Before the Great Data Floods – Why Data Management is Critical for Industry 4.0 Success
In the first part of this discussion, we have addressed general challenges of IoT in Industry 4.0. In this second part, we will be outlining the key aspects of the concept of Industry 4.0 and touch on its connections to the complex aspects of data management.
Germany’s Industry 4.0 and the Reference Architecture Model Industry 4.0 (RAMI 4.0)
Industry 4.0 is a concept that’s being promoted heavily by leading German industrial associations. This label stands for the complete digitization and integration of the industrial value chain by closely linking information and communication technology with automation technology. The concept is based on a service-based architecture and includes accepted standards and protocols (ISO, IEC etc.). Ultimately, Industry 4.0 will provide everything it needs to implement a smart factory within a digital value network.
The objectives of Industry 4.0 are to make all relevant information of an industrial domain available in real time by connecting all relevant entities with each other and to have the capability to use the data that is generated to determine current process statuses at all times so as to derive the best possible value adding decisions. Obviously, Industry 4.0 will deliver an unending source of potentially valuable data.
Bridging the communication gap between lines of business, manufacturing systems and mechanical devices, components and workpieces targets:
- customized mass production (low quantities, batch size one)
- reconfigurable production systems
- the option to produce a wide range of different types of product on the same production lines.
Recalling these ambitious objectives, second-tier purposes like optimized energy management, condition monitoring and diagnosis or self-correction (where a process reacts autonomously, fast and precisely when there are deviations from the benchmarks) are “low-hanging fruits”.
Consequently, Industry 4.0 focuses on all three of the following dimensions on integration:
- Horizontal integration by value adding networks
Within the context of horizontal integration, interconnected companies – manufacturer, supplier, and development and logistics services – regularly exchange relevant information. This notion is to take account of customer-specific requirements throughout all the different phases of a product’s lifecycle – including design, production, delivery and use.
- Vertical integration within automation hierarchies
Vertical standards link the different hierarchies within the automation technology, i.e. at actuator and sensor, control, and planning units.
- Self-optimization of resources
Integrating the manufacturing process is essential to self-optimization. The availability of interrelated data and the competence to harness intelligent tools and concepts paves the way for value adding optimizations.
As an overall technical framework for Industry 4.0, a Reference Architecture Modell Industry4.0 (RAMI 4.0) has been specified. Arranged on three axes – functionalities within factories or facilities, lifecycle & value stream and layer-bases decomposition of a machine – technical standards define a common structure and “universal set of languages” for specific domains.
To substantiate this reference architecture, the elements of the real manufacturing world must have an adequate virtually representation (both, the real and virtual dimension, coined Cyber-Physical System, CPS). In the context of Industry 4.0 this virtual image is not just a snapshot of the current status and current connections. Much more than that, it should also include all the information covering the complete lifecycle of the CPS – comprising relevant information from geometric data, mechanical properties or technical and security features. All further lifecycle dimensions - engineering, commissioning and operations, maintenance and service -add additional data.
All in all, Germany’s Industry 4.0 approach wants to set an international reference framework for a comprehensive, well-structured, fast and flexible interaction between the CPSs on shop-floor level and the LOB IT systems (ERP, Manufacturing Execution System, CRM, logistics etc.) on the other end of the line.
However, Industry 4.0 is a comprehensive framework which has yet to prove its superiority over more pragmatic or restricted approaches. From the perspective of data management, the challenges are by all means enormous. The sensor-driven flow of data must be controlled and Industry 4.0 demands powerful tools for (big) data integration, routing, validation or security management. There is no doubt, that Talend’s Data Fabric will play a significant role in an Industry 4.0 environment.
About the Author – Dr. Norbert Jesse
Jesse is co-founder and managing partner of QuinScape GmbH. QuinScape is a leading IT service provider for Talend, Jaspersoft/Spotfire, Kony and Intrexx. With today 120 employees QuinScape is partner of large corporations and internationally operating SMEs.
Jesse studied Social Sciences with emphasis on economics and statistics at Ruhr-Universität Bochum. He received his Ph.D. with a work on analytics for multi-dimensional spatial data.
Jesse has been organizer and co-organizer of numerous international conferences (Fuzzy Days, FIRA World Congresses, CIRAS, Enterprise 2.0 etc.). He is lecturer at TU Vienna and Visiting Professor at University of Business and Technology, Pristina. Furthermore, Jesse is author or co-author of more than 55 conference papers and co-editor of 6 books.