Emergence of intelligence in next-generation manufacturing systems

被引:25
作者
Brezocnik, M
Balic, J
Brezocnik, Z
机构
[1] Univ Maribor, Fac Mech Engn, Lab Intelligent Mfg Syst, SI-2000 Maribor, Slovenia
[2] Univ Maribor, Fac Elect Engn & Comp Sci, Lab Microcomp Syst, SI-2000 Maribor, Slovenia
关键词
intelligent manufacturing systems; emergence; learning; genetic programming; genetic algorithm;
D O I
10.1016/S0736-5845(02)00062-5
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
In the paper we propose a fundamental shift from the present manufacturing concepts and problem solving approaches towards new manufacturing paradigms involving phenomena such as emergence, intelligence, non-determinism, complexity, self-organization, bottom-up organization, and coexistence with the ecosystem. In the first part of the paper we study the characteristics of the past and the present manufacturing concepts and the problems they caused. According to the analogy with the terms in cognitive psychology four types of problems occurring in complex manufacturing systems are identified. Then, appropriateness of various intelligent systems for solving of these four types of problems is analyzed. In the second part of the paper, we study two completely different problems. These two problems are (1) identification of system in metal forming industry and (2) autonomous robot system in manufacturing environment. A genetic-based approach that imitates integration of living cells into tissues, organs, and organisms is used. The paper clearly shows how the state of the stable global order (i.e., the intelligence) of the overall system gradually emerges as a result of low-level interactions between entities of which the system consists and the environment. (C) 2003 Elsevier Science Ltd. All rights reserved.
引用
收藏
页码:55 / 63
页数:9
相关论文
共 16 条
[1]  
[Anonymous], 1998, Genetic programming: an introduction
[2]  
[Anonymous], 1999, GENETIC PROGRAMMING
[3]  
Back T., 1997, IEEE Transactions on Evolutionary Computation, V1, P3, DOI 10.1109/4235.585888
[4]  
BLEY H, 1996, P 28 CIRP INT SEM MA, P27
[5]   Genetic programming approach to determining of metal materials properties [J].
Brezocnik, M ;
Balic, J ;
Kuzman, K .
JOURNAL OF INTELLIGENT MANUFACTURING, 2002, 13 (01) :5-17
[6]   A genetic-based approach to simulation of self-organizing assembly [J].
Brezocnik, M ;
Balic, J .
ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING, 2001, 17 (1-2) :113-120
[7]  
Brezocnik M., 2000, J TECHNOL PLAST, V25, P1
[8]  
DORNER D, 1976, PROBLEMLOSEN INFORMA
[9]  
GEN M, 1997, GENETIC ALGORITHMS E
[10]  
HOLAND J, 1992, ADAPTATION NATURAL