Supporting Maintenance Scheduling: A Case Study

Senra, Patrícia Arantes; Lopes, Isabel da Silva; Oliveira, José A.

doi:10.1016/j.promfg.2017.07.342

Cited by 14 publications

(8 citation statements)

References 6 publications

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“…The paint peel off issue was the main warranty issue, which lowers the assembly line efficiency; the paint peel off during the transportation for one unit to the modifying the storage and transport racks. Preventive Maintenance [7].…”

Section: Resultsmentioning

confidence: 99%

Paint Peel Off - A Nuisance in Automotive Propeller Shaft Assembly

Khandare¹,

Tjprc²

2018

IJMPERD

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Manufacturing an automotive propeller shaft is really a challenging process. The propeller shaft consists of many sub components known as sub-assemblies. The sub components like Stub yoke, Flange Yoke, Sleeve Yoke, Tube, Split Spline Shaft, Mid Slip Shaft, Bearing Cup, Cross etc. As the propeller shaft is located beneath the Automobile, a little attention is given towards its aesthetic appearance. The propeller shaft is coated and painted with paint and phosphate, which is mostly carried out in the paint booth [3]. The main reason is to reduce the warranty issues and enhance the life of it and also to avoid premature failure during when the propeller shaft is in operation.

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Section: Resultsmentioning

confidence: 99%

Paint Peel Off - A Nuisance in Automotive Propeller Shaft Assembly

Khandare¹,

Tjprc²

2018

IJMPERD

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“…The goal is to find a schedule that is optimal for any realization of the uncertainty in a given set. In practice, this is equivalent to minimizing the deviation from the optimal solution in the worst-case scenario [21].…”

Section: Literature Reviewmentioning

confidence: 99%

Robust Maintenance Scheduling of Aircraft Fleet: A Hybrid Simulation-Optimization Approach

2021

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We study the maintenance task scheduling problem for an aircraft fleet in an uncertain environment from the viewpoint of robust optimization. Given a daily horizon, the maintenance tasks delegated to a shop should be scheduled in such a way that sufficient aircrafts are available on time to meet the demand of planned missions. The tasks are either scheduled maintenance activities or unexpected repair jobs when a major fault is detected during pre-or after-flight check of each mission. The availability of skilled labour in the shop is the main constraint. We propose a robust formulation so that the maintenance tasks duration is subject to unstructured uncertainty due to the environmental and human factors. As a result of the specific structure of the primary model and non-convexity of the feasible space, the classical robust optimization methods cannot be applied. Thus, we propose an ϵ-Conservative model in tandem with Monte-Carlo sampling to extract the set of all feasible solutions corresponding to various disturbance vectors. Since the one-way sampling-thenoptimization approach does not guarantee the probabilistic feasibility, we employ a hybrid simulationoptimization approach to ensure that the solutions provided by the ϵ-Conservative model are robust to all uncertainty scenarios. The experimental results confirm the scalability of the proposed methodology by generating the robust optimal solutions, satisfying all conservatism levels and uncertainty scenarios irrespective of the problem size.

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“…In another model, Hadidi et al [9] studied the practical effects of management decisions to integrate the maintenance operations with scheduling of production. Their objective is minimizing holding costs of the selected product while optimizing the maintenance costs.…”

Section: Related Workmentioning

confidence: 99%

“…is calculated as follows: Equations 7and (8) are used to determine the operation time of the first job and the other jobs on the first machine, while equations (9) and (10) are used to find the operation time of the first job and the other jobs on the other machines, respectively. PM factor ( − ) in the above equations can take a value either '1' or '0' depending on machine drives for PM or not.…”

Section: Expected Total Production Cost Model (Etpcm)mentioning

confidence: 99%

Model for Integrating Production Scheduling and Maintenance Planning of Flow Shop Production System

et al. 2020

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In this paper, a model for integrating production scheduling and maintenance planning is proposed for flow shop production system. The suggested model in this paper is based on the optimal jobs sequence for jobs that will be processed in multiple machines connected in series. The objective of this study is to find the optimal sequence for jobs while reducing the total production and maintenance costs. The model works by generating an initial solution using longest processing time (LPT) dispatching rule. Then, tabu search algorithm is established to obtain the optimal sequence for jobs. Computational experiments are performed on problems with five serially machines which are assigned to process eight diverse jobs from the same product family. The result is compared with the genetic algorithm optimization technique under individual PM scheme for obtaining superior solutions that has been proved in the literature to be one of the best approach. The computational results show that the recommended approach is qualified over the simulation based genetic algorithm optimization technique. INDEX TERMS Integrated model, Job scheduling, Maintenance planning, Tabu search algorithm.

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Supporting Maintenance Scheduling: A Case Study

Cited by 14 publications

References 6 publications

Paint Peel Off - A Nuisance in Automotive Propeller Shaft Assembly

Paint Peel Off - A Nuisance in Automotive Propeller Shaft Assembly

Robust Maintenance Scheduling of Aircraft Fleet: A Hybrid Simulation-Optimization Approach

Model for Integrating Production Scheduling and Maintenance Planning of Flow Shop Production System

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