The digital transformation has caused quite a stir. In manufacturing, it is seen as a completely new concept that is fundamentally changing the world of production and work. It will have a far-reaching impact on large and small companies, consumers, Germany as a business location and global markets. And it will be neither quick nor easy. This is particularly true for manufacturing companies that have large plants, production facilities and extensive transportation fleets. They have to plan for long investment cycles and bear enormous risks in terms of production downtime and quality control.

Dr. Stefan Grotehans, Senior Director Solutions Engineering DACH, MarkLogic Germany. © MarkLogic

In Germany, there is a lot of talk about Industry 4.0 in the course of digitalization; it is seen as a future project of the German government, while the term Internet of Things (IoT) is more common worldwide. Industry 4.0 is replacing conventional production structures with intelligent, self-controlling and sensor-supported production systems. People, machines and workpieces are networked with each other using modern technologies, which increases the degree of individualization in production.

Industry data for production

In addition, manufacturers can react to changing conditions in real time and control and optimize production processes accordingly. According to experts, this could lead to an increase in productivity of up to 30 percent by 2025. In order to successfully take this step, manufacturers must first ensure that their machines are operational and state of the art. Equally important is the technology they use to collect, process, link, analyze and correlate data. The huge streams of data collected and stored by sensors are of immense value. However, they will only bring real benefits if companies organize, search and analyse this data and ultimately use it for product development and process optimization.

In order to exploit the full potential of Industry 4.0, companies need to industrialize their data. This is the only way they will gain access to their treasure trove of data. As a first step, they must first ensure that the data obtained can be fully integrated so that a comprehensive view is possible.

In order to integrate the distributed data, an intelligent operational data hub that can accommodate data in a wide variety of formats is suitable. This can be achieved with a NoSQL database platform, for example, which offers the advantage over a traditional relational database that data can be recorded "as it is" without having to define a data model beforehand. NoSQL database systems are also suitable for scalable use. Data security must also be guaranteed so that it can be safely shared both internally and externally with business partners and suppliers. Finally, the data must be accessible at all times, including comprehensive origin and history control.

Challenges on the path to digitalization

In terms of data management, the challenges are therefore enormous. Industry 4.0 will play an enormous role in companies because networked sensors will collect and transmit data in order to obtain information about the imminent failure of a hydraulic pump, the maintenance requirements of a robot or the imminent overload of a power grid, for example. Global companies often lack the appropriate data management system to manage this flood of data, structure it, standardize it and link the data in a meaningful way. These organizations often grow through acquisitions, meaning that they work with a large number of different databases and software systems. The challenges around data and its integration into supply chains do not make things any easier. Some companies have multiple manufacturing systems that provide data to other systems from manufacturing and supply chains, but they are all part of a common supply chain. In addition, the data pots must also be integrated in the development, marketing and sales departments.

The management of data and information on the production route of workpieces in different systems is becoming increasingly important for both production and the supply chain of companies. After all, only reliable data management systems provide quick answers to questions such as "Where and when was this part manufactured?". In the event of a product recall, for example, the manufacturer can react quickly: The production location, product components and their origin as well as the time of dispatch and recipient can be determined quickly.

Every large organization knows that protecting data is mandatory. Protecting data sources as they interact with vendors, sites and customers also requires a centrally managed security model that enables and tracks role-based access rights and actions. Controlling the access of individuals and vendors is critical at every stage of the supply chain, as is tracking and auditing the individuals with access rights to the data. Modern database technologies such as operational NoSQL databases now enable granular access controls for data and control functions that can be used to answer key questions. And it's not all about data security. It is also about controlling access to and updating the data so that analysis results are trustworthy and reliable at all times.

In a highly optimized ecosystem, findings from the supply chain can be useful to other areas of the company, for example by passing on quality control problems to the development department. Delays in the supply chain should also be passed on to the sales and marketing departments. Conversely, insights from sales and marketing must also flow into the manufacturing and ERP systems of the supply chain. Almost all areas of the process benefit from increased efficiency through better information, risk reduction, more effective recalls and better products and services.

The promise of Industry 4.0

With the end-to-end industrialization of company data, manufacturers will learn more about how their products are used by business partners and consumers. This data in turn provides the basis for design decisions that enable manufacturers to bring better products to market faster. Only with such insights and knowledge will manufacturing companies be prepared for the future of Industry 4.0. They will have access to the history of their data in order to be able to react to incidents that require urgent action and to develop new, future-proof business models. The NoSQL database provides a good basis for the industrialized use of existing data, as it offers a wide range of possibilities for its use - from the optimization of business processes to the development of solid customer relationships.

Dr. Stefan Grotehans, Senior Director Solutions Engineering DACH at MarkLogic Germany / am