A Visionary Way to Novel Process Optimizations The Marriage of the Process Domain and Deep Neuronal Networks

被引:5
作者
Grum, Marcus [1 ]
Gronau, Norbert [1 ]
机构
[1] Univ Potsdam, D-14482 Potsdam, Germany
来源
BUSINESS MODELING AND SOFTWARE DESIGN, BMSD 2017 | 2018年 / 309卷
关键词
Process modeling; Artificial Intelligence; Machine learning; Deep neuronal networks; Knowledge Modeling; Description Language; KMDL; Process simulation; Simulation process building; Process optimization; NEURAL-NETWORKS; SYSTEMS;
D O I
10.1007/978-3-319-78428-1_1
中图分类号
F [经济];
学科分类号
02 ;
摘要
Modern process optimization approaches do build on various qualitative and quantitative tools, but are mainly limited to simple relations in different process perspectives like cost, time or stock. In this paper, a new approach is presented which focuses on techniques of the area of Artificial Intelligence to capture complex relations within processes. Hence, a fundamental value increase is intended to be gained. Existing modeling techniques and languages serve as basic concepts and try to realize the junction of apparently contradictory approaches. This paper therefore draws a vision of promising future process optimization techniques and presents an innovative contribution.
引用
收藏
页码:1 / 24
页数:24
相关论文
共 39 条
[1]  
[Anonymous], 1985, What is Total Quality Control?
[2]  
[Anonymous], 1987, Technical Report CUED/F-INFENG/TR.1
[3]  
[Anonymous], 1939, Statistical Method from the Viewpoint of Quality Control
[4]  
Bishop C.M., 1995, Neural networks for pattern recognition
[5]  
Broomhead D. S., 1988, Complex Systems, V2, P321
[6]   A LIMITED MEMORY ALGORITHM FOR BOUND CONSTRAINED OPTIMIZATION [J].
BYRD, RH ;
LU, PH ;
NOCEDAL, J ;
ZHU, CY .
SIAM JOURNAL ON SCIENTIFIC COMPUTING, 1995, 16 (05) :1190-1208
[7]   Process optimization via neural network metamodeling [J].
Chambers, M ;
Mount-Campbell, CA .
INTERNATIONAL JOURNAL OF PRODUCTION ECONOMICS, 2002, 79 (02) :93-100
[8]  
Deming W., 1986, OUT CRISIS
[9]  
Deming W.E., 1993, NEW EC
[10]  
Deming W.E., 1950, ELEMENTARY PRINCIPLE