Industry 4.0 is continuously picking up speed - and the more production is digitized, the more machine data is collected. The networking of individual production machines with each other within a production plant (keyword: IIoT!) makes it possible to view and analyze the performance of production as a whole and to initiate appropriate optimization measures. With the appropriate software, the enormous amount of data (in some cases 1 terabyte of data per production hour) is automatically processed and visualized. Now the data clusters can be evaluated individually for each machine - or a company can rely on central data collection in production.
In this article, you will learn about the advantages of central data collection for your production and which requirements must be met in order to make the collected data usable.
Collecting Local Process Data - The Key to Greater Competitiveness
More competitiveness: Collect and centrally store, retrieve and visualize with the IIoT platform. Integrated business processes are the basis for competitiveness. The integration of production data into commercial processing is one, albeit extremely relevant, building block on the road to smart production. For some years now, machine manufacturers have been equipping their production machines with the corresponding sensor technology. Collecting data is nothing new - what is new in the course of Industry 4.0, however, is the need within companies to take a closer look at and analyze the data obtained. After all, production data contains information that is often only recognizable at second or third glance - but conceals enormous value!
With Big Data, i.e. "collections" of huge mountains of data, new concepts can be realized after appropriate processing - for example predictive maintenance or the application of techniques and methods from lean management.
The data collection bottleneck: Different standards and data islands
The basis for a smart factory in the sense of Industry 4.0 is company-wide networking with standardized interfaces. However, it is precisely these standards that currently pose the greatest challenge - especially for machine and plant manufacturers. Today, they are required to include data acquisition and transmission in their designs, but in many cases they must adhere to the respective customer specifications when it comes to data provision. Although standards already exist in some branches of industry, they have not yet been standardized across the board and disseminated accordingly. Thus, especially in the current transformation period from classic production to the smart manufacturing of the future, many data islands with different types of data are created within a company, which must be connected with each other.
The German Machine Tool Builders' Association (VDW) has addressed this problem and, with Umati, has provided a standard interface that aims to represent a kind of "dictionary" for the communication of machines from different manufacturers. The Universal Machine Technology Interface, as Umati is called, is intended to enable the uniform definition of machine parameters. In this way, the VDW wants to ensure that machines within a company "understand" each other, even if the machines do not all come from the same manufacturer.
Why data islands also weaken your production
The smart factory is currently still a pipe dream, especially for small and medium-sized production companies. Data collection, on the other hand, has been taking place in many companies for quite some time. The operating teams collect production data using sensors and machine control, order processing also diligently stores documents on the company server, and accounting also generates valuable company data on a daily basis.
But even though most companies now use an ERP system and data collection is part of everyday life, a uniform structure is often lacking. This results in large time wasters, called data silos, every day.
Data silo is the paraphrase for data storage to which only a single department or employee has access. This data remains closed to the rest of the company. Data silos mean that the data stored is neither checked nor updated nor used properly.
Departments may also work unconsciously past each other - and the risk of data loss should not be underestimated either. Especially when only one employee is responsible for a data silo (for example, the foreman for the machine data), illness or termination can lead to the loss of important information.
What are the advantages of centralized data storage?
Even though setting up centralized data storage involves a lot of effort and investment, successful companies stand out from their competitors by implementing digital infrastructures.
The reason: In digitized factories, information is continuously collected around the clock through production data and evaluated in real time. This makes it possible for company management to monitor and control the utilization of machines, optimize production planning and back up the quality improvement of its own products with facts. From the mountain of Big Data, patterns and correlations can be found through automatic analyses that would not have been visible at all without central data collection.
Another benefit of smart production is increased automation. Through AI and machine learning, machines are able to solve problems without human intervention and adjust production steps as needed.
And comprehensive data mining can also provide a glimpse into the future! Because modern data analysis creates the possibilities to adapt production to changing market requirements or customer wishes at an early stage. Maintenance can also be updated with data for "preventive maintenance" - the machines detect malfunctions, faults or missing operating materials so early that unplanned machine stops do not occur in the first place.
Another advantage of digital, automated data acquisition is increased employee satisfaction - in times of a shortage of skilled workers, a factor for sustainable competitiveness that should not be underestimated! Because if operating teams are relieved of "non-specialist", time-consuming routine tasks such as manual data entry, they have more time for the actual tasks in production. More time means less stress - and less stress leads to greater job satisfaction. Modern lead management aims to involve everyone involved in a process in decision-making - this is achieved by centralized, automated and optimized data collection "all along the way".
The key to success: the right software
In order to make economic use of the immense data potential in production, powerful software that is perfectly tailored to the user's needs is essential. The huge mountains of data that are created every day must be processed quickly and securely by these programs to enable real-time analyses. Incidentally, whether the data is stored in a cloud or locally on the company server does not make much difference - what is more important is the performance of the communication and analysis software used.
Conclusion
Centralized data collection in a production facility offers numerous advantages over isolated solutions and data silos. For example, centralized data storage and processing allows highly accurate analysis of productivity, it saves time, and it allows much more flexible adaptation of the entire production to the needs of the markets. The major problem of non-standardized communication protocols and interfaces can currently only be solved on a company-specific basis - but it is to be expected in the near future that standardization and norms will also find their way into the area of the smart factory.
