubbed “design thinking.” SAP supports design thinking with “Leonardo Labs” located around the world that perform fast-track pilot projects with clients.

SAP product development teams, labs, partners, and users all have access to a portfolio of services and apps from the company’s Leonardo Foundation, which offers business and technical services. These include access to (big) data from operational technology (OT), geographical information systems (GIS), SAP Leonardo sapval1.JPGand IoT; plus machine learning to find new relationships between these data and put them into context using analytics. These analytics can then be built into “Leonardo Apps” to support existing process or business models, or facilitate new ones.

Industry- and process-oriented accelerator packages can reduce the time to application readiness for common processes, with an “open innovation” approach proposed for less common cases. Open to all partners in a value network, Leonardo apps enable cross-enterprise collaboration. The “system of innovation,” has access to and can interoperate with S/4 HANA (the “system of record,” Integrated Business Planning (IBP), and business networks enabled by SAP ARIBA. As sector boundaries blur, SAP Leonardo applies to industry, health care, and retail, but also infrastructure and cities.

Key takeaway from the event include:

  • The SAP Leonardo system of innovation is composed of a design approach, a cloud infrastructure with services, and a growing number of SAP and partner-developed apps

  • SAP Leonardo enables machine learning and Big Data analytics from a broad range of data and information sources, including OT and IoT edge devices

  • SAP Leonardo supports process and business innovation through partners and SAP Leonardo Labs

SAP Leonardo Applications for Process Manufacturing Industries

While many more were presented, this ARC View focuses on three that we found particularly interesting: a water utility application in Brazil, a train asset management application in Italy, and a more detailed discussion of an enterprise-wide solution for a major global chemical company headquartered in Germany.

Optimizing a Water Distribution Network in Brazil

AEGEA in Brazil, a holding company of the ProLagos water distribution company, executed a fast track project with the SAP Leonardo Lab in Brazil.

ProLagos Water Distribution Network  sapval2.JPGThe city in question is a tourist and weekend destination with a very high fluctuation in water demand. The company needed to stabilize and optimize the operation while securing water quality and supply, ideally with a self-regulating system. Using SAP’s design thinking approach and with the participation of a university and a partner, an application was designed that stabilizes operations along the several-kilometer-long network, including reservoirs, pumping stations, and distribution network. To anticipate demand and prepare for demand fluctuations, machine learning techniques correlated demand with weather and traffic conditions and other variables. The project resulted in a simulation model to predict demand and coordinate and control the pumps across the network. The company estimates that this could potentially save the utility approximately $100,000 per month, some of which could be passed along to ratepayers.

The next step will be to run the system autonomously and control operations in closed loop mode. Operators will be notified of the changes applied by the system, observe the system behavior, and only have to intervene in case of abnormal behavior. AEGEA expects that system can be easily applied to its other water distribution companies.

Co-innovating a Dynamic Maintenance Management System for a Train Network in Italy

As discussed in more detail in separate ARC reports, Trenitalia has been engaged in co-innovation with SAP since 2014 to increase the efficiency and effectiveness of the company’s train maintenance activities. The company is gradually replacing its existing preventive maintenance approach with customized methods and algorithms.

A first step was to collect real-time operating data from the trains and apply maintenance for components that needed it, based on the specific health condition of the component. At Leonardo Live, the company gave an update of the project. To enable greater precision in asset maintenance/replacement scheduling, Trenitalia is implementing machine learning to predict the useful life of the components. The solution leverages several different SAP technologies. Based on preliminary results, the company believes that it can reduce maintenance costs by 8 percent, and expects to save a total of €1.3 billion as a result of the project in 2018, with full payback by 2020.

In addition to reducing maintenance costs, the solution also increases customer satisfaction since less unnecessary maintenance and unplanned downtime enable the company’s trains to adhere better to schedules.

BASF Brings Chemical Production to the Next Level

Since the many information resources made available by the German government’s Plattform Industrie 4.0 focus mainly on discrete manufacturing, process industry participants must interpret and adapt the concept’s principles on a company-by-company basis to support transformative innovation.

BASF, one of the world’s largest chemical companies, formed a cross-functional internal team of IT, OT, and other disciplines to research and test potential Industrie-4.0-type solutions for chemicals using a three-step approach: preliminary testing in a lab, implementation of a “Lighthouse” pilot project in the real environment with real users, followed by a full rollout; with intermediate evaluations and “go/no-go” decision points.

The company investigated different applications along the value chain. These included horizontal supply chain integration with suppliers and clients, engineering data management, “Verbund” site optimization, vertical integration between business systems and production systems, and predictive maintenance. Core technologies considered were Big Data analytics, cloud computing, and IoT; which BASF believes are inseparable components. These were combined with artificial intelligence, augmented reality, 3D printing, and mobile devices as appropriate. In BASF’s view, “IoT” is about adding sensors, actuators, and communications to existing equipment. Industrial IoT, in turn, concerns the manufacturing equipment subset.

IIoT as Add-on to the “Automation Pyramid” sapval3.JPGTo realize the full potential benefits of IoT, BASF believes it’s important to address both the organizational and technical issues in concert. The company created a virtual center of expertise, including a lab dedicated to IoT. The company planned, implemented, and runs an “IoT landscape” (cyber-physical systems, communications, and cloud platforms) to identify, pilot, and share use cases. Cybersecurity is a priority and has both organizational and technical components.

In process manufacturing, BASF targets predictive applications to improve operational excellence, improve mobility, and optimize building efficiency across its large fleet of industrial sites. It uses track-and-trace to improve supply chain performance and makes products intelligent to support digital business models.

This all looks good in theory, but how will it be done in practice? According to BASF, the classical technical architecture of the “automation pyramid,” ranging from the field to business levels, will remain intact. IIoT applications will be implemented as add-ons for non-critical, on-line but open-loop applications such as monitoring and optimization. This lines up well with the NAMUR Open Architecture.

In its lighthouse projects, BASF has started to use SAP’s Asset Information Network (AIN) as a collaborative fleet management environment for field devices (instruments and actuators). Vendor-specific, cloud-based services for field devices are available, but many users would prefer to be able to manage multiple vendors from a single environment. BASF mentioned that users could provide their (blind) device usage and health information to their vendors via AIN, providing opportunities for vendors to improve their products and improve the commercial business relationship.

BASF expects its vendors to provide alerts and advice on maintaining or servicing the devices the company uses. BASF’s use case includes providing its vendors with access to historical maintenance data so they, in turn, can provide the company with decision support for selecting the right devices to service during operations or shutdown, verifying spare parts availability, issuing work orders, and providing the appropriate documentation required for maintenance.

Connecting Field Devices

The company has a large installed base of “smart” instrumentation that transmit process measurements via 4 to 20 mA analog signals, but not the rich HART device information trapped within the devices. BASF believes that wireless HART is not widely scalable because of its price. Instead, WAN solutions from the consumer world provides good options. To achieve a low cost per node and the flexibility to potentially reach any device in any plant, BASF is considering using commercial wireless networks to bring in this Wired Connectivity Up to Gateway with Data Diode sapval4.JPGinformation via an independent channel using the MQTT protocol with TLS (transport layer security) to SAP’s cloud application.

In this case, the HART interface on the edge device would be configured read-only to prevent any unauthorized tampering. BASF considers this to be a relatively easy retrofit. Wireless options could include Wireless HART, LoRa, SigFox, or NB-IoT. An alternative would be to use HART multiplexers close to the devices to send the 4-20mA signals and transfer smart instrument information via a gateway to SAP’s AIN. Once the cost of data diodes comes down, the company foresees using these to restrict information flow to the devices.

Finally, for its few greenfield plants, the company is considering installing digital fieldbuses to transmit both process signals and device information and support remote device configuration and commissioning, Wireless Connectivity to Collaborative Cloud Application AIN sapval5.JPGalthough this would require special skills.

BASF believes that IIoT connectivity could overtake fieldbuses in the near future for non-critical functions. The expected business benefits could include device health status monitoring to improve maintenance planning and effectiveness, reduce costs, and improve and avoid unplanned shutdowns; as well as more-effectively assessing the devices and equipment that have reached the end of their useful lifespans.

Conclusion

ARC believes the SAP Leonardo Live helped clarify the brand. Thanks to its success in making its software easier to use over the last ten years, the company has been able to transition from a standard solution approach, to an agile, innovative approach in which standard packages are complemented with fast-tracked custom solutions leveraging advanced analytics and industrial Big Data functionalities.

The customer success stories we attended in the breakout sessions were well-balanced among SAP Leonardo and classical SAP approaches. All were informative and well presented. We believe the BASF presentation could accelerate the adoption of Industrie 4.0 in the process industries, as it defines real-world solutions for, until-now, largely theoretical models such as the NAMUR Open Architecture.

ARC Advisory Group clients can view the complete report at ARC Client Portal on New Client Portal or Office 365 or Box.com on this website.

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Keywords: SAP Leonardo, ProLagos, Trenitalia, BASF, IIoT, Big Data, COTS, Predictive Maintenance, Fieldbus, ARC Advisory Group. 

 

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