A two-stage coupled algorithm for an integrated maintenance planning and flowshop scheduling problem with deteriorating machines

Abstract

We address a novel integrated maintenance and production scheduling problem in a multi-machine and multi-period production system, considering maintenance as a long-term decision. Deterioration of machines over time decreases production capacity. Since maintenance activities not only improve machine conditions, increasing production capacity, but also take time that cannot be used for production, the challenge is to assign maintenance to periods and to schedule maintenance and production activities within each period to minimize the combined cost of maintenance and lost production over the planning horizon. Motivated by logic-based Benders decomposition, we design an integrated two-stage algorithm to solve the problem. The first stage assigns maintenance to machines and time periods, abstracting the scheduling problem, while the second stage creates a schedule for the current time period. The first stage is then re-solved using feedback from the schedule. This iteration between maintenance planning and scheduling continues until the solution costs in two stages converge. The integrated approach models the interdependencies between maintenance and scheduling decisions in highly coupled processes such as wafer fabrication in the semiconductor manufacturing. Our results demonstrate that the benefit of integrated decision making increases when maintenance is less expensive relative to lost production cost and that a longer horizon for maintenance planning is beneficial when maintenance cost increases.

Production, maintenance and resource scheduling: A review

“…In the third stage, goal programming is applied and the optimal positions and the frequencies of the maintenance activities are determined. Simultaneous consideration of deteriorating jobs and resource constraints is also addressed for the flow shop environment in the study by Aramon Bajestani & Beck (2015) . A finite planning horizon is considered, which is composed of K discrete time periods, each T time units long.…”

Logic-Based Benders Decomposition for Large-Scale Optimization

“…k ← 0, feasible ← false; repeat if master problem ( 5) is infeasible then stop; original problem (2) is infeasible; end let x k be an optimal solution of ( 5) with value z k ; solve subproblem (7)…”

“…LBBD applications to shop and factory scheduling include aircraft repair shop scheduling [6], job shop scheduling with human resurce constraints [51], permutation flowshop scheduling with time lags [52,53], one-machine scheduling problems [22,104,105], and flowshop planning and scheduling with deteriorating machines [7]. There is also an application to feature-based assembly planning [71].…”

A mixed-integer linear programming model for integrated production and preventive maintenance scheduling in the capital goods industry

“…the subassemblies/components must be available for an assembly process to take place. Bajestani and Beck (2015) / / / / Hadidi et al (2015) / / / Hedjazi (2015) / / / Nie, Xu, and Tu (2015) / / Qi, Wan, and Yan (2015) / Von Hoyningen-Huene and Kiesmuller (2015 The objective of this work was to find an optimal schedule which minimised total costs (including penalty costs caused by tardiness and earliness, holding costs due to work-in-process and costs due to assembly, setup, production, transfer, production idle time and maintenance).…”