Towards a Conceptual Design of an Intelligent Material Transport Based on Machine Learning and Axiomatic Design Theory

Reliable and efficient material transport is one of the basic requirements that affect productivity in sheet metal industry. This paper presents a methodology for conceptual design of intelligent material transport using mobile robot, based on axiomatic design theory, graph theory and artificial intelligence. Developed control algorithm was implemented and tested on the mobile robot system Khepera II within the laboratory model of manufacturing environment. Matlab© software package was used for manufacturing process simulation, implementation of search algorithms and neural network training. Experimental results clearly show that intelligent mobile robot can learn and predict optimal material transport flows thanks to the use of artificial neural networks. Achieved positioning error of mobile robot indicates that conceptual design approach can be used for material transport and handling tasks in intelligent manufacturing systems

Friction Force Microscopy of Deep Drawing Made Surfaces

Aim of this paper is to contribute to micro-tribology understanding and friction in micro-scale interpretation in case of metal beverage production, particularly the deep drawing process of cans. In order to bridging the gap between engineering and trial-and-error principles, an experimental AFM-based micro-tribological approach is adopted. For that purpose, the can’s surfaces are imaged with atomic force microscopy (AFM) and the frictional force signal is measured with frictional force microscopy (FFM). In both techniques, the sample surface is scanned with a stylus attached to a cantilever. Vertical motion of the cantilever is recorded in AFM and horizontal motion is recorded in FFM. The presented work evaluates friction over a micro-scale on various samples gathered from cylindrical, bottom and round parts of cans, made of same the material but with different deep drawing process parameters. The main idea is to link the experimental observation with the manufacturing process. Results presented here can advance the knowledge in order to comprehend the tribological phenomena at the contact scales, too small for conventional tribology

Towards a Conceptual Design of an Intelligent Material Transport Based on Machine Learning and Axiomatic Design Theory

Reliable and efficient material transport is one of the basic requirements that affect productivity in sheet metal industry. This paper presents a methodology for conceptual design of intelligent material transport using mobile robot, based on axiomatic design theory, graph theory and artificial intelligence. Developed control algorithm was implemented and tested on the mobile robot system Khepera II within the laboratory model of manufacturing environment. Matlab© software package was used for manufacturing process simulation, implementation of search algorithms and neural network training. Experimental results clearly show that intelligent mobile robot can learn and predict optimal material transport flows thanks to the use of artificial neural networks. Achieved positioning error of mobile robot indicates that conceptual design approach can be used for material transport and handling tasks in intelligent manufacturing systems

Metalurgija Journal 1962-2022 y – List of Published Papers

U periodu 1962.–2012., tijekom 60 godina neprekidnog izlaženja, u časopisu Metalurgija su objavljivali autori iz preko 40 država, od Mexica do Kine (sa svih 5 kontinenata). Cilj članka je dati Listu objavljenih radova u 199 svezaka ili 238 brojeva, sa 2721 znanstvenih i stručnih, te 287 priloga (ukupno 3008 radova), autora, koji su svoje rezultate i ideje provjeravali ili ih našli na stranicama ovog časopisa. Svima hvala.For the interval 1962-2022 y, during the continuos publication last 60 years, in Metalurgija Journal Authors from 40 countries from Mexico to China (all 5 continent ) have publish. The goal of the Article is give List of Papers published in this interval, 199 issues or 238 numbers, 2721 scientific and technical, and 287 contributions (total 3008 papers ) of Authors whose investigation results and ideas have been examined and found on the pages of this Journal. Thanks for all

Metalurgija Journal 1962-2022 y – List of Published Papers

U periodu 1962.–2012., tijekom 60 godina neprekidnog izlaženja, u časopisu Metalurgija su objavljivali autori iz preko 40 država, od Mexica do Kine (sa svih 5 kontinenata). Cilj članka je dati Listu objavljenih radova u 199 svezaka ili 238 brojeva, sa 2721 znanstvenih i stručnih, te 287 priloga (ukupno 3008 radova), autora, koji su svoje rezultate i ideje provjeravali ili ih našli na stranicama ovog časopisa. Svima hvala.For the interval 1962-2022 y, during the continuos publication last 60 years, in Metalurgija Journal Authors from 40 countries from Mexico to China (all 5 continent ) have publish. The goal of the Article is give List of Papers published in this interval, 199 issues or 238 numbers, 2721 scientific and technical, and 287 contributions (total 3008 papers ) of Authors whose investigation results and ideas have been examined and found on the pages of this Journal. Thanks for all

Optimization of Operation Sequencing in CAPP Using Hybrid Genetic Algorithm and Simulated Annealing Approach

In any CAPP system, one of the most important process planning functions is selection of the operations and corresponding machines in order to generate the optimal operation sequence. In this paper, the hybrid GA-SA algorithm is used to solve this combinatorial optimization NP (Non-deterministic Polynomial) problem. The network representation is adopted to describe operation and sequencing flexibility in process planning and the mathematical model for process planning is described with the objective of minimizing the production time. Experimental results show effectiveness of the hybrid algorithm that, in comparison with the GA and SA standalone algorithms, gives optimal operation sequence with lesser computational time and lesser number of iterations

Optimization of Operation Sequencing in CAPP Using Hybrid Genetic Algorithm and Simulated Annealing Approach

In any CAPP system, one of the most important process planning functions is selection of the operations and corresponding machines in order to generate the optimal operation sequence. In this paper, the hybrid GA-SA algorithm is used to solve this combinatorial optimization NP (Non-deterministic Polynomial) problem. The network representation is adopted to describe operation and sequencing flexibility in process planning and the mathematical model for process planning is described with the objective of minimizing the production time. Experimental results show effectiveness of the hybrid algorithm that, in comparison with the GA and SA standalone algorithms, gives optimal operation sequence with lesser computational time and lesser number of iterations

Autonomous Navigation of Automated Guided Vehicle Using Monocular Camera

This paper presents a hybrid control algorithm for Automated Guided Vehicle (AGV) consisting of two independent control loops: Position Based Control (PBC) for global navigation within manufacturing environment and Image Based Visual Servoing (IBVS) for fine motions needed for accurate steering towards loading/unloading point. The proposed hybrid control separates the initial transportation task into global navigation towards the goal point, and fine motion from the goal point to the loading/unloading point. In this manner, the need for artificial landmarks or accurate map of the environment is bypassed. Initial experimental results show the usefulness of the proposed approach.COBISS.SR-ID 27383808

Autonomous Navigation of Automated Guided Vehicle Using Monocular Camera

This paper presents a hybrid control algorithm for Automated Guided Vehicle (AGV) consisting of two independent control loops: Position Based Control (PBC) for global navigation within manufacturing environment and Image Based Visual Servoing (IBVS) for fine motions needed for accurate steering towards loading/unloading point. The proposed hybrid control separates the initial transportation task into global navigation towards the goal point, and fine motion from the goal point to the loading/unloading point. In this manner, the need for artificial landmarks or accurate map of the environment is bypassed. Initial experimental results show the usefulness of the proposed approach.COBISS.SR-ID 27383808

Social Sciences and Cultural Studies

This is a unique and groundbreaking collection of questions and answers coming from higher education institutions on diverse fields and across a wide spectrum of countries and cultures. It creates routes for further innovation, collaboration amidst the Sciences (both Natural and Social) and the Humanities and the private and the public sectors of society. The chapters speak across socio-cultural concerns, education, welfare and artistic sectors under the common desire for direct responses in more effective ways by means of interaction across societal structures