Frank Seiferth

The voice from the midmarket – What does a successful IoT strategy from the OT to the IT world look like? | Frank Seifert | seioTec GmbH

Use Case 1 | Glass recycling manufacturer | Long-term monitoring of process data There is also a solution for OEMs with complex supplier structures to save planning time. The use case comes regionally from the Thuringian Competence Center in Ilmenau and is implemented together with an SAP integrator. The customer is a medical device manufacturer (OEM) that works with multiple service providers and suppliers across multiple locations. The OEM’s problem is that the order and delivery date cannot be directly tracked. Often, reconciliation is done via email, but there is no overall picture of where which assemblies of the medical device are located. Transparency about the location, i.e. whether the part is in final inspection or still in assembly, would optimize planning times here. Frank explained that he initially believed that suppliers did not want this data transparency. However, as the project progressed, it became apparent that the OEM was developing stronger customer loyalty and trust through cross-manufacturing planning. The added value is obvious: Planning processes can now be carried out dynamically by the OEM and times can be optimized as a result. An integration of ERP and human resources of suppliers and sub-suppliers, as well as tracking of parts via RFID lead to transparency. This use case becomes particularly interesting when feedback from live data from the shop floor is included. Finally, a “digital shadow” is created as an image of the production depending on the suppliers. Focusing on the technical solution at the start of an Industrial IoT project often does not lead to the goal. Frank explains what other mistakes seioTec GmbH has learned from in the last 2 years. The connectivity and detailed functions should be formulated only after the so-called user experience design. The operator can use a simple MVP to determine which functions are useful at all and which are not, right from the start of the customer journey. In this context, the MVP is the dashboard developed in the front end of the app, which is already operable, but does not access any real data. This is intended first and foremost to quickly and easily show the first minimally functional iteration of the software. After the feedback from the participants has been incorporated, the app can then be further developed. It should cover the minimum functional requirements and ensure relevant feedback for action from all relevant stakeholders. The company seioTec is also involved in a research project, which is composed of a consortium of different companies. The project is called SPAICER and consists of a broad network of over 40 associated partners. The BMWi part-funded consortium is developing a data-driven ecosystem based on lifelong, collaborative and low-threshold Smart Resilience services by leveraging leading AI technologies and Industrie 4.0 standards. The goal is to foresee disturbances (anticipation) and to adapt production planning to active disturbances in an optimized way at any time (reaction). As an example, Frank cites tools used in production. Questions such as, “What happens if I don’t have my tools in stock?” or “Can I predict tool breakage and how can I better prepare next time?” are sifted through. In this consortium, SeioTec is responsible for software and sub-application development to provide resilience management for companies on multiple levels. The goal is to have a sub-ecosystem emerge where other companies, who in turn have developed AI methods for weather forecasting, shipping lanes, etc., can also bring them in. At the end, Frank gives us his view on the future and the forecast on IoT technology in the next 5 years. The medium-sized mechanical engineering sector has become aware that digitization is a huge topic. Pure mechanics is becoming more and more comparable. Software-driven approaches and artificial intelligence are creating opportunities for advantages in the market. New digital services will emerge, and Frank sees great opportunities here for medium-sized companies as well. In the field of AI, it will become increasingly important to create reproducible approaches. Big Data is becoming Smart Data, and these approaches need to be communicated in an understandable, broadly simple and applicable way. AI must be comprehensible, interpretable, and reproducible by subject matter experts. This is also where boundaries of ethics and areas of application will emerge in the coming years. Are you interested in a cooperation with seioTec GmbH? Contact Frank directly via Linkedin! More about this implementation partner seioTec GmbH is the IoT spin-off of SEITEC GmbH. SEITEC GmbH has been supplying innovative solutions for manufacturing and process automation, as well as industry-related software developments, for over 20 years. The range of services extends from conception to complete project management and worldwide commissioning. For some years now, the interdisciplinary team has also been developing more advanced solutions in the context of digitalization and Industry 4.0. Since 2018, the company’s own IoT spin-off seioTec GmbH has combined 20 years of experience in industrial automation with the many years of IT and WEB technology expertise of co-founder and CTO Kay Hölzemann. seioTec develops customized IoT-based digital business models and services for its customers and accompanies them through all phases of the digital transformation, from consulting and ideation workshops to app development for established IoT platforms, as well as their operation and service.