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Relational database as a cogitative part of an intelligent manufacturing system
Igor Drstvenšek, Mirko Ficko, Jože Balič, 2004, izvirni znanstveni članek

Opis: 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.
Ključne besede: production processes, optimisation, relational database, database management systems, production automation, manufacturing system
Objavljeno: 01.06.2012; Ogledov: 959; Prenosov: 26
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Optimization of machining parameters for turning operation with multiple quality characteristics using Grey relational analysis
Franko Puh, Zoran Jurković, Mladen Perinic, Miran Brezočnik, Stipo Buljan, 2016, izvirni znanstveni članek

Opis: Optimization of machining processes is essential for achieving of higher productivity and high quality products in order to remain competitive. This study investigates multi-objective optimization of turning process for an optimal parametric combination to provide the minimum surface roughness (Ra) with the maximum material-removal rate (MRR) using the Grey–Based Taguchi method. Turning parameters considered are cutting speed, feed rate and depth of cut. Nine experimental runs based on Taguchi’s L9 (34) orthogonal array were performed followed by the Grey relational analysis to solve the multi- response optimization problem. Based on the Grey relational grade value, optimum levels of parameters have been identified. The significance of parameters on overall quality characteristics of the cutting process has been evaluated by the analysis of variance (ANOVA). The optimal parameter values obtained during the study have been validated by confirmation experiment.
Ključne besede: ANOVA, Grey relational analysis, multi-objective optimization, Taguchi method, turning
Objavljeno: 12.07.2017; Ogledov: 217; Prenosov: 93
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