Requirements

3.1 Requirements

The following third-party products are required to implement the GINA components.

Please note that the products listed may be based on other products, which must then like- wise be installed. Up-to-date information on the products required can be found in the Re-

lease Notice included in the delivery.

❍ ❍

Generic++ V2.5 [11]

GINA requires the class library Generic++ V2.5, which is contained in the GINA scope of supply and is installed under the name libsupport2.

openUTM V5.0 and openUTM-Client V5.0

For communication and transaction monitoring, the T-ORB server uses the TP monitor UTM. GINA Version 4.0 requires UTM Version openUTM (UNIX, NT, BS2000/OSD) V5.0 or later [29].

To connect non-transaction-monitored applications (T-ORB client) to a transaction- monitored server, the CPIC interface is used.

This requires the product openUTM-Client (UNIX, NT) V5.0A or later [36].

The software component UTM-D is also required when using GINA with BS2000.

INFORMIX Dynamic Server 2000 (IDS.2000) V9.2

The Persistency Service in GINA V3.3 uses INFORMIX as the data storage system. INFORMIX Dynamic Server 2000 [19] (UNIX & NT) and Client SDK 2.40 (UNIX and NT) are required.

The XA interface [5] is required for the integrated use of T-ORB and the Persistency Ser- vice. This interface is only integrated under UNIX in V9.2. Detailed information on cou- pling T-ORB and the Persistency Service under WindowsNT can be found in chapter 6, Compiling and linking, of the Developer Manual [13].

10

GINA V4.0 System Administrator Guide – September 2000

Page 22
Image 22
Siemens V 4.0 manual Requirements

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.