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Do You Know the Value of Your Machine Data?

WAGO Analytics

When it comes to optimizing your own machine or system, the challenge is to increase and quantify process understanding and integrate it into the process. WAGO Analytics supports you in data acquisition and analysis and creates intuitive visualizations of the dependencies in your equipment. The connections that are uncovered are integrated into your processes and make it possible to fully exploit your potential for optimization.

Your Data Is Valuable – Seize Its Potential
Do you want to optimize your machine or system? Use your sensors and actuators to get to know your system better. Benefit from the potential of your data.

Your Benefits with WAGO Analytics

  • Identifying potential optimization
  • Improving quality levels
  • Saving energy and resources
  • Increasing efficiency and reducing costs
  • Improving process stability

The Steps from Data Acquisition
to Data Analysis

1

Acquiring existing machine and sensor data. WAGO offers all the components needed for this, e.g., the WAGO I/O System 750 and PFC Controllers.

2

The data is recorded from the machine and stored in a uniform structure, either in remote storage or a cloud (e.g., WAGO Cloud).

3

Analyzing and illustrating the information hidden in the existing data makes potential applications and connections visible. This gives you a greater understanding of your equipment and its processes.

Acquiring existing machine and sensor data. WAGO offers all the components needed for this, e.g., the WAGO I/O System 750 and PFC Controllers.

The data is recorded from the machine and stored in a uniform structure, either in remote storage or a cloud (e.g., WAGO Cloud).

Analyzing and illustrating the information hidden in the existing data makes potential applications and connections visible. This gives you a greater understanding of your equipment and its processes.

What is necessary for successful implementation?

Acquiring Existing Machine and Sensor Data

To capture machine and sensor data, you need different pieces of hardware that can provide you with the appropriate database. WAGO offers you a wide product portfolio of different components. The corresponding WAGO products support all standard interfaces as well as most industrial protocols. In addition to the WAGO I/O System 750, the PFC family of controllers or modules for current measurement, the WAGO IoT Boxes are also available for measurement and sensor data acquisition. The WAGO IoT Box is incredibly versatile and ideal for machine and system connections. WAGO's IoT Box is pre-assembled and can send the first data to WAGO Cloud within minutes.

Data Acquisition from Machines and Systems

WAGO Cloud gives you the option of collecting data from various machines and systems, centralizing it and analyzing it. Furthermore, you can manage and monitor all WAGO controllers – including your data and application – on a PC, in a conference room or on a tablet while traveling. With simple, user-friendly operation, the WAGO Cloud was developed so that people without extensive IT experience can use it. Thanks to the app structure, WAGO Cloud is intuitive to use. Many standard functions such as visualization, remote maintenance and firmware update are already set up. Your WAGO Cloud is ready after just a few mouse clicks.

WAGO Cloud is based on the established Microsoft Azure cloud platform. This has numerous advantages for you: Microsoft Azure is highly scalable in terms of computing power, data storage, transactions, availability and security standards – it represents a future-proof solution.

Data Analysis – Centralized or Decentralized

The collected machine and system data can be used for analysis both centrally and decentrally. To centrally analyze your data, all you need to do is bring the data to a cloud environment and then analyze the data there. The difference to the decentralized approach here is that all data is in the cloud and can be accessed at any time from anywhere in the world. By contrast, with the decentralized solution approach, you can, for example, analyze the machine and system data directly in the system. For example, you can use WAGO's Docker technology to implement the analysis application on the controller. WAGO's PFC200 Series Controllers are already Docker-ready. So you can start using modern software and numerous applications on the PFC200.

For additional information about Docker technology, click on the following link.

WAGO Helps You Use
Your Data Profitably

We help you understand your processes and guide you in successfully performing the following steps:

1. Gathering raw data from various data sources

In the first step, the various interfaces of the machines and systems are read out independently of the respective protocol and values are taken directly from the controller. The data is aggregated in one location.

2. Processing the data

There is time synchronization of the data. The relevant information is extracted and decoded in a uniform format. Irrelevant data is filtered out and removed.

3. Continuous data acquisition

An individual data logger for the machine or system is put into operation. The data is stored and used for in-depth analysis.

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4. Explorative data analysis and selection of the right representation

In offline analyses, dependencies and relationships are extracted, interpreted and visualized. Rare events are revealed. With the involvement of process experts, the application potentials are identified and validated.

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5. Integration into the operating process

The analyses and visualizations optimized for the machine or system are integrated into the operating process. They are now always available and can be operated intuitively.

6. Use correlations and optimization potentials

The analyses available in live operation are now used to exploit optimization potentials. Furthermore, live visualizations allow machine and system operators to verify and expand their understanding of the process as well as to identify further relationships and application potentials of the data.

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FAQ – Analytics

General Questions

No, WAGO is happy to assist and advise you.

With the WAGO IoT Box, you can bring additional machine and system data to the cloud without extensive effort or IT knowledge.

No, depending on the application, a local solution (central solution) is possible.

Every analytics solution is individual. If you feel there is more in your data, contact us and we will evaluate your use case with you.

Your data does not leave your existing infrastructure, because the analytics solution is integrated on site in your machine or system.

Real-time analyses can be realized for smaller amounts of data.

We enable specific visualizations that allow you to keep an eye on your analytics application.

A transfer to the same machine and system usually requires no major adjustments. For another machine or system, the effort depends on the specific analytics solution.

To enable independent analysis, we develop interactive visualizations.

This depends on the size of the project and can only be assessed seriously after an exploratory data analysis and discussion with the process experts.

Analytics solutions are designed to identify problems in your process. You can use and interpret the results to derive or avoid technical changes. What is possible can only be assessed after an exploratory data analysis.

For us, an analytics project starts with the first data collected. This is followed by a data analysis to quantify your process understanding. Usually, no data records are necessary on your part. If the solution to your problem requires precise recognition of rare events, longer data collection periods are usually needed.

Yes, as the amount of data increases, the precision of data analysis increases. There is no generally applicable answer whether a high data volume is necessary for your requirement.

The first step, and the first benefit for you, is quantifying your processes. According to experience, further application possibilities are identified.

Processes and Methods

Data science, machine learning and artificial intelligence are intersecting. WAGO Analytics describes the provision and use of the methods of this intersection in the field of automation technology.

Data analysis grows in your computing time with the amount of data examined. Not every analysis method is therefore suitable for live applications.

The range of proven methods is great. Currently neural networks are receiving a lot of attention. However, these are suitable, for example, only for the recognition of events. This means you can not get a complete picture of your machine or system.

WAGO Analytics describes the integration of your analyses into live operation. On the other hand, statistics mean a study of historical data.

Big Data describes large amounts of data. Data Science involves the analysis of data, which can be Big Data, but can also be the live data of your machine or system. Machine Learning is a class of methods for generating new information from data and is part of Data Science.

Approach and Procedure during the Analysis

First, there is a discussion and evaluation of the use case. Data is recorded and your understanding of the process is quantified. Thereafter, further steps with your process experts will be planned and re-evaluated.

After a discussion and evaluation of the application, commissioning of a data logger of the various data sources and preparation of the data takes place. In offline analyzes, the application possibilities are worked out and evaluated in exchange with your process experts. If you are convinced of the results, an integration into the operating process follows. In further steps, we are available to you as a partner.

Not all data is relevant and consistent. Data cleansing is designed to transform the data into a high consistency and information density format. As a result, no unnecessary data is transported, visualized or forwarded to the data analysis algorithm. This allows for efficient operation of your analytics solution.

Focus on the smallest possible area of your system that you want to investigate. Formulate a concrete question and use your process understanding to assess which data provide important information.

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