Fuzzy uncertainty modelling for project planning; application to helicopter maintenance

Maintenance is an activity of growing interest specially for critical systems. Particularly, aircraft maintenance costs are becoming an important issue in the aeronautical industry. Managing an aircraft maintenance center is a complex activity. One of the difficulties comes from the numerous uncertainties that affect the activity and disturb the plans at short and medium term. Based on a helicopter maintenance planning and scheduling problem, we study in this paper the integration of uncertainties into tactical and operational multiresource, multi-project planning (respectively Rough Cut Capacity Planning and Resource Constraint Project Scheduling Problem). Our main contributions are in modelling the periodic workload on tactical level considering uncertainties in macro-tasks work contents, and modelling the continuous workload on operational level considering uncertainties in tasks durations. We model uncertainties by a fuzzy/possibilistic approach instead of a stochastic approach since very limited data are available. We refer to the problems as the Fuzzy RoughCut Capacity Problem (FRCCP) and the Fuzzy Resource Constraint Project Scheduling Problem (RCPSP).We apply our models to helicopter maintenance activity within the frame of the Helimaintenance project, an industrial project approved by the French Aerospace Valley cluster which aims at building a center for civil helicopter maintenance

Project scheduling under uncertainty using fuzzy modelling and solving techniques

In the real world, projects are subject to numerous uncertainties at different levels of planning. Fuzzy project scheduling is one of the approaches that deal with uncertainties in project scheduling problem. In this paper, we provide a new technique that keeps uncertainty at all steps of the modelling and solving procedure by considering a fuzzy modelling of the workload inspired from the fuzzy/possibilistic approach. Based on this modelling, two project scheduling techniques, Resource Constrained Scheduling and Resource Leveling, are considered and generalized to handle fuzzy parameters. We refer to these problems as the Fuzzy Resource Constrained Project Scheduling Problem (FRCPSP) and the Fuzzy Resource Leveling Problem (FRLP). A Greedy Algorithm and a Genetic Algorithm are provided to solve FRCPSP and FRLP respectively, and are applied to civil helicopter maintenance within the framework of a French industrial project called Helimaintenance

Decision Support Procedure for Medical Equipment Maintenance Management

Hospitals outsource several activities of the service support in order to focus on the core healthcare production as maintenance service. Recently, faced to the sophistication and the costs of medical equipment that continue to escalate, governments have implemented new reforms to control costs and improve the efficiency and the quality. Hospitals become interested in minimizing the total operational cost, by optimizing healthcare production planning and their support activities. Reorganizing the medical equipment maintenance service becomes a priority for the hospital managers to reduce the cost and the dependency on external parties while ensuring that the medical devices are safe, accurate, and operating at the required level of performance. In this article, we propose an efficient procedure to take the appropriate decisions for medical equipment maintenance such as the selection of maintenance strategy, the insourcing/outsourcing, and the selection of contracts’ type and content. A practical application of this procedure in the Tunisian context is considered. Nevertheless, our procedure is general and can be tailored to hospitals in both developed and developing countries

Tactical project planning under uncertainty: fuzzy approach

At the tactical planning level in a multi-project environment, uncertainties are inherent to the workloads, and costs may be involved for using non-regular capacity and violating project due dates. We propose an approach to identify whether non-regular capacities might be needed to meet the projects' due dates. This problem is known as rough-cut capacity planning (RCCP) problem under uncertainty. We propose a possibilistic approach, which is based on modelling uncertain workloads with fuzzy sets. We present the resulting fuzzy rough-cut capacity planning (FRCCP), and show that we can use the possibilistic approach to provide a robust solution with a fuzzy resource loading profile that supports managers in decision making. We provide a simulated annealing approach to solve the FRCCP, and test it against several existing RCCP approaches. For the experiments we use real life instances from a shipyard maintenance centre

La rétinopathie de décompression oculaire: une complication rare de la trabéculectomie

Une patiente âgée de 50 ans, monophtalme de l'oeil droit nous a été adressée pour une crise aigüe de glaucome par fermeture de l'angle de l'oeil droit qui a évolué vers la chronicité malgré le traitement médical précoce. A j1 post trabéculectomie l'examen retrouve une hypotonie à 6 mmHg avec au fond d'oeil présence d'un oedème  papillaire et de multiples hémorragies pré-rétiniennes rondes dont certaines à centre blanc localisées au pôle postérieur et en moyenne périphérie, épargnant la macula. L'évolution spontanée était favorable avec  stabilisation de la pression intra-oculaire (PIO) à 12 mm Hg et nettoyage du fond de l'oeil au bout de 6  semaines. Le bilan hématologique était sans particularités. La rétinopathie de décompression oculaire est une complication rare de la trabéculectomie. Son évolution est habituellement favorable. Dans certains cas une perturbation du bilan hématologique a été incriminée. Enfin cette complication peut être prévenue en évitant les variations brutales de la PIO.Key words: Rétinopathie, décompression oculaire, trabéculectomi

A GA-based fuzzy resource leveling optimization for helicopter maintenance activity

Abstract Genetic algorithm is one of the main heuristics that have been applied to scheduling problems in the last few decades. This paper presents a generalization of the genetic algorithm for solving project scheduling problem under time uncertainties within resource leveling technique. The generalization consists of handling fuzzy time parameter and fuzzy resource distribution instead of crisp ones. The provided fuzzy genetic algorithm is justified and applied to a real multi-project and multi-resources problem from the helicopter maintenance activity

Quantitative techniques for medical equipment maintenance management

The maintenance department in a hospital is responsible for ensuring the safety of medical equipment and their availability while keeping the operation costs minimal. The selection of the best maintenance strategy is a key decision to reduce the equipment downtime, increase the availability, and bring down the maintenance costs. In this paper, we use an integrated approach that includes several tools from the literature, namely, the Analytical Hierarchy Process (AHP), the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS), and the mathematical optimization (especially mixed integer problems MILP) to provide the decision maker of the maintenance department with an entire solution to the problem at hand. These three tools are introduced to 1) determine the criticality of medical equipment based on a multi-criteria analysis, 2) rank the different maintenance strategies based on their (benefits) importance to the hospital and 3) select the optimal maintenance strategy for each device while keeping the total maintenance costs within a predetermined budget. We applied our approach to a case study at the Hospital of “Habib Bourguiba” in Tunisia, and the numerical results show the efficiency of our approach to improve the availability and the reliability of high risk medical devices

Diagnostic and modeling of elderly flow in a French healthcare institution

One of the highest priorities in the French health care system is to deal with the continuous growth of the percentage population older than 65 years, expected to reach 31% in 2030. This development poses enormous challenges to the operations of the health care system, especially, related to elder patients. The elderly flow in the hospital services is typically uncertain and subject to variations on the length of stay in each stage and on the path or sequence of stages followed by the patient. For that reason, we propose to model the patient flow in a hospital as a continuous-time Markov chain with an absorbing state representing the elderly discharge from the hospital. Three Markov chains are provided with different levels of details and computation complexity. The first model called aggregated provides a prediction of the length of stay per service, the second model called Coxian provides a reliable prediction of the total length of stay, and the third model called detailed provides a prediction of the length of stay per class of elderly. A classification of elderly based on multiple correspondence technique is considered before the application of the third model. Our models are fitted with the data collected from Roanne Hospital, a typical French health care structure

Planification et ordonnancement de projet sous incertitudes : application à la maintenance d'hélicoptères

This thesis is a study within the framework of the Helimaintenance project; a European project approved by the French aerospace valley cluster that aims to establish a center for civil helicopter maintenance which is also able to make R&D projects in the field. Our work consists of integrating uncertainties into both tactical and operational multiresources, multi-projects planning and dealing with Rough Cut Capacity Planning, Resource Leveling Problem and Resource Constraint Project Scheduling Problem under uncertainties. Uncertainty is modelled within a fuzzy/possibilistic approach instead of a stochastic approach since very limited data is available in our case of study. Three types of problems are referred in this study which are the Fuzzy Rough Cut Capacity Problem (FRCCP), the Fuzzy Resource Leveling Problem (FRLP) and the Fuzzy Resource Constraint Project Scheduling Problem (RCPSP). Moreover, a Genetic Algorithm and a Parallel SGS are provided to solve the FRLP and FRCPSP problems, respectively. A Simulated Annealing is provided to solve the FRCCP problem.Cette thèse entre dans le cadre du projet Hélimaintenance ; un project labellisé par le pôle de compétitivité Français Aérospace-Valley, qui vise à construire un centre dédié à la maintenance des hélicoptères civils qui soit capable de lancer des travaux en R&D dans le domaine. Notre travail consiste à prendre en considération les incertitudes dans la planification et l'ordonnancement de projets et résoudre les problèmes Rough Cut Capacity Planning, Resource Leveling Problem et Resource Constraint Project Scheduling Problem sous incertitudes. L'incertitude est modélisée avec l'approche floue/possibiliste au lieu de l'approche stochastique ce qui est plus adéquat avec notre cas d'étude. Trois types de problèmes ont été définis dans cette étude à savoir le Fuzzy Rough Cut Capacity Problem (FRCCP), le Fuzzy Resource Leveling Problem (FRLP) et le Fuzzy Resource Constraint Project Scheduling Problem (RCPSP). Un Algorithme Génétique et un Algorithme "Parallel SGS" sont proposés pour résoudre respectivement le FRLP et le FRCPSP et un Recuit Simulé est proposé pour résoudre le problème FRCCP

Special Issue on Efficient and Robust (Meta)Heuristics for Industrial and Service Engineering Preface

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