NDLI: A joint model of production scheduling and predictive maintenance for minimizing job tardiness

Content Provider	Springer Nature Link
Author	Pan, Ershun Liao, Wenzhu Xi, Lifeng
Copyright Year	2011
Abstract	As increasingly diverse tasks are being processed on single multi-functional machine, production scheduling has become a critical issue in the planning and management of manufacturing processes. However, the majority of production scheduling literature ignores machine availability and assumes that machine is available all the time. In reality, machines physically deteriorate with increased usage and time. Thus, there is an intense need for manufacturing industries to reduce unexpected breakdowns and remain competitive, and motivating maintenance operations should be integrated into production scheduling models. With the advancements in sensor and prognostic technologies, machine’s condition can be monitored and assessed over time through conducting predictive maintenance. Hence, based on this scheme, this study proposes a single-machine-based scheduling model incorporating production scheduling and predictive maintenance. A machine’s effective age and remaining maintenance life are introduced to describe machine degradation. Finally, a numerical example is given; the computational results show that this integrated scheduling model has better performance than those existing models, which proves its efficiency.
Starting Page	1049
Ending Page	1061
Page Count	13
File Format	PDF
ISSN	02683768
Journal	The International Journal of Advanced Manufacturing Technology
Volume Number	60
Issue Number	9-12
e-ISSN	14333015
Language	English
Publisher	Springer-Verlag
Publisher Date	2011-10-04
Publisher Place	London
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Production scheduling Predictive maintenance Health index (HI) Effective age Remaining maintenance life (RML) Tardiness Mechanical Engineering Computer-Aided Engineering (CAD, CAE) and Design Production/Logistics/Supply Chain Industrial and Production Engineering
Content Type	Text
Resource Type	Article
Subject	Industrial and Manufacturing Engineering Control and Systems Engineering Mechanical Engineering Computer Science Applications Software

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