Replacement optimization of ageing infrastructure under differential inflation

Ageing public infrastructure assets necessitate economic replacement analysis. A common replacement problem concerns an existing asset challenged by a replacement option. Classic techniques obtained from the domain of engineering economics are the mainstream approach to replacement optimization in practice. However, the validity of these classic techniques is built on the assumption that life cycle cash flows of a replacement option are repetitive. Differential inflation undermines this assumption and therefore more advanced replacement optimization techniques are required under these circumstances. These techniques are found in the domain of operations research and require linear or dynamic programming (LP/DP). Since LP/DP techniques are complex and time-consuming, the current study develops an alternative model for replacement optimizations under differential inflation. This approach builds on the classic capitalized equivalent replacement technique. The alternative model is validated by comparison with a DP model showing to be equally accurate for a case with characteristics that apply to many infrastructure assets.     

A life cycle costing approach for discounting in age and interval replacement optimisation models for civil infrastructure assets

Civil infrastructure assets, such as roads, locks, bridges, treatment plants and storm surge barriers, are often characterised by long service lives and corresponding technical life cycles. When life cycles are long, the time value of money plays a role in asset management decision-making on capital investments and operation and maintenance expenditures. In this paper, a new life cycle costing (LCC) approach for discounting in two classes of maintenance optimisation models is developed. These models are the age replacement model and the interval replacement model. Three well-known LCC techniques, which are the present worth, the capital recovery and the capitalised equivalent worth, are combined and used to develop a stepwise methodology. This methodology is validated with the few case-specific mathematical equations that exist in the literature. The advantage of using this alternative LCC approach is its applicability and flexibility for reliability and maintenance engineers. The resulting LCC method builds on well-known LCC formula and enhances the understanding of the inclusion of discounting principles in reliability models. Understanding these principles makes the method flexible. Practitioners can extend or adapt the method to changing circumstances, such as additional cash flows and altering reliability modelling.     

Concurrent bilevel multi-objective optimisation of renewal funding decisions for large-scale infrastructure networks

Infrastructure fund-allocation is a complex multi-dimensional decision-making problem. It involves multiple stakeholders, thousands of assets with multiple alternative renewal types and timings for each intervention over the planning horizon. Decision-makers need to satisfy stakeholders’ preferences, and determine which and when assets will be funded (network-level decisions) and what repair strategy to use for each asset (project-level decisions). Most of the existing research efforts that addressed both levels have suffered from: consideration of a single objective, fragmented optimisation formulation, and scalability issues in handling large networks of assets. Accordingly, a concurrent bilevel optimisation model that combines both levels into one mathematical formulation while satisfying the varying objectives of infrastructure stakeholders is developed. A pavement case study is used to evaluate its performance against existing phased techniques. Afterwards, two multi-objective formulations have been examined: penalty and compromise. Results demonstrated that the proposed concurrent bilevel model: (1) out-performed comparable phased models, (2) was able to arrive at near-optimum solutions in a feasible processing time for large-scale infrastructure networks, and (3) is capable of dealing with conflicting stakeholder objectives in a flexible manner, using multi-objective formulation, that is extendable to include other objectives that exist in the context of infrastructure fund-allocation problems.     

Life cycle utility-informed maintenance planning based on lifetime functions: optimum balancing of cost,failure consequences and performance benefit

Decision-making regarding the optimum maintenance of civil infrastructure systems under uncertainty is a topic of paramount importance. This topic is experiencing growing interest within the field of life cycle structural engineering. Embedded within the decision-making process and optimum management of engineering systems is the structural performance evaluation, which is facilitated through a comprehensive life cycle risk assessment. Lifetime functions including survivor, availability, and hazard at component and system levels are utilised herein to model, using closed-form analytical expressions, the time-variant effect of intervention actions on the performance of civil infrastructure systems. The presented decision support framework based on lifetime functions has the ability to quantify maintenance cost, failure consequences and performance benefit in terms of utility by considering correlation effects. This framework effectively employs tri-objective optimisation procedures in order to determine optimum maintenance strategies under uncertainty. It provides optimum lifetime intervention plans allowing for utility-informed decision-making regarding maintenance of civil infrastructure systems. The effects of the risk attitude, correlation among components and the number of maintenance interventions on the optimum maintenance strategies are investigated. The capabilities of the proposed decision support framework are illustrated on five configurations of a four-component system and an existing highway bridge.     

Coordination of urban infrastructure reconstruction projects

The large number of urban infrastructure renewal activities occurring in cities throughout the world leads to social, economic and environmental impacts on the communities in its vicinity. As such, a coordinated effort is required to streamline these activities. This paper presents a framework to enable temporal (time-based) coordination of water, sewer and road intervention activities. Intervention activities include routine maintenance, renewal and replacement of physical assets. The coordination framework considers (1) life-cycle costs, (2) infrastructure level-of-service and (3) risk exposure to system operators. The model enables infrastructure asset managers to trade-off options of delaying versus bringing forward intervention activities of one system in order to be executed in conjunction with another co-located system in the right-of-way. The framework relies on a combination of meta-heuristics and goal-based optimisation. In order to demonstrate the applicability of the framework, a case study for a major infrastructure corridor in Cairo, Egypt, is taken as an example. Results show that the framework can be scaled up to include other infrastructure systems located in the right-of-way like electricity, gas and telecom, provided that information can be shared among these entities     

An augmented Lagrangian decomposition approach for infrastructure maintenance and rehabilitation decisions under budget uncertainty

This article addresses a general class of infrastructure management problems raised in maintenance and rehabilitation scheduling. Infrastructure agencies usually face budget uncertainties that eventually lead to suboptimal scheduling planning if maintenance decisions are made without taking the uncertainty into consideration. It is important for decision makers to adopt maintenance and rehabilitation scheduling policies that consider all budget scenarios. The authors propose a multistage, stochastic programming model to address this problem. The authors also develop a solution procedure using the augmented Lagrangian decomposition algorithm. A case study exploring the computational characteristics of the proposed algorithm is conducted and the benefit ofusing the stochastic programming approach is discussed.     

Network level bridges maintenance planning using Multi-Attribute Utility Theory

Bridge infrastructure managers are facing multiple challenges to improve the availability and serviceability of ageing infrastructure, while the maintenance planning is constrained by budget restrictions. Many research efforts are ongoing, for the last few decades, ranging from development of bridge management system, decision support tools, optimisation models, life cycle cost analysis, etc. Since transport infrastructures are deeply embedded in society, they are not only subject to technical requirements, but are required to meet the requirements of societal and economic developments. Therefore, bridge maintenance planning should accommodate multiple performance goals which need to be quantified by various performance indicators. In this paper, an application of Multi-Attribute Utility Theory (MAUT) for bridge maintenance planning is illustrated with a case study of bridges from the Netherlands road network. MAUT seeks to optimise multiple objectives by suggesting a trade-off among them and finally assigns a ranking to the considered bridges. Moreover, utility functions of MAUT appropriately account for the involved uncertainty and risk attitude of infrastructure managers. The main contribution of this study is in presenting a proof-of-concept on how MAUT provides a systematic approach to improve the decision-making of maintenance planning by making use of available data, accommodating multiple performance goals, their uncertainty, and preferences of infrastructure managers.     

Fuzzy approach for optimum replacement time of mixed infrastructures

Investments in infrastructure assets represent a sizable portion in the governments’ public fund. Continuous maintenance, rehabilitation, and replacement are required to maintain the level of service of infrastructure assets. Knowing the replacement needs of infrastructures and the timing of replacement are challenging tasks. This paper presents a decision support tool that aids in deciding the best time to replace several types of infrastructure assets, that is, mixed infrastructure. The paper uses fuzzy logic to model uncertainties in order to identify the useful lifetime of each infrastructure asset. Infrastructure replacement decision is made based on least cost option(s). A fuzzy logic tool is applied in three steps: data fuzzification, fuzzy inference, and data defuzzification. The developments made in the fuzzy logic tool are presented. A numerical example is presented to demonstrate the practical features of the proposed tool.     

Capital renewal optimisation for large-scale infrastructure networks: genetic algorithms versus advanced mathematical tools

Civil infrastructure assets require continuous renewal (repair, rehabilitation or replacement) actions to modernise the inventory and sustain its operability. Allocating limited renewal funds among numerous asset components, however, represents a complex optimisation problem. Earlier efforts using genetic algorithms (GAs) could optimise small size problems yet exhibiting steep degradation in solution quality as problem size increases. Even by applying sophisticated mechanisms such as ‘segmentation’ to improve the performance of GAs, large processing time hinders the practicality of the algorithm for large-scale problems. This article, therefore, aims at improving both processing speed and solution quality for very large-scale problems (up to 50,000 assets). The article develops optimisation models using an advanced modelling tool (GAMS/CPLEX), and compares its results with GAs on three different model formulations. Both approaches proved to be beneficial, yet the advanced mathematical approach showed superior performance.     

Bridge life-cycle performance and cost: analysis,prediction, optimisation and decision-making

The development of a generalised framework for assessing bridge life-cycle performance and cost, with emphasis on analysis, prediction, optimisation and decision-making under uncertainty, is briefly addressed. The central issue underlying the importance of the life-cycle approach to bridge engineering is the need for a rational basis for making informed decisions regarding design, construction, inspection, monitoring, maintenance, repair, rehabilitation, replacement and management of bridges under uncertainty which is carried out by using multi-objective optimisation procedures that balance conflicting criteria such as performance and cost. A number of significant developments are summarised, including time-variant reliability, risk, resilience, and sustainability of bridges, bridge transportation networks and interdependent infrastructure systems. Furthermore, the effects of climate change on the probabilistic life-cycle performance assessment of highway bridges are addressed. Moreover, integration of SHM and updating in bridge management and probabilistic life-cycle optimisation considering multi-attribute utility and risk attitudes are presented.     

Managing essential infrastructure

Modern society has total dependence on key national infrastructure. Privatisation has led to a perennial search for efficiency gains, one manifestation being multiple subcontracting to least cost providers. The danger of ineffective control of subcontractors calls for a new approach to the management of essential infrastructure. The author describes the business model of 24seven in the electricity and gas market in the UK. In this market full competition in the energy supply (retail) sector is resulting in lower prices for customers and innovation in the market place. It has also produced a structural change that allows ownership of delivery infrastructure to be separated from the product's marketing and sale. The benefit is that infrastructure experts focus on their core skills, as do the retailers. The 24seven model takes the path of separation a stage further. The ownership of the assets is separated from the management and servicing of those assets. The result is a business model that addresses the 'value for money' needs of customers and ensures safety and long term health of vital infrastructure assets     

Sewer asset management – state of the art and research needs

ABSTRACT

Sewer asset management gained momentum and importance in recent years due to economic considerations, since infrastructure maintenance and rehabilitation directly represent major investments. Because physical urban water infrastructure has life expectancies of up to 100 years or more, contemporary urban drainage systems are strongly influenced by historical decisions and implementations. The current decisions taken in sewer asset management will, therefore, have a long-lasting impact on the functionality and quality of future services provided by these networks. These decisions can be supported by different approaches ranging from various inspection techniques, deterioration models to assess the probability of failure or the technical service life, to sophisticated decision support systems crossing boundaries to other urban infrastructure. This paper presents the state of the art in sewer asset management in its manifold facets spanning a wide field of research and highlights existing research gaps while giving an outlook on future developments and research areas.     

Infrastructure deterioration modeling with an inhomogeneous continuous time Markov chain: A latent state approach with analytic transition probabilities

Markov chains have been widely used to characterize performance deterioration of infrastructure assets, to model maintenance effectiveness, and to find the optimal intervention strategies. For long-lived assets such as bridges, the time-homogeneity assumptions of Markov chains should be carefully checked. For this purpose, this research proposes a regime-switching continuous-time Markov chain of which the state transition probabilities depend on another, latent, Markov chain that characterizes the overall aging regime of an asset. With the aid of a state-augmentation technique, closed-form solutions for the transition probabilities are analytically derived, making the statistical analysis simple. A case study is presented using the open Ontario Bridge Condition data for provincial highway bridges. The case study demonstrates that the proposed method allows to (1) estimate a statistically superior model to the homogeneous Markov chain and (2) obtain results with comparable accuracy in approximately 48% of the computation time of the state-of-the-art inhomogeneous Markov chain.     

Algorithms for bottom-up maintenance optimisation for heterogeneous infrastructure systems

This paper presents a methodology for maintenance optimisation for heterogeneous infrastructure systems, i.e., systems composed of multiple facilities with different characteristics such as environments, materials, and deterioration processes. We present a bottom-up approach: facility-level optimal maintenance policies are first found; these policies are then combined with budget constraints in the system-level optimisation. In the first step, optimal and near-optimal maintenance policies for each facility are found and used as inputs for the system-level optimisation. In the second step, the problem is formulated as a constrained combinatorial optimisation problem, where the best combination of facility-level optimal and near-optimal solutions is identified. Two heuristics, pattern search heuristic (PSH) and evolutionary algorithm (EA), are adopted to solve the combinatorial optimisation problem. Their performance is evaluated using a hypothetical system of pavement sections. Comparison result with real optimal solutions for 20 facilities showed that both algorithms give near-optimal solutions (within less than 0.1% difference from the optimal solution) in 978 (PSH) and 966 (EA) cases out of 1000 executions. The EA performs better in terms of processing time than the PSH. Numerical experiments show the potential of the proposed algorithms to solve the maintenance optimisation problem for realistic heterogeneous systems.     

Spatial Planning and High-Speed Broadband: Australia's National Broadband Network and Metropolitan Planning

The Australian government is constructing a National Broadband Network (NBN), which at an estimated cost of $43 billion will be Australia's largest ever infrastructure project. The NBN, if its full benefits are to be realized, raises a number of important, but largely unexplored, questions for planning. This paper investigates the implications of the NBN for Australian metropolitan planning focusing on the question of how these plans will exploit the NBN to improve urban outcomes. The paper examines the Sydney, Melbourne and Brisbane metropolitan areas and analyses the strategies shaping the future of these regions during the rollout and implementation of the NBN. This comparative analysis reveals similarities across these three metropolitan areas in their weak stance towards the NBN. Some key findings include: (1) a segregation of infrastructure planning and metropolitan planning; (2) a lack of consistency between different policies within each metropolitan area and (3) policy gaps regarding the role of telecommunications at the metropolitan level. Considering the number of governments worldwide that are making large investments in high-speed broadband, this paper addresses policy issues that will impact upon metropolitan planning well beyond the borders of Australia.     

Untangling decision tree and real options analyses: a public infrastructure case study dealing with political decisions,structural integrity and price uncertainty

Managerial flexibility in infrastructure investment and replacement decisions adds value. Real options analysis (ROA) captures this value under uncertain market prices. The concept of ROA is that future unfavourable payoffs can be deferred as soon as more information about market prices becomes available. The popularity of ROA is seen in a growing number of case studies on real assets. Despite its increasing popularity, ROA has not gained a foothold in public infrastructure decision making. One of the difficulties in the application of ROA is the required estimation of market variables. To avoid this, a simplified but not correct version of ROA is easily applied, referred to as a Decision Tree Approach (DTA) to ROA. Another difficulty is that infrastructure assets are subject to other types of uncertainties, defined here as asset uncertainties. This study investigates the value of managerial flexibility in a public infrastructure replacement decision. The uncertainty drivers are the strength of a bridge, political decisions regarding traffic flow and the price development of construction costs. Three valuation approaches are compared: DTA, ROA and the DT approach to ROA. Although it is complex, ROA certainly adds value in public infrastructure decision making when market price uncertainty is prevalent. However, in the absence of reasonable estimates of market variables, the DT approach to ROA is the best alternative. In the absence of market price uncertainties, ROA should be avoided DTA is to be preferred.     

Maintenance strategies optimisation of metro tunnels in soft soil

This paper proposes a quantitative approach for selecting effective maintenance strategies for metro tunnels in order to reduce maintenance cost and ensure tunnel safety in the presence of structural degradation during the service life. A non-stationary gamma process is used to simulate the tunnel gradual degradation and to investigate the effects of different maintenance measures on the life cycle maintenance cost of metro tunnels in soft soil. Two commonly applied reinforcement methods, Aramid Fibre Reinforced Polymer and bonded steel plate reinforcement, are investigated in this study. The feasibility of the proposed methodology is demonstrated with maintenance strategies based on periodic and aperiodic inspection policies. Numerical results show that the optimisation of maintenance strategy can reduce the life cycle maintenance cost of metro tunnels in soft soil while ensuring sufficient level of structural safety, and the maintenance strategy with aperiodic inspection policy produces lower maintenance cost.     

EMS‐WSV – Ein Erhaltungsmanagementsystem für Verkehrswasserbauwerke

A maintenance system of the German Federal waterways infrastructure. The German waterways network including the associated infrastructure facilities such as locks, weirs, culverts, canal bridges, bridges and lighthouses, has a fixed assets of around 40 billion €. The age structure of the hydraulic engineering structures becomes more and more unfavourable. Regarding locks, more than 35% are older than 80 years and have therefore exceeded their service life. Requirement for a technically reasonable and economic maintenance of the waterways infrastructure is an IT‐based maintenance system based on regular inspections. The article describes the approach of the German Federal Waterways and Shipping Administration (Wasser‐ und Schifffahrtsverwaltung des Bundes, WSV) for the inspection of the infrastructure facilities and gives an overview of the development of a maintenance system, which is currently worked out by the Federal Waterways Engineering and Research Institute (Bundesanstalt für Wasserbau, BAW).     

Offshore infrastructure planning using a vine copula approach for environmental conditions: an application for replacement maintenance of tidal energy infrastructure

Installation and maintenance operations of offshore assets are impacted by local environmental conditions such as wave height and period, wind speed and current velocity. These parameters are substantially of influence for the asset planning (time and costs) given the uncertainty of operational windows. In this article, a method is proposed to construct realistic time series of the aforementioned dependent conditions using a vine copulas approach. This method makes it possible to obtain a large number of realizations of these conditions at a certain location. It is shown that the operational windows remain persistent with the original limited dataset. Moreover, this method enables the incorporation of environmental uncertainties in the operational planning processes. To illustrate the value of this method, an application regarding replacement maintenance of a tidal energy infrastructure is examined. For this purpose, the maintenance activities are represented as a semi-Markov decision process. For every synthetic environmental time series, the algorithm finds the optimal set of decisions and the corresponding maintenance plans, including replacement costs and revenue losses. It is shown that the proposed method is effective in replacement maintenance decision making, while taking into account the environmental uncertainties.