Artificial Neural Networks in Manufacturing: Concepts, Applications, and Perspectives

Samuel H. Huang, Hong Chao Zhang

Research output: Contribution to journalArticlepeer-review

46 Scopus citations


New approaches and techniques are continuously and rapidly introduced and adopted in today’s manufacturing environment. Recently, there is an explosion of interest in applying artificial neural networks to manufacturing. Artificial neural networks have several advantages that are desired in manufacturing practice, including learning and adapting ability, parallel distributed computation, robustness, etc. There is an expectation that neural network techniques can lead to the realization of truly intelligent manufacturing systems. This paper introduces the basic concepts of neural networks and reviews the current application of neural networks in manufacturing. The problems with neural networks are also identified and some possible solutions are suggested. We hope that the material presented in this paper can provide useful guidelines and references for the research and implementation of artificial neural networks in the field of manufacturing.

Original languageEnglish
Pages (from-to)212-228
Number of pages17
JournalIEEE Transactions on Components Packaging and Manufacturing Technology Part A
Issue number2
StatePublished - Jun 1994


Dive into the research topics of 'Artificial Neural Networks in Manufacturing: Concepts, Applications, and Perspectives'. Together they form a unique fingerprint.

Cite this