Manufacturing Insights
Which downtime events, quality losses, or slow process steps deserve attention first? Manufacturing Insights helps production managers prioritize losses, pinpoint causes, and compare the impact of corrective actions.
Message analysis
A message appears on the operator panel, is acknowledged, and disappears from view. Which messages recur during failures and how much downtime is associated with them often remains unclear. Manufacturing Insights systematically analyzes recorded errors and warnings and connects them with machine states and stoppage intervals.
Initial situation
Production losses often result not from a single event, but from the interplay of process deviations, materials, tools, equipment condition, and a lack of context.
These symptoms occur particularly frequently in efficiency projects in automated lines.
Losses in performance and quality often manifest themselves indirectly at first: through longer cycles, more rework or more frequent disruptions.
With complex lines, it is difficult to trace which process steps, parameters or materials actually contributed to the deviation.
Knowledge about typical patterns, threshold values, and measures often remains confined to individual minds.
Analysis approach
Select the period with lower output. Compare machine states and open the error messages for unusual stoppage intervals. After taking action, check whether lost time and output improve under comparable production conditions.
Depending on the line and data situation, different forms of evaluation are used to narrow down the causes more quickly.
Definition and KPIs
Production efficiency describes how effectively a machine converts available time, technical performance, and materials into good parts. The three OEE factors provide a starting point; for more in-depth root cause analyses, they are linked to machine states and process parameters derived from live machine data.
The improvement process combines reliable KPIs with root-cause analysis and a verifiable before-and-after comparison.
Define the relevant loss metric and a reference period for one line, such as downtime, rework, or output.
Investigate anomalies by line, station, product, shift and process parameter instead of comparing aggregated KPIs alone.
Evaluate improvements by loss magnitude, frequency and technical feasibility, then begin with the greatest leverage.
Compare before and after under comparable product mix and operating conditions. Check whether the action works or shifts losses elsewhere.
Ready-made analytics within one platform
Manufacturing Insights provides ready-made manufacturing analytics; the IoT Data Hub handles connectivity, processing, and storage. Select views to match the loss you want to investigate.
These modules supplement the efficiency view with additional analysis perspectives.
The IoT Data Hub extension with ready-made analyses for output, machine states, process parameters, errors, and part histories.
View Manufacturing InsightsFor example: Which recurring stops cost the most time? Within a few days to weeks, we set up a line and the appropriate loss analysis. Scope and data availability determine the timeline.
We'll work with you to select a system and a specific loss scenario. We'll connect the initial data sources directly during the workshop.
We configure the IoT Data Hub and the relevant Manufacturing Insights modules. States, errors, and the required product or process data are mapped.
With customized views, you can identify production losses early on. We evaluate the benefits based on the agreed-upon goals.
30-minute product demo
In 30 minutes, we'll show you how your team can prioritize loss patterns, analyze periods of downtime, and evaluate comparison periods—all without any preparation.