Today, scenarios based on the Internet of Things (IoT) can be implemented in almost every industry and for almost all types of products. They offer companies the opportunity to leverage lucrative revenue and growth potential. A key driver for companies to add additional services and products to their portfolio is the rising expectations and changing needs of customers.
Lengthy support processes and cyclical, biannual visits from a customer service representative are no longer what customers want. Instead, machines and devices should ideally initiate the necessary maintenance or support processes themselves and provide all the relevant information at the same time: What is the condition of the machine? What work needs to be done? Where is the machine located?
When machines and devices provide such data, this not only has a positive impact on customer service. Rather, this information also offers the opportunity to optimize asset management and reduce the total cost of ownership (TCO). What’s more, the increased expectations don’t stop at service. Adjusting the functionality of a device remotely and while it is in use is increasingly moving from the exception to the rule. At the same time, the variety of machines to be produced is reduced. This includes not only the creation of new functionalities, but also the subsequent modification and improvement of existing features: one machine, many feature flags by software.
The goal of establishing new business models may also require innovative, IoT-supported solutions. This means, for example, that usage-based tariff models can be applied to entirely new types of applications. For example, companies can sell consumption materials that match their machines, automatically resupply them based on inventory and current usage, let machines schedule their own maintenance, or keep track of containers and similar mobile objects at all times. For companies, the Internet of Things offers lucrative opportunities to offer new services based on collected data.
In addition to many new ideas, existing processes in logistics also benefit enormously from increasing networking. Routes can be planned optimally on the basis of mass data, and warehouse sizes can be reduced by quantities that can be determined precisely at any time. Such a permanent inventory creates considerable savings potential.
A core element of every IoT solution is the digital twin – the image of a device, machine or plant in the cloud. This virtual image is always kept up to date and supplied with data by its counterpart in the real world. Analysis models are fed, processes triggered or dashboards filled on the basis of the digital twin.
With the help of customer portals, companies can get closer to their customers and their machines. Customers have greater confidence in the manufacturer’s maintenance and support capabilities, while the associated costs are reduced. New sales channels can also be established with such portals. A great deal of useful information flows back and forth.
Thanks to the Internet of Things, machine manufacturers receive long-term data on machine conditions, user behavior and process information. This data pool offers many approaches to improving products and gaining valuable insights from which new products can be created. Innovative benefits and services such as telemetry-based insurance or leasing are also conceivable. In addition, maintenance strategies and machine wear can be optimized in this way.
Being able to take advantage of the opportunities described requires a well thought-out IoT strategy. This involves overcoming a number of challenges. After all, the digital twin places a few demands on product development, IT and management.
Companies unlock the full potential of the Internet of Things if they manage to detach themselves from the concrete machine as a physical device and view the digital twin as a collection of properties. An abstraction of the functions and circumstances of the individual machine must take place. Only this step makes it possible, for example, to maintain consistent models even across assembly changes and similar deviations. The digital twin is therefore primarily a unified virtual model consisting of various properties and features that can also be found in other products.
Furthermore, the communication path and connectivity of the devices, machines or production lines must be established and standardized. At best, each device should be accessible independently of the company’s networks. Managing all devices uniformly and securing communications requires a logical path of communication. That is, the entire fleet of machines – from small devices to large machines to manufacturing equipment – sends its data to the identical logical endpoint in the same way, if possible. This allows the transport path to be built into each device in a standardized way. This greatly simplifies the management of networked devices and machines.
The endpoint and its downstream systems must be able to receive and process very large amounts of data. The data stream must be able to trigger actions based on each individual message. But direct evaluations on an aggregate basis of a specific time window are also helpful. In addition, the data should be stored and easily accessible for later queries. Ideally, this accessibility is based on APIs that use standard protocols so that any form of client can access it. In this way, an ecosystem of apps and services can be supported.
Ultimately, an IoT system only makes sense if it is integrated with an ERP system. Companies must therefore ensure that they are working on a platform that not only supports seamless integration, but also enhancements and changes. After all, business processes are subject to continuous development, which must be mapped in the software system.
Thanks to SAP Internet of Things, many of the aforementioned challenges can be covered with the help of standard software, so that companies can fully concentrate on the business added value of their IoT scenarios. The basis is SAP Business Technology Platform, through which the service SAP Internet of Things (SAP IoT) is subscribed to and integrated into the respective solution.
The SAP IoT service represents the endpoint for the machine data and offers corresponding onboarding and management options. The ingestion pipeline can be used to define rules and actions in different ways that allow reacting to the data stream and directly launching integrative actions. Modeling machine abstraction works through groups of properties that are grouped into “thing” types. Accordingly, a device or machine is the instance of one or more such types. It is important to note that a “thing” represents the business entity and not, for example, the technical part that provides the data.
SAP IoT provides a whole range of OData-based APIs that can be used to evaluate instantaneous data, but also time series. An extended analytical component can be realized via SAP Analytics Cloud. This standard BI tool is used for both visualization and statistical analysis.
SAP Cloud SDK, together with the SAP Cloud Application Programming Model, offers ideal conditions for creating customized Fiori apps and microservices in SAP Business Application Studio, which are hosted on SAP Business Technology Platform. A seamless extension of SAP S4/HANA in the cloud is thus possible.
By using the portal service, Fiori launchpads can be created that give users access to exactly the use cases they need via roles and groups. Customized apps and environments are the key to ease of use and high user adoption.
But that’s not the end of integration: SAP Customer Experience, SAP Qualtrics, SAP Field Service Management and many other systems can also be easily integrated into the ecosystem. The entire landscape of SAP Business Technology Platform is available for this purpose. This means that there are practically no limits to the design of innovative IoT scenarios.