Data, especially machine data, is becoming increasingly important in manufacturing: Based on information about production quantities and throughput, the condition of the machines, or possible disruptions, production managers can derive measures to continuously optimize production. But how do you obtain such data when the shop floor is not yet digitized? The answer sounds simple at first – manufacturing must retrofit a machine data collection (MDC). But it's not that easy in practice, as there are many different options available, but not all offer the same functionalities. 

Retrofitting machine data collection: These options are available

Manual machine data collection and analysis in Excel is the quickest and most cost-effective alternative. For this, machine data is recorded via run sheets or shift handover protocols and then manually digitized via Excel. However, this method has its pitfalls. Typically, only data that is several days old is available, making a quick response to errors impossible. The disadvantages of manual machine data collection in Excel and the reasons why success remains elusive have been summarized in this article.

Another option is to extend an existing Manufacturing Execution System (MES) with machine data collection. This can be a good solution. Many companies see the advantage of not having to implement another system and train employees on a new system. However, the MES often needs to be updated first, which means the advantages of a familiar system are lost. Furthermore, implementation can take months, and costs can quickly exceed €100,000, while subsequent changes can lead to further high costs.

The last option is to build an IIoT platform, for which pre-manufactured technology components are put together. Then, the "gaps" between the components need to be closed to ensure that the platform operates smoothly. While data quality is much better than the MDC option with Excel, the effort required to build the IoT platform as well as the complexity of such projects can incur high personnel and ongoing maintenance costs.

These components are needed for machine data collection

For successful use of machine data, four components are necessary:

Connectivity

The networking of the data source with a connectivity solution that translates the proprietary and closed protocol of the data source into an open protocol such as OPC UA or MQTT. From this point on, the data can be freely distributed to systems.

Data preparation

Correctly configured units and a standardized naming convention turn confusing variables into usable and easily comprehensible data.

Data storage

Corresponding IT solutions make your prepared machine data accessible in the long term, securely, and centrally. It is also important that machine data is enriched with additional information – contextual data – . Typically, these include order and product data, reasons for downtime, and further comments from workers. This later guarantees the availability of all data in one application.

Data utilization

The collected and prepared data can then be analyzed using reports and dashboards to gain insights and optimize your production. 

The crux lies in having all relevant information in one application, allowing for analysis from high level down to the smallest detail. Then, one achieves a better output with less effort.

More information on how to analyze machine data and what to look for when choosing the appropriate software can be found in this article.

Retrofitting machine data collection with ENLYZE

Another option that covers all four components while saving time, effort, and costs is the Manufacturing Data Platform from ENLYZE. It is also suitable for retrofitting older facilities and mixed machine parks and is fully operational in less than two weeks. The difference from alternatives on the market is that ENLYZE delivers a product that works from the start, rather than a project. 

We establish connectivity to all relevant data sources, take care of the entire integration on-site, and ensure that all data flows reliably. The effort required from the IT department in the company is only to securely integrate the edge devices into the network. Moreover, we handle the entire data infrastructure – our customers can focus on analyzing their machine data.

The collected machine data is then stored in a central location and enriched with order and product data to automatically calculate relevant key figures or Key Performance Indicators (KPIs) in the background. Through the ENLYZE app, we also provide ready-to-use applications for production monitoring, OEE management, reproducibility and performance enhancement, as well as traceability and process auditing. This way, you can not only collect and store your data but also analyze and utilize it immediately for specific applications.

Those who want to use their machine data for additional applications can easily complement our platform and app with other tools via interfaces and integrations – it is designed to prevent the creation of data silos.

Alternative solutions for retrofitting

Alternatively, manufacturing can also be digitized through MES providers with integration partners to implement machine data collection with little effort and low costs. Those who do not find a suitable solution on the market can also build their own solution from tools offered by various providers. More information on what exactly you need for analyzing machine data and what to consider when choosing the right software can be found in this article.

Retrofitting machine data: many options

Companies have many different options to retrofit machine data collection and digitize their shop floor. Based on the collected and processed machine data, they gain important insights into the state of production and facilities to continuously optimize manufacturing. Which option is best suited for retrofitting depends on the local conditions and the company's needs.