Data Analytics

Our understandig …

Application possibilities

Industrial Smart Data …

Use Cases

Dicover our Use Cases …

Different customer groups - one goal: Intelligent data for intelligent decisions

Business Development

Data Scientists

Plant manager / production manager

Quality manager

Maintenance manager

Not included? We are looking forward to meet you!

Data Analytics with the Digital Twin

Throughout the entire planning and production process the ASCon Digital Twin Product Suite helps you to analyze your value-added processes quickly, targeted and with high performance by enriching logic, context and dependencies in the semantic model of the Digital Twin. With our digital services you analyze, optimize and control your process and production flows and create a structured, semantic data model for the efficient use of integrated AI services.

Our Smart Data analyses are based on artificial neural networks. They learn to identify objects and movements by analyzing data of different size and structure. The spectrum of analysis methods includes both statistical methods and methods of machine learning including deep learning.

Here we integrate AI services of our technology partner Synergeticon, whose analyses support quality assurance and the determination of production errors by evaluating 3D and sensor data.

ASCon Systems - Data Analytics

Throughout the entire planning and operating process the ASCon Digital Twin Product Suite helps you to analyze your value-added processes quickly, targeted and with high performance by enriching logic, context and dependencies in the semantic model of the Digital Twin. With our digital services you analyze, optimize and control your process and production flows and create a structured, semantic data model for the efficient use of integrated AI services.

From Industrial Big Data to Industrial Smart Data

It is not primarily the amount of data collected that matters, but rather its relevance. Smart Data Analyses aim to identify the “right” data, quickly filter out what is really important and place it in the right semantic context of the value creation process. The full economic potential of data can only be unlocked through intelligent processing in the semantic data model of the Digital Twin. This is where Big Data becomes Smart Data.

Big Data

 

1. Collect actual data
Capturing the data of the system
without an overall context

2. Persist data
Storing the unstructured data sets
in the respective raw format

3. Reconstruct context
Complex reconstruction of the context
with technical knowledge

4. Analyze data
Advanced Analytics based on
unstructured data in data lakes

Smart Data

 

1. Modeling Context
Modelling of the information and behaviour model of the system including all dependencies

2. Collect actual data
Collect data of the system in the respective valid context

3. Persist data: digital record
Storage of parameters and measured values in the respective valid context

4. Analyze data
“Refined” structured data is created, which can be analyzed by Smart Data Analytics

From Industrial Big Data to Industrial Smart Data

It is not primarily the amount of data collected that matters, but rather its relevance. Smart Data Analyses aim to identify the “right” data, quickly filter out what is really important and place it in the right semantic context of the value creation process. The full economic potential of data can only be unlocked through intelligent processing in the semantic data model of the Digital Twin. This is where Big Data becomes Smart Data.

Big Data

1. Collect actual data
Capturing the data of the system
without an overall context

2. Persist data
Storing the unstructured data sets
in the respective raw format

3. Reconstruct context
Complex reconstruction of the context
with technical knowledge

4. Analyze data
Advanced Analytics based on
unstructured data in data lakes

Smart Data

1. Modeling Context
Modelling of the information and behaviour model of the system including all dependencies

2. Collect actual data
Collect data of the system in the respective valid context

3. Persist data: digital record
Storage of parameters and measured values in the respective valid context

4. Analyze data
“Refined” structured data is created, which can be analyzed by Smart Data Analytics

Smart Data – Smart Decisions – Smart Business

The ASCon Digital Twin Product Suite intelligently connects different data, system and information sources and converts the collected raw data by the Digital Twin into an “algorithm-friendly” format that can be used by data scientists as well as less IT-savvy users. The centrally collected, contextualized data enables the efficient use of our integrated AI services and can support the user in monitoring, analyzing and optimizing process and production flows – and thus in important decision-making processes. Through targeted training, the AI algorithm can be trained to identify changes in the relevant process parameters and to react accordingly, e.g. with predictions or warnings.

The following analyses are basically possible:

  • Trend detection for a parameter and limit violation detection
  • Continuous trend recalculation
  • Pattern recognition in the course of parameters
  • Statistical limit value detection of minimum and maximum, as well as standard value calculation
  • Anomaly detection (online) for quality and maintenance parameters
  • Correlation of parameters (supervised) for quality and maintenance parameters

Application possibilities of Industrial Smart Data

The areas of application for Industrial Smart Data are many and varied. Two of the most important and economically most interesting applications are in the data-driven prediction of machine or system states (predictive maintenance) and of product states (predictive quality):

Data Discovery

Uncovering unknown relationships in data sets

Decision Support

Shorter-term, more accurate information on decision-making processes

 

Predictive Maintenance

More efficient, proactive maintenance planning through data-driven forecasting

Predictive Quality

Optimization of product and process-related quality through data-driven forecasts

Logistikoptimierung

More efficient, accurate resource planning and utilization

Our Use Cases

Get to know our Use Cases and discover the advantages of our solutions.

Predictive Quality Assistant

Do you have questions or are you interested in a product demonstration?

 

Your contact person

Oliver Browa,
Key Account Manager

Contact us