Joint optimization of the selective maintenance and repairperson assignment problem when using new and remanufactured spare parts

This paper deals with the problem of the selective maintenance (SM) optimization for a series-parallel system. The system performs several missions with breaks between consecutive missions. To improve the system reliability during the next mission, its components are maintained during the breaks. Current models in the SM literature usually assume that when a component is subjected to a replacement, it is done by a new one. This paper introduces a novel variant of the selective maintenance problem (SMP) where a mixture of new and reconditioned/remanufactured parts are used to carry out replacements. It has indeed been proved that remanufacturing processes can extend the life of a product returned from the field. This provides not only economic opportunities but also favours sustainable practices. Accordingly, a novel mixed integer nonlinear programming model of the SMP is developed and optimally solved. Numerical experiments show how using reconditioned spare parts impacts the SM decisions. (C) 2019, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved

Outsourcing selective maintenance problem in failure prone multi-component systems

In many industrial settings, there are systems designed to perform consecutive missions interspersed with finite breaks during which only a set of component repairs can be carried out due to limited time, budget, or resources. The decision maker then has to decide which components to repair in order to guarantee a given performance level. This is known as the selective maintenance problem (SMP). This paper introduces a new variant of the SMP by specifically taking into account the maintenance outsourcing alternative. A novel integrated non-linear programming formulation where both the in-house and outsourcing maintenance alternatives are accounted for is developed and optimally solved. The effect of the outsourcing alternative on maintenance decisions is investigated through numerical experiments. The overall results obtained demonstrate the validity of the proposed approach. (C) 2018, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved

Optimal selective maintenance for systems operating under random environments

This paper proposes a new variant of the joint selective maintenance and repair person assignment problem (SM&RAP) in multicomponent systems. The system carry out missions under random operating environments (OE). Between consecutive missions there are scheduled breaks of finite length within which maintenance actions are performed. Current selective maintenance (SM) models assume that the OE is static and does not change over the course of a mission. However, many mission critical systems are subjected to harsh and varying OE which impacts the mission success probability. This paper develops a new SM optimization model in systems under a random OE. The OE randomness is modeled as a random shock process, and the occurrence of a shock directly impacts the failure process of the components. A nonlinear SM optimization model along with its binary integer programming version are developed and solved to optimality. Numerical experiments are provided where the results obtained demonstrate the added value and the benefit of including the impact of the OE when dealing with SM&RAP

Condition-based selective maintenance for multicomponent systems under environmental and energy considerations

This work develops a new variant of selective maintenance (SM) optimization model for multicomponent systems running multiple alternating sequences of missions and breaks. A component deteriorates randomly and fails when the corresponding failure threshold is exceeded. Components' failures impact the quality of the environment and increase the energy consumption. Thus, failures induce penalty costs. Improving the system reliability during the following mission is achieved by performing maintenance activities on its elements during the breaks. A condition-based SM optimization problem (CBSMP)is developed to minimize the total expected cost subject to the limited break durations and required reliability for the next mission. A model's solution determines an optimal SM plan which minimize the total expected cost resulting from inspection, maintenance, and costs due to impact of components' failures on the environment and energy requirements. The proposed approach is tested on a numerical example

Optimization of the integrated fleet-level imperfect selective maintenance and repairpersons assignment problem

Industrial environments such as manufacturing and transportation industries usually involve fleets of identical systems that must carry out several missions interspersed with scheduled finite breaks. Given the limited amount of maintenance resources and time available, only a restricted number of maintenance actions can be performed on selected components to ensure a pre-specified performance level of the fleet for the next mission. Such a maintenance strategy is known as fleet-level selective maintenance (FSM). The FSM is more complex than the selective maintenance problem as it adds the total number of systems in the fleet as another level of combinations to be explored during the optimization process. Most FSM models consider the replacement or perfect repair of system components as the only maintenance option. Furthermore, they consider a single repair channel and disregard the assignment of repairpersons and the impact of their variable skillsets on the maintenance costs and duration. In this paper, an approach is proposed to help in more realistic decision making for FSM where several imperfect maintenance levels and multiple repair channels are available. A novel integrated non-linear programming formulation of the FSM problem where maintenance and repairpersons assignment decisions are made jointly is proposed. All relevant parameters and terms of this non-linear optimization problem are developed and discussed. A two-phase modeling approach is then used to transform the original nonlinear problem into a binary integer optimization model. To demonstrate the validity and the added value of the proposed approach, multiple sets of numerical experiments are investigated and managerial implications are provided

Supply chain modelling frameworks for forest products industry : a systematic literature review

Considering the economic importance of forest products industries in Canada, there has been an increasing interest to study the operations and interactions of all the relevant entities involved in its supply chain (SC). The forest products industry has a set of specific SC characteristics to meet the needs of its final consumers. While a growing number of mathematical and simulation models are being presented for the SC in this sector, an integrated formal structure is evidently required for guiding the development of and evaluating these models. Therefore, in this research, we systematically review and identify existing frameworks for modelling SCs with the interest of highlighting the ones relevant to the forest products SCs. While we find no framework specific to the forest products industry, we identify a number of existing frameworks that could be customized to represent the industry's SC

Supply chain modelling frameworks for forest products industry : a systematic literature review

Considering the economic importance of forest products industries in Canada, there has been an increasing interest in studying the operations and interactions of all the relevant entities involved in its supply chain (SC). The forest products industry has a set of specific SC characteristics to meet the needs of its final consumers. While a growing number of mathematical and simulation models are being presented for the SC in this sector, an integrated formal structure is evidently required for guiding the development of and evaluating these models. Therefore, in this research, we systematically review and identify existing frameworks for modelling SCs with the interest of highlighting the ones relevant to the forest products SCs. While we find no framework specific to the forest products industry, we identify a number of existing frameworks that could be customized to represent the industry's SC

Optimization of the joint selective maintenance and repairperson assignment problem under imperfect maintenance

This paper addresses the maintenance optimization problem in a multi-component system, carrying out several missions interspersed with scheduled finite breaks. Due to limited time, budget, or resources, maintenance actions can be only carried out on a limited set of components. The decision maker then has to decide which components to maintain to ensure a pre-specified performance level during the next mission. This is known as the selective maintenance problem. Most of the existing models in the literature usually assume that only one repair channel is available or that the assignment optimization can be done at a subsequent stage. To overcome this restrictive assumption, this paper introduces a novel integrated non-linear programming formulation of the selective maintenance problem to jointly select the components to be maintained, the maintenance levels to be carried out and the assignment of the maintenance tasks to multiple repair-persons or repair-channels. The fundamental constructs and the relevant parameters of this non-linear optimization problem are developed and discussed. Numerical experiments show the benefits of jointly selecting the components to be maintained and assigning the repair tasks to repair-persons

Selective maintenance optimization problem in systems under repairpersons availability

Industrial systems are sometimes designed to operate their missions with finite breaks scheduled between two consecutive missions. During the break, maintenance actions can be carried out. Given the limited break duration, in addition to other limited maintenance resources, not all components can be maintained. To meet the required performance of the system during the next mission, it is often required to select components to be maintained. This decision making problem is known as the selective maintenance problem (SMP). In the literature, the existing SM models merely rely on the assumption that repair channels are always available to perform their maintenance duties. The present paper introduces a novel and more realistic formulation of the SMP where the unavailability of the repair channels is accounted for. Two integrated non-linear programming models are developed and solved, without loss of generality, in a series-parallel system under multiple repair channels. The results derived allow to show the validity and the accuracy of the proposed approach

Optimizing selective maintenance problem in mission-oriented systems under repairpersons availability

Mission-oriented industrial systems are designed to operate a sequence of alternate missions and scheduled breaks. During breaks, maintenance tasks are usually carried out to improve the system's performance for the next missions. Given the limited length of breaks as well as other maintenance resources, only a subset of components set can be maintained. Therefore, there is a need to select components to maintain in order to meet the required performance of the system during the next mission. This maintenance strategy is referred to in the literature as the selective maintenance problem (SMP). The existing selective maintenance models assume that repairpersons are always available to carry out their tasks. The present work aims to relax this assumption and to develop a novel SMP formulation for mission-oriented systems under a planing horizon composed of several missions. Genetic algorithm is used to solve the resulting integrated non-linear programming model. To show the validity and the accuracy of the proposed approach, numerical experiments are provided. The results obtained indeed show that taking into account repairpersons availability impacts both the selective maintenance and repairpersons assignment decisions, while ensuring good estimation of the system reliability