Dynamic optimisation of preventative and corrective maintenance schedules for a large scale urban drainage system

Chen, Yujie; Cowling, Peter I.; Polack, Fiona; Remde, Stephen; Mourdjis, Philip

doi:10.1016/j.ejor.2016.07.027

Cited by 35 publications

(17 citation statements)

References 44 publications

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“…The main feature of corrective maintenance is that the repairs are only taken after failure and no intervention is done before the machine fails (Chen, ). Break‐down maintenance (BM)…”

Section: Maintenance Strategy Selectionmentioning

confidence: 99%

Maintenance strategy selection with risky evaluations using RAHP

Seiti

Tagipour

Hafezalkotob

et al. 2017

Multi Criteria Decision Anal

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In recent years, maintenance, especially its preventive type, has been seen as an effective and considerable factor in improving the functions of machines. Maintenance plays a vital role in organizations by keeping and increasing the reliability, accessibility, the quality of products, risk mitigation, return improvement, and safety. An effective maintenance programme can be realized by implementing a proper maintenance strategy. Therefore, maintenance and its strategies have a special status in industries. However, selecting a proper maintenance strategy has always been a complex process because maintenance is a nonrepetitive task. Likewise, the lack of failure records and constant changes in the conditions of machines makes it further complicated. Hence, the decision‐making also depends on experts' opinions and because some kind of risk and uncertainty are always there in experts evaluations, the reliability of evaluations is questionable. The present study was aimed to develop a risk‐based model grounded on the analytical hierarchical process, namely, RAHP, to meet this need of maintenance. A case study from a steel rolling company was considered to evaluate the effectiveness of this model.

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“…The main feature of corrective maintenance is that the repairs are only taken after failure and no intervention is done before the machine fails (Chen, ). Break‐down maintenance (BM)…”

Section: Maintenance Strategy Selectionmentioning

confidence: 99%

Maintenance strategy selection with risky evaluations using RAHP

Seiti

Tagipour

Hafezalkotob

et al. 2017

Multi Criteria Decision Anal

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“…Camci (2015) and Irawan et al, (2017) accomplished this for geographically scattered assets assuming that only one maintenance team is available, and each asset can be handled only once during the planning horizon. In a similar work, Chen et al (2017) studied the integrated optimization of maintenance scheduling and staff routing for a drainage system with general network topology. Their goal was to minimize the flood risk of the whole system.…”

Section: Introductionmentioning

confidence: 99%

MILP of multitask scheduling of geographically distributed maintenance tasks

Allaham¹,

Dalalah²

2022

10.5267/j.ijiec

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Due to its proactive impact on the serviceability of components in a system, preventive maintenance plays an important role particularly in systems of geographically spread infrastructure such as utilities networks in commercial buildings. What makes such systems differ from the classical schemes is the routing and technicians' travel times. Besides, maintenance in commercial buildings is characterized by its short tasks’ durations and spatial distribution within and between different buildings, a class of problems that has not been suitably investigated. Although it is not trivial to assign particular duties solely to multi-skilled teams under limited time and capacity constraints, the problem becomes more challenging when travel routes, durations and service levels are considered during the execution of the daily maintenance tasks. To address this problem, we propose a Mixed Integer Linear Programming Model that considers the above settings. The model exact solution recommends collaborative choices that include the number of maintenance teams, the selected tasks, routes, tasks schedules, all detailed to days and teams. The model will reduce the cost of labor, replacement parts, penalties on service levels and travel time. The optimization model has been tested using different maintenance scenarios taken from a real maintenance provider in the UAE. Using CPLEX solver, the findings demonstrate an inspiring time utilization, schedules of minimal routing and high service levels using a minimum number of teams. Different travel speeds of diverse assortment of tasks, durations and cost settings have been tested for further sensitivity analysis.

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“…Therefore, municipalities regularly clean out gully pots. This is done once or twice a year in urban areas [9,10] and two to four times a year at vulnerable locations, such as market places or shopping areas [9].…”

Section: Introductionmentioning

confidence: 99%

Sediment Morphology and the Flow Velocity Field in a Gully Pot: An Experimental Study

Rietveld

Rijke

Langeveld

et al. 2020

Water

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Urban runoff (re)mobilises solids present on the street surface and transport them to urban drainage systems. The solids reduce the hydraulic capacity of the drainage system due to sedimentation and on the quality of receiving water bodies due to discharges via outfalls and combined sewer overflows (CSOs) of solids and associated pollutants. To reduce these impacts, gully pots, the entry points of the drainage system, are typically equipped with a sand trap, which acts as a small settling tank to remove suspended solids. This study presents data obtained using Particle Image Velocimetry (PIV) and Laser Doppler Anemometry (LDA) measurements in a scale 1:1 gully to quantify the relation between parameters such as the gully pot geometry, discharge, sand trap depth, and sediment bed level on the flow field and subsequently the settling and erosion processes. The results show that the dynamics of the morphology of the sediment bed influences the flow pattern and the removal efficiency in a significant manner, prohibiting the conceptualization of a gully pot as a completely mixed reactor. Resuspension is initiated by the combination of both high turbulent fluctuations and high mean flow, which is present when a substantial bed level is present. In case of low bed levels, the overlaying water protects the sediment bed from erosion.

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Dynamic optimisation of preventative and corrective maintenance schedules for a large scale urban drainage system

Cited by 35 publications

References 44 publications

Maintenance strategy selection with risky evaluations using RAHP

Maintenance strategy selection with risky evaluations using RAHP

MILP of multitask scheduling of geographically distributed maintenance tasks

Sediment Morphology and the Flow Velocity Field in a Gully Pot: An Experimental Study

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