Prebuilt manufacturing analytics
Production analysis, error analysis, process analysis, product lifecycle, and OEE directly from machine data.
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Manufacturing Insights
Investigate production losses. Target your improvements.
With add-ons for plant analysis, fault analysis, machine status, and more, Manufacturing Insights helps not only understand production issues but also resolve them in a targeted manner. Instead of generic dashboards, production staff have access to views tailored to their specific needs on a daily basis.
- OEE and Machine Conditions
- Error and Process Analysis
- Parts History
When metrics indicate that something is wrong—but not why
Manufacturing Insights is aimed at production, quality, and maintenance staff who want to investigate production losses.
- 01
Key figures show losses, but not their causes
OEE, output, or scrap reveal a deviation. However, detailed data is often lacking to interpret the results.
- 02
Production knowledge is distributed across systems and people
Machine statuses, error messages, process values, and quality information are evaluated separately or compiled manually.
- 03
Messages are acknowledged but not systematically analyzed
It remains unclear which error messages recur during outages and how long the system remains idle as a result. Without a detailed analysis, there is no basis for prioritizing relevant failure patterns.
- 04
It is difficult to ensure that improvements are implemented
Without a comprehensive before-and-after analysis, it remains unclear whether a measure has a lasting effect or merely shifts losses.
Output → State interval → Errors → Comparison
Example: A line falls short of its usual output
The team investigates the affected period, compares stations, and checks the errors recorded during a stoppage. The analysis provides evidence for an action whose effect can then be assessed using production data.
- 01
Recognize
Compare line output and production KPIs over time.
- 02
Narrow Down
Select the affected period and investigate lost time in the machine states.
- 03
Understand
Open a notable deviation and examine, for example, plant notifications or process parameters.
- 04
Improve
Define an action and reassess KPIs under comparable production conditions.
Prebuilt analysis views for your production questions
Plant analysis brings together output, cycle times, process parameters, and station KPIs. Error analysis, machine states, process analysis, and part history extend the investigation with the relevant data and filters.
Message analysis
Which errors occur frequently or last longest?
Analyze error codes, warnings, and downtime by frequency, duration, station, and time period to identify relevant loss patterns.
Top Errors · Time Clusters · Ward-Specific Data
View Analysis Area
Impact on Day-to-Day Production
Less downtime. Better quality. Verifiable results.
Plant managers and process engineers receive the details they need to achieve real cost savings, faster commissioning, and on-schedule ramp-up.
Your IoT Data Hub. Extended for manufacturing.
Manufacturing Insights is an add-on for the IoT Data Hub. You can leverage the data infrastructure and configure manufacturing analytics tailored to your needs. Thanks to extensive configuration options, no in-house development is required.
Data foundation
IoT Data Hub
Connectivity, history, asset and semantic models for machines, production lines, and locations.
View IoT Data HubAI-assisted analysis
Fully automated background analysis using locally running AI detects anomalies and helps with prioritization.
→Frequently Asked Questions Before Getting Started
Does Manufacturing Insights fit into our improvement efforts?
Do we need a perfect database first?
No. The process begins with a clear question about what needs to be improved. From there, the signals and contexts that are actually needed are identified. Existing data can be used, and missing sources can be specifically supplemented.
Does Manufacturing Insights replace our MES or BI system?
No. Manufacturing Insights supplements existing systems with production-related analytics and integrates machine, process, quality, and product context for root cause analysis.
Is this product just another OEE dashboard?
No. OEE and production metrics are potential starting points. The key added value lies in drilling down into machine statuses, error patterns, process parameters, and part histories.
Can we start with a line or a problem?
Yes. The scope of the initiative, the areas for improvement, and the required data context can be limited initially. Proven models and analyses can then be applied to other areas.
Start with a specific question about how to improve
The scope of the data and the analytical views are derived from the desired outcome. Proven models can then be applied to other lines and questions.
- 01Focus
Improvement Question and Narrowing Down the Scope
Together, we determine which deviation should be understood and which line, stations, or products are relevant to it.
- 02Data basis
Mapping Required Data and Context
Machine statuses, process values, error events, and product information are assigned to the specific technical issue.
- 03Utilization
Provide analytics views for the team
The relevant key metrics, drill-downs, and comparison views are reviewed within the context of production, quality, or maintenance.
- 04Scaling
Evaluate Measures and Apply the Approach
Findings and measures are tracked using the same data set. Proven models can be applied to other lines or issues.
30-minute product demo
From production KPI to an unusual machine interval
In 30 minutes, we'll trace a production variance by analyzing equipment, machine statuses, and error messages. You'll see how your team can pinpoint patterns of loss and what data is needed to do so—all without any preparation.
Built on an open IIoT data platform