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Ababutain, A Y (2002) A multi-criteria decision-making model for selection of BOT toll road proposals within the public sector, Unpublished PhD Thesis, , University of Pittsburgh.

Aktas, C B (2011) Impact of product lifetime on life cycle assessment results, Unpublished PhD Thesis, , University of Pittsburgh.

Aktas, E (2001) Structural design code calibration using reliability-based cost optimization, Unpublished PhD Thesis, , University of Pittsburgh.

Alkhathami, M M (2004) Examination of the correlation of critical success and delay factors in construction projects in the kingdom of Saudi Arabia, Unpublished PhD Thesis, , University of Pittsburgh.

Almazroa, D A (2003) Project delivery system decision framework using the weighting factors and analytic hierarchy process methods, Unpublished PhD Thesis, , University of Pittsburgh.

Amruthapuri, R S G R (2021) Partnership between diverse stakeholders: A potential solution to issues migrant construction workers face in Bengaluru, India, Unpublished PhD Thesis, , University of Pittsburgh.

Banawi, A A (2013) Improving construction processes by integrating lean, green, and six-sigma, Unpublished PhD Thesis, , University of Pittsburgh.

Bilec, M M (2007) A hybrid life cycle assessment model for construction processes, Unpublished PhD Thesis, , University of Pittsburgh.

Campion, N A (2015) Advancing life cycle assessment: Perspectives from the building and healthcare industries, Unpublished PhD Thesis, , University of Pittsburgh.

Hussain, M A D (2001) Value engineering expert system in suburban highway design (VEESSHD), Unpublished PhD Thesis, , University of Pittsburgh.

Kalainesan, S (2007) Best management practices for highway construction site sedimentation basins, Unpublished PhD Thesis, , University of Pittsburgh.

Osman, A E (2006) Life cycle optimization model for integrated cogeneration and energy systems applications in buildings, Unpublished PhD Thesis, , University of Pittsburgh.

Rajagopalan, N (2011) Residential life cycle assessment modeling for green buildings and building products, Unpublished PhD Thesis, , University of Pittsburgh.

Sanoubar, S (2022) Temporal and spatial considerations in maintenance planning, Unpublished PhD Thesis, , University of Pittsburgh.

  • Type: Thesis
  • Keywords: optimization; replacement; policy; heuristic
  • ISBN/ISSN:
  • URL: https://www.proquest.com/docview/2748385101
  • Abstract:
    Maintenance spending is well-known to constitute a substantial part of total production and service costs. We focus on optimal planning of maintenance activities in several novel settings. In each setting, we formulate a mathematical optimization model using stochastic modeling techniques and establish the structural properties of the optimal policy through theoretical derivations. We provide additional policy insights using numerical observations and develop easy-to-implement and high-performing heuristic policies.Specifically, we first study an age-replacement setting (with minimal repair) in which the maintenance worker may be unpunctual. That is, the actual preventive replacement times may deviate from the prescribed replacement times in a probabilistic manner. We formulate a long-run expected cost-rate minimization model and compare the optimal solution and its performance to those when the unpunctual behavior is assumed to be either absent or independent of the prescribed replacement time.Next, we consider an age-replacement setting (without minimal repair) in which replacement costs are non-decreasing in system age. This assumption is motivated by factors such as decreasing salvage value or increasing costs associated with obtaining spare parts. We formulate a long-run expected cost-rate minimization model that captures this dependency and compare the optimal solution and its performance to those for the case in which replacement costs are assumed to be constant.Finally, we consider the problem of performing condition-based maintenance on a set of geographically distributed assets via a single maintenance resource that travels between the assets' locations. We use a graph representation to model possible geographical locations of the resource, including idling and asset locations and the links between them. We formulate a Markov decision process to dynamically obtain the optimal positioning of the maintenance resource and the optimal timing of the interventions that the resource performs.