The move towards integrating products and services has increased significantly. As a result, some business models, such as Product Service Systems (PSS) have been developed. PSS emphasises the sale of use of the product rather than the sale of the product itself. In this case, product ownership lies with the manufacturers/suppliers. Customers will be provided with a capable and available product for their use. In PSS, manufacturers/suppliers are penalised for any down time of their product according to the PSS contract. This has formed a pressure on the service providers (maintenance teams) to assure the availability of their products in use. This pressure increases as the products are scattered in remote places (customer locations). Authors have urged that different product monitoring levels are applied to enable service providers to monitor their products remotely allowing maintenance to be performed accordingly. They claim that by adopting these monitoring levels, the product performance will increase. Their claim is based on reasoning, not on experimental/empirical methods. Therefore, further experimental research is required to observe the effect of such monitoring levels on complex maintenance operations systems as a whole which includes e.g. product location, different types of failure, labour and their skills and locations, travel times, spare part inventory, etc. In the literature, monitoring levels have been classified as Reactive, Diagnostics, and Prognostics. This research aims to better understand and evaluate the complex maintenance operations of a product in use with different levels of product monitoring strategies using a Discrete Event Simulation (DES) approach. A discussion of the suitability of DES over other techniques has been provided. DES has proven its suitability to give a better understanding of the product monitoring levels on the wider maintenance system. The requirements for simulating a complex maintenance operation have been identified and documented. Two approaches are applied to gather these generic requirements. The first is to identify those requirements of modelling complex maintenance operations in a literature review. This is followed by conducting interviews with academics and industrial practitioners to find out more requirements that were not captured in the literature. As a result, a generic conceptual model is assimilated. A simulation module is built through the Witness software package to represent different product monitoring levels (Reactive, Diagnostics, and Prognostics). These modules are then linked with resources (e.g. labour, tools, and spare parts). To ensure the ease of use and rapid build of such a complex maintenance system through these modules, an Excel interface is developed and named as Product Monitoring Levels Simulation (PMLS). The developed PMLS tool needed to be demonstrated and tested for tool validation purposes. Three industrial case studies are presented and different experimentations are carried out to better understand the effect of different product monitoring levels on the complex maintenance operations. Face to face validation with case companies is conducted followed by an expert validation workshop. This work presents a novel Discrete Event Simulation (DES) approach which is developed to support maintenance operations decision makers in selecting the appropriate product monitoring level for their particular operation. This unique approach provides numerical evidence and proved that the higher product monitoring level does not always guarantee higher product availability.

Traditional Canadian pavement construction contracts provide detailed specifications for the work that needs to be carried out. This is the case for both maintenance and rehabilitation contracts. However, for many road agencies around the world, this traditional way of contracting had shortcomings. These agencies have been proactive in changing their contracts to maintain the road networks while reducing the cost. The challenge of maintaining the road networks to the highest possible condition while investing the minimal amount of money has promoted innovative contracting approaches. Furthermore, road agencies have increased the private sector involvement through warranty contracts. According to road agencies around the world, there has been a movement over the last two decades towards Performance Based Contracts (PBCs); a long term warranty contract. In PBCs, the client agency specifies certain clearly defined minimal performance measures to be met or exceeded during the contract period and payments are explicitly linked to the contractor successfully meeting or exceeding those performance measures. Therefore, the PBC maintenance and rehabilitation selection differs significantly from that of traditional asset management contracts and more complex due to the pavement deterioration process and probability of failure to achieve the specified level of service for various performance measures along the contract period. This thesis involves the development of a novel framework that facilitates the selection of maintenance and rehabilitation activities for pavement assets under PBCs. The framework consists of two phases. Phase-One, called the Initial Program, uses historical data, performance modeling, and optimization to establish and select the maintenance and rehabilitation program for the bidding stage. Phase-Two, called Project Asset Management, is implemented after the contract is awarded. This phase uses the contract performance monitoring data and the cost estimate from Phase-One as a baseline budget to update and validate the established program through performance modeling and optimization. A case study using data from the Ministry of Transportation Ontario (MTO) second generation Pavement Management System (PMS2) is used to illustrate the framework.

Thesis (Ph.D.)--University of Melbourne, Dept. of Medicine, Western Hospital, 2007. / Typescript. Includes bibliographical references (leaves 145-181).

Thesis (Ph. D.)--University OF MICHIGAN.

Thesis (Ph. D.)--University of Michigan, 1997. / Includes bibliographical references.

Thesis (D.P.H.)--University of Michigan, 2004. / Includes bibliographical references.

Thesis (M. Soc. Sc.)--University of Hong Kong, 1998. / Includes bibliographical references (leaves 201-207).

Thesis (M.Soc.Sc.)--University of Hong Kong, 1998. / Includes bibliographical references (leaves 201-207) Also available in print.

Dissertation (D.P.H.)--University of Michigan, 2004. / Includes bibliographical references.

Cette thèse propose un outil d’aide à la décision pour la gestion de processus de maintenance basée surune affectation optimale des ressources humaines afin d’améliorer la performance de la maintenance.En effet, une bonne performance de la fonction maintenance est indispensable pour maintenir laproductivité des installations industrielles, et donc de la compétitivité des entreprises manufacturières.L’approche que nous développons dans ce manuscrit procure un cadre de référence des leviersd’actions envisageables pour mesurer, évaluer, améliorer et optimiser la performance de lamaintenance. Nous prenons en considération un problème d’affectation des ressources humaines, quiprend en compte non seulement leurs disponibilités et compétences, mais aussi la gestion des urgencesd’intervention sur terrain.La méthode que nous proposons est basée sur un modèle de simulation à événements discrets,reproduisant au mieux un service de maintenance. Ceci nous a permis d’évaluer la situation via desindicateurs de performance présélectionnés. Pour optimiser le système, nous proposons un couplagedu modèle de simulation avec un module d’optimisation indépendant qui se réfère à une métaheuristiquebasée sur une approche Pareto. Notre proposition a été testée dans une entrepriseindustrielle réelle.L’approche que nous proposons donne un ensemble de solutions d’affectation des ressourceshumaines, aidant le décideur à mieux gérer l’indisponibilité de ses outils. Nous obtenons de bonsrésultats en un temps raisonnable. / In this thesis, a decision-making tool for maintenance management process based on assignment ofhuman resources is proposed in order to improve maintenance performance. An optimal maintenanceperformance is indispensable to guarantee the productivity and competitiveness of manufacturingcompanies.The proposed approach provides a framework of different possible levers to measure, evaluate,improve and optimize the maintenance performance. The assignment of human resources problem isconsidered. It takes into account different constraints like human resources availability, competences,urgency degree management of interventions requests etc.The proposed method is based on a discrete event simulation model, providing a better presentation ofthe maintenance service and better comprehensive thanks to the performance indicators. To improveuntil optimize the model, a simulation-based Pareto optimization method is introduced. Optimizationmodule was coded on independent programs in order to provide an opportunity of control thesimulation based optimization process.The proposed simulation based optimization method find good solutions in a reasonable amount oftime. Applying this technique on an industrial case-study, we show that it is more effective indetecting real faults than existing alternatives. The approach can be extended to cover other domainsand other types of simulation models.