Joint optimization of production scheduling and machine group preventive maintenance

TY - JOUR

T1 - Joint optimization of production scheduling and machine group preventive maintenance

AU - Xiao, Lei

AU - Song, Sanling

AU - Chen, Xiaohui

AU - Coit, David W.

N1 - Publisher Copyright: © 2015 Published by Elsevier Ltd.

PY - 2016/2/1

Y1 - 2016/2/1

N2 - Joint optimization models were developed combining group preventive maintenance of a series system and production scheduling. In this paper, we propose a joint optimization model to minimize the total cost including production cost, preventive maintenance cost, minimal repair cost for unexpected failures and tardiness cost. The total cost depends on both the production process and the machine maintenance plan associated with reliability. For the problems addressed in this research, any machine unavailability leads to system downtime. Therefore, it is important to optimize the preventive maintenance of machines because their performance impacts the collective production processing associated with all machines. Too lengthy preventive maintenance intervals may be associated with low scheduled machine maintenance cost, but may incur expensive costs for unplanned failure due to low machine reliability. Alternatively, too frequent preventive maintenance activities may achieve the desired high reliability machines, but unacceptably high scheduled maintenance cost. Additionally, product scheduling plans affect tardiness and maintenance cost. Two results are obtained when solving the problem; the optimal group preventive maintenance interval for machines, and the assignment of each job, including the corresponding start time and completion time. To solve this non-deterministic polynomial-time problem, random keys genetic algorithms are used, and a numerical example is solved to illustrate the proposed model.

AB - Joint optimization models were developed combining group preventive maintenance of a series system and production scheduling. In this paper, we propose a joint optimization model to minimize the total cost including production cost, preventive maintenance cost, minimal repair cost for unexpected failures and tardiness cost. The total cost depends on both the production process and the machine maintenance plan associated with reliability. For the problems addressed in this research, any machine unavailability leads to system downtime. Therefore, it is important to optimize the preventive maintenance of machines because their performance impacts the collective production processing associated with all machines. Too lengthy preventive maintenance intervals may be associated with low scheduled machine maintenance cost, but may incur expensive costs for unplanned failure due to low machine reliability. Alternatively, too frequent preventive maintenance activities may achieve the desired high reliability machines, but unacceptably high scheduled maintenance cost. Additionally, product scheduling plans affect tardiness and maintenance cost. Two results are obtained when solving the problem; the optimal group preventive maintenance interval for machines, and the assignment of each job, including the corresponding start time and completion time. To solve this non-deterministic polynomial-time problem, random keys genetic algorithms are used, and a numerical example is solved to illustrate the proposed model.

KW - Genetic algorithms

KW - Preventive maintenance

KW - Random keys

KW - Scheduling

UR - https://www.scopus.com/pages/publications/84946615854

UR - https://www.scopus.com/pages/publications/84946615854#tab=citedBy

U2 - 10.1016/j.ress.2015.10.013

DO - 10.1016/j.ress.2015.10.013

M3 - Article

SN - 0951-8320

VL - 146

SP - 68

EP - 78

JO - Reliability Engineering and System Safety

JF - Reliability Engineering and System Safety

ER -