A Joint Optimization of Strategic Workforce Planning and Preventive Maintenance Scheduling: A Simulation–Optimization Approach

Akl, Amany M.; Sawah, Sondoss El; Chakrabortty, Ripon K.; Turan, Hasan Hüseyin

doi:10.1016/j.ress.2021.108175

Cited by 20 publications

(15 citation statements)

References 35 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Furthermore, methods of evolutionary algorithms, clustering method [25] and/ or linear programming [5] are used to plan and schedule maintenance and reduce its costs. Using a digital twin improves the visibility of problems in this process well in the article [17].…”

Section: Methodsmentioning

confidence: 99%

“…There is more interest in a production than in maintenance the text [4] notes. It is necessary to address unplanned maintenance also due to the availability of staff as in the text [25]. A major problem for many organisations is a lack of strategic maintenance planning and overall integration of the maintenance into the strategy of organisations according to the article [23].…”

Section: Problems Of Areamentioning

confidence: 99%

See 1 more Smart Citation

The Maintenance Management

Pelantová¹

2023

Maintenance Management - Current Challenges, New Developments, and Future Directions

View full text Add to dashboard Cite

The chapter deals with the maintenance management. The review is based on maintenance and management trends in organisations in 2022 and on other findings. There are also historical parallels. Aspects such as maintenance planning and control and management including downtime, resources in terms as material (spare parts and added materials) and personnel are discussed. The issue is linked to other management systems such as quality control, occupational safety, and environment and information security. The methods of planning and control of equipment maintenance are presented. The application of the process approach and the concept of maintenance as a process that needs to be improved are described. The relationship to the Industry 4.0 is mentioned. Linking to risk management is included in this chapter. The chapter is based on a small survey probe in several organisations, and points out identified nonconformities of the maintenance and suggested actions. The goal is effective maintenance for needs of organisations in a current dynamic environment.

show abstract

Section: Methodsmentioning

confidence: 99%

Section: Problems Of Areamentioning

confidence: 99%

The Maintenance Management

Pelantová¹

2023

Maintenance Management - Current Challenges, New Developments, and Future Directions

View full text Add to dashboard Cite

show abstract

“…According to the ISO 14,224 standard, maintenance is the set of technical and administrative actions oriented toward keeping or restoring an item so it can fulfil a required function (ISO 2016 ). Al-Najjar and Alsyouf ( 2003 ), Alsyouf ( 2007 ), Velmurugan and Dhingra ( 2015 ), Liu et al ( 2021 ), Akl et al ( 2022 ), among other researchers, highlighted that industrial maintenance studies increased over the past decades, contributing to maintain equipment integrity, reducing costs and guaranteeing overall availability by preventing failures, as well as improving product quality, operational performance, and people safety.…”

Section: Literature Reviewmentioning

confidence: 99%

“…Planning preventive maintenance includes definition of intervention frequency and intervals, workforce and resource coordination, and part replacement management (Mena et al 2021 ). This is not a simple task, as the balance between reliability and maintenance cost must be considered (Lie and Chun 1986 ; Akl et al 2022 ; Kunz 2022 ; de Silva et al 2022 ). Shortening the maintenance interval and replacing parts before the end of service life impact the overall cost, due to the cumulative mean time to repair preventively (MTTR p ) and downtime cost (CHC) plus part cost (CC n ), while the postponement of maintenance interventions increases the mean time to repair correctively (MTTR c ), and higher failure rates are expected, due to reliability depletion, as shown in Fig.…”

Section: Literature Reviewmentioning

confidence: 99%

Straightening machine preventive maintenance intervention plan based on AHP: a case study in a steel company in Brazil

et al. 2023

View full text Add to dashboard Cite

Equipment failure and production shortfalls can cause significant impacts on companies. Preventive maintenance can potentially increase equipment reliability and availability, helping companies achieve their corporate goals while reducing operation and maintenance costs. However, determining the optimal interval between maintenance interventions involves balancing various factors such as maintenance costs, equipment availability, risk of failures, and the need for corrective maintenance, as well as potential operational and financial impacts. Under this context, this paper aims to define the interval between preventive maintenance interventions for a key production equipment in a steel company located in Southeast region of Brazil. Upon documental analysis and interviews with experts, an AHP was applied to hierarchize the maintenance periodicity, based on the following criteria: part replacement based on service life, downtime hours for preventive maintenance, equipment reliability, and cost of materials and labour. A biweekly preventive maintenance periodicity was identified as the most adequate for the analysed device. An implementation plan was approved and preliminary results indicate no availability deterioration, while maintenance costs are below historical average.

show abstract

“…Alimian et al [20] investigated parallel-line capacitated lot sizing and scheduling problems by incorporating sequence-dependent setup time and cost and the preventive maintenance schedule. Akl et al [21] have studied a maintenance study that accounts for production resources. In this study, a high-value asset maintenance system was modelled using a novel largescale discrete event simulation model and simulated by incorporating multiple aspects, including asset acquisitions, maintenance workforce planning, and preventive maintenance activity scheduling.…”

Section: Introductionmentioning

confidence: 99%

Incorporating deep learning data analytics techniques in the optimisation of capacitated planned maintenance

Purnomo

2022

j. sist. manaj. ind.

View full text Add to dashboard Cite

Manufacturing systems must be supported by the availability of materials, a streamlined production process and a prepared production line to achieve the production target. In a mass customization manufacturing system, the number of machines required for customization is relatively small. Conse-quently, maintenance on critical machines will impact this manufacturing system the most. Two types of maintenance strategies are implemented: corrective and preventive maintenance. The corrective maintenance requires more resources since the time and cost to repair the breakdown machine will be higher due to fatal failure. For the management to consider preventive maintenance while the binding machines are still operational, it must be equipped with a deep analysis demonstrating that fewer resources will be required. This paper discusses two deep analyses: accurate prediction of the binding machines' breakdown based on Mean Time Between Failure (MTBF) data using a deep learning data analytics technique and optimizing the maintenance total cost in the available capacitated time. The findings and results of this paper show that the proposed deep learning data analytics technique can increase the MTBF prediction accuracy by up to 66.12% and reduce the total maintenance cost by up to 4% compared with the original model.

show abstract

A Joint Optimization of Strategic Workforce Planning and Preventive Maintenance Scheduling: A Simulation–Optimization Approach

Cited by 20 publications

References 35 publications

The Maintenance Management

The Maintenance Management

Straightening machine preventive maintenance intervention plan based on AHP: a case study in a steel company in Brazil

Incorporating deep learning data analytics techniques in the optimisation of capacitated planned maintenance

Contact Info

Product

Resources

About