Igor Drstvenšek (Author), Mirko Ficko (Author), Jože Balič (Author)

Abstract

An intelligent manufacturing system is intended to produce one or more subjects that it is designed for in an optimal way. This means that it has to find a proper production process to produce the subject in an optimal way. The manufacturing system can be called "intelligent" when it is able to find applicable optimisation criteria upon its past experiences thus improving its performance in future. Therefore, an intelligent manufacturing system needs capabilities to store data and make decisions upon them. Such a "brain" can be established by a proper design of a technological database and its database management system (DBMS). Examining all constitutive parameters of a work operation a model of a production process organization can be made, which can serve as a basis for a suitable database design. In addition, an application programme that will check the existence and availability of work operations in the database has to be added to the DBMS. What remains are some optimisation criteria upon which we will choose an operation among suitable and available work operations. This task is fulfilled by a genetic algorithm optimisation technique that would consider work operations' data as parameters of optimisation and on this basis search the optimal one out of the set of available operation.

Keywords

proizvodni procesi;optimiranje;relacijska baza podatkov;avtomatizacija proizvodnje;proizvodni sistemi;production processes;optimisation;relational database;database management systems;production automation;manufacturing system;

Data

Language: English
Year of publishing:
Typology: 1.01 - Original Scientific Article
Organization: UM FS - Faculty of Mechanical Engineering
UDC: [004.89+004.6]:621.7.06
COBISS: 9191446 Link will open in a new window
ISSN: 0924-0136
Views: 1434
Downloads: 105
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Other data

Secondary language: English
Secondary keywords: proizvodni procesi;optimiranje;relacijska baza podatkov;avtomatizacija proizvodnje;proizvodni sistemi;
URN: URN:SI:UM:
Pages: str. 114-122
Volume: ǂVol. ǂ157/158
Chronology: Dec. 2004
ID: 8718727
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