NDLI: Soft computing framework for intelligent human–machine system design, simulation and optimization

Content Provider	Springer Nature Link
Author	Zha, X. F.
Copyright Year	2003
Abstract	This paper proposes a novel soft-computing framework for human–machine system design and simulation based on the hybrid intelligent system techniques. The complex human–machine system is described by human and machine parameters within a comprehensive model. Based on this model, procedures and algorithms for human–machine system design, economical/ergonomic evaluation, and optimization are discussed in an integrated CAD and soft-computing framework. With a combination of individual neural and fuzzy techniques, the neuro-fuzzy hybrid soft-computing scheme implements a fuzzy if-then rules block for human–machine system design, evaluation and optimization by a trainable neural fuzzy network architecture. For training and test purposes, assembly tasks are simulated and carried out on a self-built multi-adjustable laboratory workstation with a flexible motion measurement and analysis system. The trained neural fuzzy network system is able to predict the operator's postures and joint angles of motion associated with a range of workstation configurations. It can also be used for design/layout and adjustment of human assembly workstations. The developed system provides a unified, intelligent computational framework for human–machine system design and simulation. Case studies for workstation system design and simulation are provided to illustrate and validate the developed system.
Starting Page	184
Ending Page	198
Page Count	15
File Format	PDF
ISSN	14327643
Journal	Soft Computing
Volume Number	7
Issue Number	3
Language	English
Publisher	Springer-Verlag
Publisher Date	2003-01-01
Publisher Place	Berlin Heidelberg
Access Restriction	One Nation One Subscription (ONOS)
Content Type	Text
Resource Type	Article
Subject	Theoretical Computer Science Software Geometry and Topology

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