Druck vom 24. 01.2001 17:01.04 sys-adm

DB administration

Should a recovery procedure be required, manual interception to diagnose the error on the one hand and rectify it on the other (replace the faulty component) is generally necessary. Only then can the data recovery be performed from the backup archives using the appro- priate programs (onarchive). This process can take a long time, during which the database can only be partially used or not at all. If this cannot be tolerated in reality (error-protected 24-hour operation), additional replica databases can be installed on a secondary system, with the option of automatically switching over to the replica in the event of error. Of course, this also means that appropriate access possibilities (connections) are required to commu- nicate with this secondary system.

A detailed description of these topics can be found in the appropriate manuals for the data- base system [19], [20], [21].

8.2.3 Logging database errors

GINA allows you to log INFORMIX errors in a file for the purpose of debugging during the development phase.

If the GINA_DBPROT environment variable is set when the application is started, database errors at SQL level are logged to the file specified by the value in this variable. In the case of errors in filter iterators, the relevant select statement is output before the INFORMIX error message.

GINA_DBPROT must contain a valid file name. The file is created automatically if it does not yet exist. If the file already exists, new error messages are simply appended to the existing file.

GINA V4.0 System Administrator Guide – September 2000

195

Page 206 Page 208
Page 207
Image 207
Siemens V 4.0 manual Logging database errors
Page 206 Page 208

V 4.0 specifications

Siemens V 4.0 is an advanced digital platform designed to enhance operational efficiency and streamline processes in various industries. It embodies the principles of Industry 4.0, leveraging cutting-edge technologies to create a more connected, intelligent, and automated manufacturing environment. This platform integrates data-driven insights and advanced analytics to facilitate informed decision-making and improve productivity.

One of the main features of Siemens V 4.0 is its ability to provide end-to-end visibility across the manufacturing value chain. By connecting machines, production lines, and supply chains through the Internet of Things (IoT), Siemens V 4.0 enables real-time monitoring and control. This connectivity allows companies to identify bottlenecks, reduce downtime, and enhance overall operational performance.

Another key technology embedded in Siemens V 4.0 is artificial intelligence (AI). AI algorithms analyze vast amounts of data generated throughout the production process, enabling predictive maintenance and optimizing production schedules. By anticipating equipment failures and streamlining operations, businesses can achieve significant cost savings and minimize disruptions.

Siemens V 4.0 also emphasizes the importance of automation and robotics. By integrating robotic process automation (RPA) into manufacturing workflows, companies can achieve higher levels of efficiency while reducing human error. This automation not only speeds up production times but also allows workers to focus on more complex tasks that require human ingenuity.

Additionally, Siemens V 4.0 supports advanced simulation and digital twin technology. Through the creation of virtual models of physical assets, manufacturers can simulate different scenarios, identify risks, and optimize design processes before implementation. This capability accelerates innovation while minimizing waste and resource consumption.

Another important characteristic of Siemens V 4.0 is its scalability. The platform can be tailored to meet the unique needs of various industries, from automotive to pharmaceuticals. This flexibility ensures that companies of all sizes can leverage its capabilities, driving global competitiveness.

In conclusion, Siemens V 4.0 is revolutionizing the manufacturing landscape through its comprehensive suite of features, including IoT connectivity, AI-driven insights, automation, and digital twin technology. By adopting this platform, businesses can transition toward more efficient and sustainable operations, ultimately preparing them for the future of industrial production.
Top Page Image Contents