Study of dynamic workload assignment strategies on production performance * *Acknowledgments to financial support of Cambridge Trust and China Scholarship Council-Reference-Cited by-同舟云学术

Study of dynamic workload assignment strategies on production performance * *Acknowledgments to financial support of Cambridge Trust and China Scholarship Council

Published:2017-07 Issue:1 Volume:50 Page:13710-13715
ISSN:2405-8963
Container-title:IFAC-PapersOnLine
language:en
Short-container-title:IFAC-PapersOnLine

Author:

Li H.,Parlikad A.K.

Publisher

Elsevier BV

Subject

Control and Systems Engineering

Reference19 articles.

1. Optimal joint maintenance and operation policies to maximise overall systems effectiveness;AlDurgam;International Journal of Production Research,2012

2. Multi-agent based joint production and maintenance scheduling considering human resources;Bouzidi-Hassini;2013 5th International Conference on Modeling, Simulation and Applied Optimization, ICMSAO,2013

3. Integrated Maintenance Decision-Making and Product Sequencing in Flexible Manufacturing Systems. accepted for publication in the ASME;Celen;Journal of Manufacturing Science and Engineering, 137(August,2016

4. Operation-dependent maintenance scheduling in flexible manufacturing systems;Celen;CIRP Journal of Manufacturing Science and Technology,2012

5. Agents-based design for fault management systems in industrial processes;Cerrada;Computers in Industry,2007

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