Shop floor data collection and visualization
Insights on how MES enables real-time performance analysis, KPI tracking, and decision-making through data visualization
Production managers and IT managers in medium-sized companies are under increasing pressure to make manufacturing processes more efficient, transparent, and flexible.
Supply chains must remain stable, customers demand short lead times and increasing variety, while at the same time cost pressure and skills shortages are on the rise. In this environment, a precise, up-to-date, and holistic view of production becomes a strategic success factor.
This is exactly where a modern manufacturing execution system (MES) comes in: it not only makes production data visible, but also usable.
Through consistent real-time data collection, analysis, and visualization, MES becomes a data hub that supports both operational excellence and strategic decision-making.
The following article shows why data visualization and KPI tracking are the key to greater transparency, efficiency, and responsiveness. Learn which technologies and features offer concrete benefits to medium-sized manufacturing companies.
MES as the foundation for real-time transparency
The manufacturing execution system (MES) plays a central role in ensuring transparency in operational processes by continuously recording, analyzing, and displaying production data. Machine, process, and quality data flow together from a wide variety of sources, including machine controls, sensors, ERP systems, and quality assurance systems.
The MES converts raw production data into actionable insights in real time: machine statuses, cycle times, process progress, utilization rates, and malfunctions are immediately visible at all times. Bottlenecks or deviations are not only identified in daily or weekly reports, but at the very moment they occur.
Based on defined thresholds, the MES can send out warning messages as soon as performance drops, increasing downtime, or quality problems are detected. The result: teams react faster, downtime is reduced, and unnecessary follow-up costs are minimized.
KPI tracking: From OEE to WIP – always up to date, always fact-based
Sound production control requires reliable key performance indicators. The MES offers both standard KPIs and customer-specific indicators that are precisely tailored to the needs of the respective plant. The most important KPIs (key performance indicators) include:
- Overall equipment effectiveness (OEE)
As one of the most widely used KPIs on the shop floor, it combines availability, performance, and quality into a clear performance indicator. - Scrap and error rates
Basis for process optimization and early identification of systematic errors. - Target/actual comparison of cycle times
Essential for detailed planning and identifying hidden inefficiencies. - WIP (work in progress)
Transparency regarding circulating stocks helps to shorten throughput times and reduce capital commitment. - Delivery reliability
By tracking plan deviations and order progress, bottlenecks can be alleviated at an early stage.
A good MES displays these KPIs in real time, not just at the end of the shift or day. Dashboards are continuously updated so that shift supervisors, production planners, and management can use the same reliable information and immediately see whether an order is running on schedule, whether bottlenecks are developing, or whether scrap is looming.
Visualization & analysis: From mountains of data to intuitive decision support
The true value of data only becomes apparent when it is presented in an understandable way. MES systems therefore rely on intuitive visualization formats:
- Color-coded machine status displays (e.g., green = production, yellow = malfunction, red = downtime)
- Real-time OEE boards for lines, machines, or entire plants
- Time series charts for quality and performance trends
- Personalized KPI dashboards for different roles
- Interactive target/actual trends for root cause analysis
- Shop floor monitors for visualizing key performance indicators
The concept of a modular portal provides an example of a particularly flexible work interface. As in a modular system, users can individually assemble dashboards from building blocks such as diagrams, lists, drawings, or hall monitors using drag-and-drop. This creates a work interface that is precisely tailored to the tasks on the shop floor.
The portal technology used in cronetwork, for example, enables the creation of cross-system, customized user interfaces – from simple KPI overviews to comprehensive worker cockpits. Users decide for themselves which data sources their interface is composed of and can design new portals without any programming knowledge.
Thanks to the no-code approach, adjustments can be implemented quickly in-house, which reduces the workload on the IT department and cuts external development costs. This flexible design provides operators, shift supervisors, planners, and managers with exactly the information they need: machine status for workers, line performance for foremen, WIP data for planners, and higher-level KPIs for management.
The modular portal thus ensures a targeted, transparent, and always relevant supply of information. On this basis, companies can make informed decisions more quickly and identify optimization potential at an early stage.
Predictive analytics: Looking ahead instead of just reacting
Many medium-sized companies are currently facing the challenge of making meaningful use of the ever-growing volume of sensor data. MES-supported predictive analytics functions create significant added value here by translating large amounts of data into concrete recommendations for action. They enable reliable prediction of downtime and at the same time support the early detection of potential quality risks.
In addition, they can be used to accurately forecast future production output, enabling companies to plan their capacities more effectively. The analysis of pattern deviations reveals irregularities in the process flow, while automatically generated maintenance recommendations define the optimal times for preventive interventions.
Predictive analytics models also help to identify previously undiscovered savings potential. In this way, production control is evolving from a reactive response to disruptions to a proactive, continuously optimized mode of operation.
Plant data collection as a basis for quality
Modern plant data collection (PDC) forms the essential basis of every MES. Only correctly recorded and timely data enable reliable analyses. Production data is collected in real time and assigned to the respective orders.
Supplementary modules such as in-process quality assurance or traceability ensure that quality and material flow information is also fully documented.
Precise production data shortens response times in the event of malfunctions, makes order processes transparent and traceable, and enables realistic target times for planning. In addition, the transfer to the ERP system provides a reliable basis for post-calculation and master data maintenance.
Through the comprehensive introduction of plant data collection, machine data acquisition, detailed scheduling, OEE analysis, and material replenishment control, we plan and control the entire shop floor level based on live data. In combination with SAP, we are now able to digitize processes. With these newly acquired amounts of data, the optimization/digitization of processes is virtually unlimited.
Conclusion: MES as a pioneer of the smart factory
The path to the smart factory involves the intelligent use of data and key performance indicators. An MES provides the central platform for this, from data collection and visualization to analysis, and ensures that all parties involved have access to the same, up-to-date, high-quality information. This creates transparency, efficiency, and a reliable basis for decision-making across the entire shop floor.
At the same time, it is clear that effective KPI management means more than just monitoring numbers. Understanding the causes behind deviations is crucial. Modern MES solutions such as cronetwork help to reveal precisely these problem areas – from hidden bottlenecks to inefficient processes. If such structural causes are specifically addressed, productivity increases sustainably.
For manufacturing companies, this means:
- Greater transparency thanks to real-time data
- Faster response times due to alerts and live dashboards
- Improved planning and utilization thanks to precise KPIs
- Continuous improvement thanks to well-founded trend and root cause analyses
- Cross-departmental consistency of the database
An MES not only makes data visible, but also turns it into a real competitive advantage, laying the foundation for more efficient processes and better decisions in the long term.
Maren Niedermaier
