This paper describes several prototypical applications of neural network technology to engineering problems. The applications were developed by the authors as part of a graduate-level course taught at the University of Illinois at Urbana-Champaign by the first author (now at Carnegie Mellon University). The applications are: an adaptive controller for building thermal mass storage; an adaptive controller for a combine harvester; an interpretation system for non-destructive evaluation of masonry walls; a machining feature recognition system for use in process planning; an image classification system for classifying land coverage from satellite or high-altitude images; and a system for designing the pumping strategy for contaminated groundwater remediation. These applications are representative of many of the engineering problems for which neural networks are applicable: adaptive control, feature recognition, and design.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
References
BLAST (1990) Building Loads Analysis and System Thermodynamics (BLAST) Users Manual, Version 3.0, Blast Support Office, University of Illinois.
Bungey, J. H. (1989) The Testing of Concrete in Structures, Surrey University Press.
Choi, B. K., Barash, M. M. and Anderson, D. C. (1984) Automatic recognition of machined surfaces from a 3D solid model, Computer-Aided Design, 16, 81–86.
Chryssolouris, G. and Domroese, M. (1988) Sensor integration for tool wear estimation in machining, in Proceedings of the ASME Winter Annual Meeting, 1988: Sensors and Controls for Manufacturing, pp. 115–123.
De Floriani, L. (1987) A graph based approach to object feature recognition, in Proceedings of the Third Annual Symposium on Computational Geometry, ACM, pp. 100–109.
Epperson, G. S. and Abrams, D. P. (1989) Nondestructive evaluation of masonry buildings, ACTC Report No. 89-26-03, Department of Civil Engineering, UIUC, October.
Gorelick, S. M. (1983) A review of distributed parameter groundwater management modeling methods, Water Resources Research, 19(2), 305–319.
Gorelick, S. M. (1988) Incorporating assurance into groundwater quality management models, in Groundwater Flow and Quality Modeling, Proceedings of the NATO Advanced Research Workshop on Advances in Analytical and Numerical Groundwater Flow and Quality Modeling, Custodio, E., Gurgui, A. and Lobo Ferreira, J. P. (eds), pp. 135–150, D. Reidel, Hingham, Mass.
Hinton, G. E., Sejnowski, T. J. and Ackley, D. H. (1984) Boltzmann machines: constraint satisfaction networks that learn, Tech. Rep. No. CMU-CS-84–119, Department of Computer Science, Carnegie Mellon University, Pittsburgh, PA.
Hopfield, J. J. and Tank, D. W. (1985) Neural computation of decisions in optimization problems, Biological Cybernetics, 52, 141–152.
Kingsley, G. R. and Noland, J. L. (1987) An overview of nondestructive techniques for evaluating structural properties of brick masonry, Evaluation and Retrofit of Masonry Structures, Joint US-Italy Workshop, August.
Li, R. K. (1988) A part-feature recognition system for rotational parts, International Journal of Production Research, 26(9), 1451–1475.
McGonnagle, W. J. (1961) Nondestructive Testing, McGraw-Hill.
Mehta, S. and Fulop, L. (1990) A neural algorithm to solve the Hamiltonian cycle problem, in Proceedings of the International Joint Conference on Neural Networks, Vol. III, pp. 843–849.
Nguyen, D. and Widrow, B. (1989) The truck backer-upper: an example of self-learning in neural networks, in Proceedings of IJCNN International Conference on Neural Networks, Vol. II, pp. 357–363.
Poliac, M. O., Lee, E. B., Slagle, J. R. and Wick, M. R. (1987) A crew scheduling problem, in Proceedings of the International Joint Conference of Neural Networks, Vol. IV, pp. 779–786.
Quick, G. R. and Buchele, W. F. (1978) The grain harvesters, American Society of Mechanical Engineers, 258.
Rumelhart, D. E. and McClelland, J. L. (eds) (1986) Parallel Distributed Processing, Volume 1, Chapter 8, The MIT Press, Cambridge, MA.
Snyder, M. E. (1990) Cooling cost reduction using building mass for thermal storage, Unpublished Master of Science Thesis, University of Illinois.
Sohn, C. W. and Cler, G. L. (1989) Market potential of storage cooling systems in the Army, Technical Report E-89/13, USACERL.
Staley, S. M., Henderson, M. R. and Anderson, D. C. (1983) Using syntactic pattern recognition to extract feature information from a solid geometric data base, Computers in Mechanical Engineering, 61–66.
Widrow, B. and Stearns, S. D. (1985) Adaptive Signal Processing, Chapter 6, Prentice Hall, Inc.
Wong, W. S. and Funka-Lea, C. A. (1990) An elastic net solution to obstacle avoidance planning, in Proceedings of the International Joint Conference on Neural Networks, Vol. III, pp. 799–804.
Woo, T. C. (1982) Feature extraction by volume decomposition, Technical report No. 82–4, Department of Industrial and Operations Engineering, The University of Michigan, Ann Arbor, Michigan.
Yerramareddy, S., Lu, S. C.-Y. and Arnold, K. F. (1993) Developing empirical models from observational data using artificial neural networks, Journal of Intelligent Manufacturing (this issue).
Zhou, D. N., Cherkassky, V., Baldwin, T. R. and Hong, D. W. (1990) Scaling neural network for job-shop scheduling, in Proceedings of the International Joint Conference on Neural Networks, Vol. III, pp. 889–894.
Author information
Authors and Affiliations
Rights and permissions
About this article
Cite this article
Garrett, J.H., Case, M.P., Hall, J.W. et al. Engineering applications of neural networks. J Intell Manuf 4, 1–21 (1993). https://doi.org/10.1007/BF00124977
Issue Date:
DOI: https://doi.org/10.1007/BF00124977