Posts Tagged ‘data processing’

The Possibilities of zenon and zenon Analyzer in the Cloud

Tuesday, December 22nd, 2015

The cloud offers some interesting benefits that make moving an energy data management system to the cloud interesting for companies of any size. You can implement the cloud solution flexibly, because both zenon and zenon Analyzer offer secure connections to Microsoft Azure. The following scenarios are possible:

Scenario 1: Data in the Cloud

With this variant, the software components, zenon Operator, zenon Supervisor and zenon Analyzer, are installed locally. The data is stored in the cloud. Energy data is recorded free from error in the LAN and does not depend on the internet connection. Only in the next step is the data stored in the cloud. If the internet connection fails, the data is cached locally until the connection is re-established again. The data that is stored decentrally can be called up from the cloud regardless of location. If the energy manager is not at the same site or if a company has several production sites, this is a decisive organizational advantage. Another plus is that upfront investment costs and running costs are low.

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Scenario 2: zenon Analyzer in the Cloud

In this process, zenon Analyzer is installed in the cloud in full. The data is stored locally on the respective zenon Operator or zenon Supervisor. For reports, zenon Analyzer gets this local data and creates the respective reports. This solution is primarily interesting if there are several production sites that record data independent of one another. The investment costs and running costs are low; the solution can be easily scaled up if required.

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Scenario 3: Both Data and zenon Analyzer in the Cloud

With this scenario, the infrastructure is almost completely moved to the cloud. The data is stored in the cloud and zenon Analyzer is also installed in the cloud. You thus no longer need to worry about data storage and the server infrastructure. The internet connection is no longer a limiting factor, because the data connection within the cloud is extremely fast. Here too, there is a decisive advantage in location independence: regardless of whether you have several production sites, regardless of where the energy manager is, the data can always be evaluated and analyzed anywhere. With this solution too, the costs are low and the storage capacity and computing power can be adapted individually and expanded quickly.

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Big Data in the Production Environment?

Friday, October 9th, 2015

Big Data has been one of the hyped topics in the IT field for some time. But what’s the situation in automation infrastructures? Is the handling of large amounts of data also becoming more significant in the industrial production environment?

In the recommendations for implementing Smart Factory, Big Data is named as one of the future technology requirements. But where are we now? Handling data amounts in petabyte dimensions is currently the exception in production. However, today there are already application scenarios that lead us towards very large amounts of data.

Typical Status Quo

When archiving production data, choices are made selectively in relation to which data is saved. Some data is automatically deleted again after certain time periods. With applications such as Energy Management, for example, a multitude of data points are often archived, but generally with a very rough granularity, which in turn keeps the amount of data low. In HMI applications, machine-orientated data is often saved at the panel directly and, at least in part, exported to central archives or databases.

Possible Scenarios

With Big Data in manufacturing, all relevant data in relation to the complete life cycle of a machine or plant can be saved. Based on this data, completely new possibilities for analysis arise. The operators of machines and equipment (manufacturing companies) can work with the data from their entire production estate. The machine and equipment manufacturers have data from a number of the same machines available for their evaluations.

The Benefit of Big Data

Manufacturing companies can uncover unexploited potential in equipment efficiency and effectiveness as well as quality management with Big Data analyses, which in turn increases the Overall Equipment Effectiveness (OEE). Another advantage is that it allows predictive maintenance. Optimized maintenance management has a positive effect on production costs and overall equipment effectiveness.

Machine and equipment manufacturers can also gain additional valuable findings in relation to improvements in construction using Big Data analyses which can, for example, consequently increase the manufacturing capacity and energy efficiency at the same time.

Big Data applications with zenon

Big Data applications with zenon

Big Data with zenon

zenon already offers possibilities for handling very large amounts of data. Data security, the rapid evaluation of data and ergonomic handling are the main focus. Users can freely choose whether they operate zenon purely on-premises or scale it with enhancements to the cloud. With version 7.20, zenon can be seamlessly integrated with the Microsoft Azure cloud platform.

In addition, we are working in both Product Management and Research & Development to make zenon even better at handling ever-larger amounts of data.

How the zenon Analyzer connectors work and how they are used in practice.

Tuesday, June 4th, 2013

The zenon Analyzer reports are based on process data from HMI/SCADA systems. In order to avoid redundant data these data are not stored directly in the zenon Analyzer. When creating a report the data are loaded into the zenon Analyzer using our so called ‘connectors’. Depending on the location of the data, we provide two different connectors.

The SCADA Runtime Connector is used to load data directly from the SCADA runtime, whereas the SCADA SQL Connector is used to load the data directly from SQL databases.

For increased availability the SCADA Runtime Connector is capable of working in a redundancy environment and connects automatically to the standby server if required.

Connector types

Each connector works in a different way:

SCADA Runtime Connector:

zenon Analyzer_Runtime Connector

This connector consists of two components. An extension of the Microsoft SQL-Server directly on the Analyzer Server (the so called ‘ZRS Provider’) and the connector container incl. the connector plug-in  installed on the SCADA runtime computer. When requesting a report, the ZRS Provider connects via the network to the connector container. Its plug-in contacts the runtime using the COM interface and the runtime delivers the requested data which are sent back to the ZRS Provider. Now the Analyzer Server can access the data for further processing.

The big advantage of this connector is the possibility of using actual data from the runtime.

The connector can access:

  • Actual values from variables
  • Historical values from variables
  • Lots
  • Alarms
  • Chronological Event List

 

SCADA SQL Connector:

zenonAnalyzer_SQLConnector

This connector directly accesses process data evacuated in databases. The database server used for storing these data just needs to be added once in the ‘zenon Analyzer Management Studio’ as a linked server and can be of any type of SQL-Server, Oracle server or ODBC-Server.

The data are accessed directly with Table Valued Functions in order to ensure optimal performance.

The big advantage of this connector is the speed of the data connection and the independence from the HMI/SCADA runtime.

The connector can access:

  • Historical values from variables
  • Shifts
  • Lots
  • Alarms
  • Chronological Event List

 

Open data interface

All connector functions can be accessed directly and manually in the SQL Server of the Analyzer Server using Table Valued Functions. So you are free to develop your own reports.

Furthermore, you can develop customized connectors according to your data and your needs.

SCADA SQL Connector:

If you need a personal, network-based connector, it is possible to develop an own connector plug-in as a dll file.

SCADA SQL Connector:

For individual connection to databases the SQL Connector has an open SQL interface. By using Table Valued Functions you can program your own connector accesses to any data format.

Conclusion

The connectors are a very easy and comfortable way of retrieving the data you need for reports, regardless of whether you use our predefined reports or if you wish to develop your own reports. The interfaces allow them to be customized and modified to suit the customers` needs.