Managing data volumes over the long term and across organisations

Data Management for Production – From Collection to Archiving

In modern production environments, there is rarely a shortage of data. Machines, sensors, control systems and ERP solutions continuously provide measurement values, status messages and process parameters. What are the prerequisites for good data management? The data is captured automatically, meaning that manual work is completely eliminated. Furthermore, the data must be sufficiently up to date and readily available. However, the real challenge lies not in collecting this data – but in keeping it permanently available, consistent, analysable and compliant with regulations. This is precisely where professional data management begins.

Raw Data Alone does not Create Added Value

In its unprocessed form, raw production data is of little use for business decisions. It is available in various formats, originates from isolated systems and does not follow a uniform structure. Without targeted processing, this data yields no reliable key figures, no traceable quality records and no audit-ready documentation.

Typical problems without structured data management: Only once raw data has been harmonised, consolidated, structured and secured for the long term does it yield genuine informational value for corporate management.

Measurement values from different systems are not comparable because units, timestamps or designations differ.
Data is lost because there is no regulated archiving strategy.
Requests from authorities or internal audits cannot be dealt with promptly because relevant information cannot be found or has not been processed.
Decision-makers work on the basis of outdated or inconsistent data.

The difference: Process Data Acquisition vs. Data Management

Process data acquisition and data management are often treated as synonymous – yet they describe fundamentally different tasks when it comes to handling production data.

Process data acquisition answers the question: How does the data get into the system? It encompasses the technical connection of machines, sensors and control systems, as well as the automated or manual transfer of measured values into a database. Process data acquisition ends once the value has been stored.

Data management answers the question: What happens to the data once it is in the system? It encompasses all processes that ensure data remains accurate, accessible, consistent and compliant throughout its entire lifecycle – from initial harmonisation through long-term archiving to structured transfer to ERP systems, quality assurance or regulatory authorities.

Both disciplines complement each other – however, professional data management begins where process data acquisition ends. KRIS covers both: reliable acquisition from heterogeneous sources and the complete management of data throughout its entire lifecycle.

The Complete Data Lifecycle with KRIS

Production data has a lifecycle – it is generated, processed, utilised and must remain available in the long term. KRIS supports this entire cycle: from the initial data capture at the machine right through to structured provision for internal systems and external recipients. No breaks, no data gaps, no manual rework.

Data Acquisition: Connecting Sources

Modern production environments are rarely homogeneous. Machines from different manufacturers, legacy system landscapes and parallel control architectures generate data in different formats and via different protocols. KRIS connects all these sources via a unified platform.

Supported systems and protocols: Data acquisition takes place automatically and continuously at configurable intervals down to the millisecond range. Once a source is connected, data collection runs without manual intervention – reliably and seamlessly.

Machine controllers and sensors via OPC-DA, OPC UA, Modbus TCP and S7
Process control systems such as PCS 7 and WinCC, including automated tag import
REST- and MQTT-based interfaces for modern IoT environments
ERP systems for the transfer of order data, bills of materials and quality specifications
Manual input via counter devices for measured values without sensor connection

Data Retention: Long-term Archiving for over 20 Years

Production data is not disposable. Quality records, energy consumption figures, batch documentation and process parameters must remain traceable and accessible over long periods of time – for internal audits, regulatory inspections and traceability in the event of a complaint.

KRIS is Designed Precisely to Meet this Requirement:

Data retention for over 20 years in a central database
High data compression reduces storage requirements without losing relevant information
Complex caching mechanisms ensure fast access even to historical data records
Redundant databases and automatic backups protect against data loss
Installation in high-availability (HA) environments ensures uninterrupted operation

Data Provision: Transfer to ERP Systems, Regulatory Aauthorities and Auditors

Stored data only reveals its full value when it is made available to the right recipients at the right time and in the right format. KRIS manages the structured transfer of production data to all relevant recipients – both internal and external.

Internal systems: Processed production data is automatically fed back into ERP systems such as SAP – as actual data, quality reports or production logs. Quality management systems (QMS) and fault inspection systems (FIS) receive the information they need for a seamless process chain.

Regulatory authorities and auditors: KRIS processes relevant measurement values, consumption data and process parameters so that they can be used directly for regulatory reporting requirements or external audits.

Management and Controlling: Aggregated key figures, production reports and trend analyses are available via the KRIS apps for plant management, controlling and quality management – role-based, up-to-date and without any IT effort.

We offer complete solutions