Scheduling jobs and maintenance activities on parallel machines

Lee, Chung Yee; Chen, Zhi Long

doi:10.1002/(sici)1520-6750(200003)47:2<145::aid-nav5>3.0.co;2-3

Cited by 182 publications

(38 citation statements)

References 25 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…There are alternative models which address the effect of machine maintenance: the maintenance activity may improve the processing rate of the machine; the maintenance activity may have to be completed before a given deadline; or the duration of the maintenance activity will increase if its start is delayed, etc. For further details, we refer to Lee and Chen (2000), Lee and Leon (2001) and Kubzin and Strusevich (2006).…”

Section: Scheduling With Machine Availability Constraintsmentioning

confidence: 99%

Fifty years of scheduling: a survey of milestones

Potts

Strusevich

2009

Journal of the Operational Research Society

174

View full text Add to dashboard Cite

Scheduling has become a major field within operational research with several hundred publications appearing each year. This paper explores the historical development of the subject since the mid 1950s when the landmark publications started to appear. A discussion of the main topics of scheduling research for the past five decades is provided, highlighting the key contributions that helped shape the subject. The main topics covered in the respective decades are combinatorial analysis, branch and bound, computational complexity and classification, approximate solution algorithms, and enhanced scheduling models.

show abstract

Section: Scheduling With Machine Availability Constraintsmentioning

confidence: 99%

Fifty years of scheduling: a survey of milestones

Potts

Strusevich

2009

Journal of the Operational Research Society

174

View full text Add to dashboard Cite

show abstract

“…Lee [19] studied the two-machine flow shop-scheduling problem under availability constraint and developed dynamic programming algorithm and heuristic solutions. Lee and Chen [20] considered in their parallel machines scheduling model that jobs can be maintained only one time during the planning horizon. They also assumed two strategies: machines can be maintained simultaneously or separately.…”

Section: -1 Integration Of Maintenance and General Production Problemsmentioning

confidence: 99%

Developing Simulation Based Optimization Mechanism for Novel Stochastic Reliability Centered Maintenance Problem

2017

View full text Add to dashboard Cite

This research investigates joint scheduling of maintenance and production planning. This novel integrated problem takes benefit of reliability-centered maintenance (RCM) for monitoring and managing maintenance function of a stochastic complex production-planning problem namely flexible job shop scheduling problem (FJSP). The developed RCM works based on stochastic shocking of machines during their process time. In fact, it implements condition based maintenance approach regulated according to stochastic reliability concept. Comparison of the system reliability with critical levels determines the failure statues of the machines. It activates two main types of reaction called preventive and corrective maintenance. Considering breakdown of the system between inspection intervals makes the proposed model more realistic. Moreover, maintenance activity times and their duration are considered stochastically. Because of the high complexity level for this joint system, simulation-based optimization (SBO) approach is proposed for solving the problem. This SBO searches the feasible area through genetic algorithm (GA) and biogeography based optimization (BBO) algorithm. Different test problems, statistical methods, novel visualizations are used to discuss the problem and the algorithm explicitly.

show abstract

“…With the controllable maintenance interval which is solved by the stochastic production scheduling model (either mathematical or simulated), the job sequence can be well arranged to avoid machine idleness so as to make full use of machine. In addition, this scheduling model will schedule multiple maintenance operations, but not schedule only one maintenance operation during the whole planning horizon [17,36]. 3.…”

Section: Development Of the Integrated Production Scheduling Modelmentioning

confidence: 99%

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

Pan

Liao

2011

Int J Adv Manuf Technol

View full text Add to dashboard Cite

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-machinebased 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.

show abstract

Scheduling jobs and maintenance activities on parallel machines

Cited by 182 publications

References 25 publications

Fifty years of scheduling: a survey of milestones

Fifty years of scheduling: a survey of milestones

Developing Simulation Based Optimization Mechanism for Novel Stochastic Reliability Centered Maintenance Problem

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

Contact Info

Product

Resources

About