Machine data provides important insights into a company's production and, accordingly, information on how effectively and productively the equipment is operating. The collection of machine data (MDE) serves as the interface between machines, production technology, and data processing, allowing for the real-time evaluation of production-relevant data. To analyze and utilize this data for optimizing manufacturing, companies must first be able to collect and store the data.

What is machine data collection?

Machine data generally includes all information that can be generated in a production facility and is captured and made available by programmable logic controllers (PLC) or sensors. This includes, for example, operational data such as start and stop times, performance data like speed, pressure, and temperature, or production data such as information on quantities and throughput.

It's worth noting that machine data collection is not synonymous with operational data collection. MDE only provides a portion of the information that can be collected and analyzed across operations. You will learn about the exact difference and how the two relate to each other in this article.

How can you evaluate and analyze machine data?

Machine data provides important information about the condition of machines, equipment, and production as a whole. But how can companies efficiently collect this data so that they can evaluate it afterward?

Machine data collection involves four components:

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 standardized naming turn confusing variables into usable and clearly understandable data.

Data storage

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

Utilizing data

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

The crux lies in having all relevant information in one application, enabling analyses from high-level down to the smallest detail. This way, better output can be achieved with less effort.

For more information on how you can evaluate machine data and what to look for when choosing appropriate software, refer to this article. 

Four tools for evaluating machine data

Machine data holds great potential for companies to make their own production competitive and continuously optimize it. To obtain information about the condition of manufacturing, the necessary machine data must first be collected and then prepared and analyzed. There are various tools and platforms that focus on different aspects:

ENLYZE

With our Manufacturing Data Platform, even older and mixed machine parks can be fully digitized within a few weeks. Retrofitting machine data collection is often expensive and time-consuming because companies need to set up a comprehensive IT project for that. In contrast, the ENLYZE platform works from day one. The machine data is stored in a central location and enriched with order and product data to automatically calculate relevant KPIs in the background and ensure traceability. Moreover, the ENLYZE app provides ready-to-use applications for production monitoring and OEE management, process analysis, reproducibility, and performance enhancement, as well as traceability and process auditing, so you can easily access the data with just a click.

If you need data for additional specific applications, it can be easily integrated through the platform interfaces, as the Manufacturing Data Platform is designed for maximum flexibility.

Excel

A particularly simple solution for machine data collection is the classic manual recording using run sheets or shift handover protocols, which are then digitized via Excel. While this is a cost-effective and low-threshold solution, it is also extremely labor-intensive. Additionally, it only allows for retrospective work, as the data is usually several days old, making it impossible to correct errors immediately. For more information on why machine data collection with Excel often does not lead to the desired success, refer to this article.

Power BI

The business analysis tool Power BI primarily offers options for visualizing captured machine data. The tool can be easily integrated into the ENLYZE Manufacturing Data Platform.

Minitab

Minitab can also be integrated into the ENLYZE Manufacturing Data Platform and offers numerous possibilities for visualizing data, analyzing processes, and monitoring production.

Evaluating machine data with dashboards

When evaluating machine data, visualization plays a particularly important role: the data often becomes truly tangible, and processes—or disturbances—become visible. Dashboards are especially suitable for this purpose. There are also many different options available. You can find out which options are available, for example, in the area of OEE management in this article, and which five dashboards should be present in any production in this article. 

Evaluating machine data with the right tools

Machine data is invaluable when it comes to making one's production as effective and productive as possible. It provides information about the current state of production, and in a prepared form, it can yield opportunities for optimization. To leverage this potential, companies need the right tools to analyze the machine data. In addition to easy and quickly integrable solutions like those from ENLYZE, there are other tools that can also be easily integrated into the Manufacturing Data Platform. Which ones are sensible for one's own production depends on the specific requirements of each company.