Integrated maintenance/spare parts management for manufacturing system according to variable production rate impacting the system degradation

2020 ◽  
Vol 28 (1) ◽  
pp. 72-84 ◽  
Author(s):  
Sofiene Dellagi ◽  
Wajdi Trabelsi ◽  
Zied Hajej ◽  
Nidhal Rezg
Keyword(s):  
Production Rate ◽  
Preventive Maintenance ◽  
Manufacturing System ◽  
Planning Horizon ◽  
Sensitivity Study ◽  
Spare Parts ◽  
Rate Variation ◽  
Maintenance Strategy ◽  
Spare Parts Management ◽  
The Impact

This study develops an analytical model in order to determine an optimal integrated maintenance plan and spare parts management. We consider a manufacturing system, producing only one type of product, over a finite planning horizon H equal to the sum of all production periods and the production quantity of each period is known. This system is subject to a continuously increasing degradation rate. That is why a preventive maintenance strategy is adopted in order to face the increasing failure rate. We noted that contrarily to the majority of studies in literature, we take into account the impact of the production rate variation on the manufacturing system degradation and consequently on the adopted optimal maintenance strategy. In addition, the real need of spare parts relative to the scheduled maintenance actions is taken into account. In fact, the purpose of our study consists at determining the optimal preventive maintenance frequency and the optimal quantity of spare parts to order by minimizing a total cost, including maintenance and spare parts management. Numerical examples are presented along with a sensitivity study in order to prove the use of the developed model for deriving the optimal integrated strategy for any instance of the problem.

Preventive Maintenance and Spare Parts Management Optimization in Natural Gas Pipelines Operating Under Variable Conditions Across the Year

2015 ◽  
Author(s):  
Elisa Carlucci ◽  
Leonardo Tognarelli
Keyword(s):  
Gas Turbines ◽  
Block Diagram ◽  
Sensitivity Study ◽  
Spare Parts ◽  
Pipeline Architecture ◽  
Gas Generator ◽  
Natural Gas Pipelines ◽  
Spare Parts Management ◽  
The Impact ◽  
Very High

Pipeline architecture consists in several stations in series configuration; hence the unavailability of one station impacts the availability of the whole pipeline. This lead to the need of optimizing the availability of each station in terms of configuration and number of units required in order to be able of satisfying the demand at any time. The loss of production cost in gas supply application is very high. Aero-derivatives gas Turbines are typically used as drivers in pipeline applications since they maximize train efficiency, minimizing gas consumption. PGT25+ aero-derivative Gas Turbines are among the most popular units applied in pipeline services. They merge demonstrated reliability performances together with a very limited outage duration impact that leads to very high Availability. Outage duration is optimized through modular replacement of both GG and HSPT that is facilitated by light weight of the machine. A Reliability Block Diagram has been built with the aim to optimize the Pipeline PGT25+ Gas Generator scheduled maintenance. Each block represents a Gas Generator while each station is realized taking into account the actual k-out-of-N configuration of each station units. Once the model has been created, a sensitivity analysis has been performed in order to estimate the impact of the Gas Generator cycle time (Gas Generator refurbishment time),that is what if larger or shorter than the baseline 6 months. Further, even a sensitivity study has been carried on to estimate the impact of the number of available spare parts on the delay that some units will suffer due to un-sufficient number of GG spare with consequent higher risk.

Optimal maintenance strategies for repairable systems with general degree of repair

1991 ◽  
Vol 28 (02) ◽  
pp. 384-396 ◽  
Author(s):  
Wolfgang Stadje ◽  
Dror Zuckerman
Keyword(s):  
Optimal Policy ◽  
Planning Horizon ◽  
Spare Parts ◽  
Inventory Systems ◽  
Maintenance Strategy ◽  
Repairable Systems ◽  
Discounted Cost ◽  
Wide Range ◽  
Optimal Maintenance ◽  
New Research

In this study we examine repairable systems with random lifetime. Upon failure, a maintenance action, specifying the degree of repair, is taken by a controller. The objective is to determine an age-dependent maintenance strategy which minimizes the total expected discounted cost over an infinite planning horizon. Using several properties of the optimal policy which are derived in this study, we propose analytical and numerical methods for determining the optimal maintenance strategy. In order to obtain a better insight regarding the structure and nature of the optimal policy and to illustrate computational procedures, a numerical example is analysed. The proposed maintenance model outlines a new research channel in the area of reliability with interesting theoretical issues and a wide range of potential applications in various fields such as product design, inventory systems for spare parts, and management of maintenance crews.

scholarly journals Preventive Maintenance Topic Models for LNG Containment Systems of LNG Marine Carriers Using Dock Specifications

2019 ◽  
Author(s):  
Ik-Hyun Youn ◽  
Sung-Cheol Kim
Keyword(s):  
Language Processing ◽  
Preventive Maintenance ◽  
Low Temperatures ◽  
Spare Parts ◽  
Liquefied Natural Gas ◽  
Maintenance Strategy ◽  
High Demand ◽  
Containment System ◽  
System Maintenance ◽  
Processing Techniques

The high demand for liquefied natural gas (LNG) requires more LNG carriers (LNGCs) to be in operation. During transportation, there is a high risk due to the required extremely low temperatures and the explosive nature of LNG cargo. Moreover, when there is a lack of experience in operating old LNGCs, there is a serious concern regarding operational accidents. A systematic maintenance strategy, especially for LNG cargo containment systems, is crucial for maintaining safe LNG transportation at sea. The purpose of this study is to develop preventive LNG cargo containment system maintenance models by using LNGC dock specifications from LNGCs of various ages. The dock specifications from a conventional LNGC repairing dock were analyzed using natural language processing techniques in order to develop preventive maintenance models of the LNG cargo containment system. From these results, and by considering the ship’s age, it was found that for young LNGCs the priority for repair should focus on checking routine consumable spare parts by tank inspections, whereas for older LNGCs the focus should be on tank condition maintenance rather than on other facilities. These results are expected to be useful in the development of a maintenance strategy of preventive LNG cargo containment systems in maritime LNG transportation.

scholarly journals Age-dependent production and replacement strategies in failure-prone manufacturing systems

2016 ◽  
Vol 231 (3) ◽  
pp. 540-554 ◽  
Author(s):  
Samir Ouaret ◽  
Jean-Pierre Kenné ◽  
Ali Gharbi ◽  
Vladimir Polotski
Keyword(s):  
Numerical Methods ◽  
Production Rate ◽  
Manufacturing Systems ◽  
Planning Horizon ◽  
Replacement Policy ◽  
Control Policies ◽  
Bellman Equations ◽  
Machine Failure ◽  
The Impact ◽  
Imperfect Repairs

A failure-prone manufacturing system that consists of one machine producing one type of product is studied. The random phenomena examined are machine breakdowns and repairs. We assume that the machine undergoes a progressive deterioration while in operation and that the machine failure rate is a function of its age. The aging of the machine (the dynamics of the machine age) is assumed to be an increasing function of its production rate. Corrective maintenance activities are imperfect and restore the age of the machine to as-bad-as-old conditions. When a failure occurs, the machine can be repaired, and during production, the machine can be replaced, depending on its age. When the replacement action is selected, the machine is replaced by a new and identical one. The decision variables are the production rate and the replacement policy. The objective of this article is to address the simultaneous production and replacement policy optimization problem in the context of manufacturing with deterioration and imperfect repairs satisfying the customer demand and minimizing the total cost, which includes costs associated with inventory, backlog, production, repair and replacement, over an infinite planning horizon. We thoroughly explore the impact of the machine aging on the production and replacement policies. Particular attention is paid to the verification of underlying mathematical results that guarantee the existence of optimal solutions and the convergence of numerical methods. Due to imperfect repairs, the dynamics of the system is affected by the system history, and semi-Markov processes have to be used for modeling. Optimality conditions in the form of the Hamilton–Jacobi–Bellman equations are developed, and numerical methods are used to obtain the optimal control policies (production (rate) and replacement policies). A numerical example is given to illustrate the proposed approach, and an extensive sensitivity analysis is presented to confirm the structure of the obtained control policies.

Analytical evaluation of TPM performance based on an economic criterion

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Kenza Chaabane ◽  
Jérémie Schutz ◽  
Sofiene Dellagi ◽  
Wajdi Trabelsi
Keyword(s):  
Preventive Maintenance ◽  
Sensitivity Study ◽  
Analytical Models ◽  
Total Productive Maintenance ◽  
Economic Criterion ◽  
Content Type ◽  
Decision Variables ◽  
Manufacturing Performance ◽  
The Impact ◽  
A Company

PurposeTotal productive maintenance (TPM) has been widely recognized as a strategic weapon for improving manufacturing performance. Evaluate efficiency of TPM implementation is considered as a key element in order to motivate staff and to give decision-makers more confidence.Design/methodology/approachThis study consists in developing a new method of evaluating TPM implementation, relying on analytical models and considering two preventive maintenance strategies: periodic and age-dependent.FindingsThe preventive maintenance period and TPM period defined as decision variables are obtained simultaneously by maximizing the expected profit under TPM implementation. A numerical example is presented and a sensitivity study is developed to validate the proposed models.Originality/valueThe aim of this research is to quantify, through analytic development, the impact of TPM implementation in a company by calculating and comparing the profit made with and without TPM.

Bayesian degradation modelling for spare parts inventory management

2020 ◽  
Vol 32 (1) ◽  
pp. 31-49 ◽  
Author(s):  
Cesar Ruiz ◽  
Edward Pohl ◽  
Haitao Liao
Keyword(s):  
Inventory Management ◽  
Optimal Solution ◽  
Planning Horizon ◽  
Degradation Process ◽  
Spare Parts ◽  
Optimal Time ◽  
Model Parameters ◽  
Stochastic Dynamic ◽  
Spare Parts Management ◽  
Spare Parts Inventory

Abstract Decision makers in various sectors, such as manufacturing and transportation, strive to minimize downtime costs. Often, brief-planned stoppage times allow for changes in shifts and line configurations and longer periods are scheduled for major repairs. It is quite important to proactively make use of these downtimes to reduce the costs of unexpected downtimes due to failures. Among many aspects, the availability of spare parts significantly affects the operational costs of such systems. Current sensor technologies enable the condition monitoring of critical components and degradation-based spare parts management. This paper focuses on Bayesian degradation modelling for spare parts inventory management for a new system. We propose a stochastic dynamic program to minimize the expected spare parts inventory cost for a fixed planning horizon. A numerical example illustrates the value of Bayesian analysis in this management setting. The proposed methodology finds the optimal time between long stoppages and optimal spare parts order quantity when the prior information about the degradation process is accurate. The methodology can be used to analyse the sensitivity of the optimal solution to changes in the accuracy and bias of the prior distributions of the model parameters, the cost structure and the number of machines in the system.

Maintenance scheduling based on PROMETHEE method in conjunction with group technology philosophy

2018 ◽  
Vol 35 (7) ◽  
pp. 1423-1444 ◽  
Author(s):  
Abdelhakim Abdelhadi
Keyword(s):  
Preventive Maintenance ◽  
Group Technology ◽  
Spare Parts ◽  
Strategic Decision ◽  
Maintenance Cost ◽  
Manufacturing Strategy ◽  
Content Type ◽  
Clustering Problem ◽  
Promethee Method ◽  
The Impact

Purpose The purpose of this paper is to implement a strategic decision-making framework by selecting clusters of maintainable machines and scheduling their maintenance as part of a company’s manufacturing strategy. Design/methodology/approach Multi-criteria clustering problem in conjunction with the application of a group technology is used to establish clusters of maintainable machines based on their need for maintenance according to the type of failures they can encounter. Findings Using the concept of group technology in conducting preventive maintenance will result in the grouping of machines according to the impact of a failure based on the criteria specified by the decision makers. Accordingly, it will facilitate the process of executing the maintenance itself by ordering spare parts and informing the maintenance personnel which will lead to minimize the maintenance cost. Originality/value The results presented in this paper are reliable, objective may be used to minimize the total cost of conducting preventive maintenance in a manufacturing environment.

Optimal maintenance strategies for repairable systems with general degree of repair

1991 ◽  
Vol 28 (2) ◽  
pp. 384-396 ◽  
Author(s):  
Wolfgang Stadje ◽  
Dror Zuckerman
Keyword(s):  
Optimal Policy ◽  
Planning Horizon ◽  
Spare Parts ◽  
Inventory Systems ◽  
Maintenance Strategy ◽  
Repairable Systems ◽  
Discounted Cost ◽  
Wide Range ◽  
Optimal Maintenance ◽  
New Research

In this study we examine repairable systems with random lifetime. Upon failure, a maintenance action, specifying the degree of repair, is taken by a controller. The objective is to determine an age-dependent maintenance strategy which minimizes the total expected discounted cost over an infinite planning horizon. Using several properties of the optimal policy which are derived in this study, we propose analytical and numerical methods for determining the optimal maintenance strategy. In order to obtain a better insight regarding the structure and nature of the optimal policy and to illustrate computational procedures, a numerical example is analysed. The proposed maintenance model outlines a new research channel in the area of reliability with interesting theoretical issues and a wide range of potential applications in various fields such as product design, inventory systems for spare parts, and management of maintenance crews.

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