Glossary

general reference

A general reference GREF(P) is a global reference. The smart pointer GREF(P) can refer to a local persistent object or a stub object. A method call is handled accor- dingly using either a local or a remote call.

global interface

The global interface of a class is the subset of the methods of the class which can also be called remotely.

global reference

A global reference is used in GINA to address an object, which is (possibly) remote. There are different types of global references – pure data references or smart pointers in the form of remote references or general references. A global reference can be reduced to a local Persistency Service reference on the target application.

global transaction

In a distributed transaction, a transaction monitor groups together a number of local transactions to form a global transaction.

When the end of the global transaction is reached, either all the local transactions are rolled back, or all the local transactions are terminated with a commit. The local trans- actions do not therefore behave like nested transactions.

inheritance

In object-oriented languages, a derived class inherits the interface of its base classes. In C++, the implementation of the base classes is also inherited together with the interface.

instance method

An instance method is a method which is used on a certain instance, i.e. an object, of a class. These are also called object methods or simply methods.

instantiation

In object-oriented database systems, an object is generally accessed directly using a reference. In Persistency Service, the persistent object is instantiated when it is first accessed, i.e. it is loaded into the process address space.

job submitter

see client

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Siemens V 4.0 General reference, Global interface, Global reference, Global transaction, Inheritance, Instance method

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.

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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.