David W. Coit

• Professor at Rutgers, The State University of New Jersey

The degradation of concrete structures is a significant issue in the United States, with the corrosion of steel reinforcement being a primary contributor. Cracks in concrete intensify the corrosion process by allowing easier access for chloride ions from deicing salts, adversely affecting the lifespan of structures. This study examines the corrosio...

In this paper, we develop a data-driven approach to predict the reliability of multi-component repairable systems, considering component dependencies. We estimate component reliability functions from system-level time-to-failure data without prior knowledge of the system structure and use these estimates to generate training data for a deep long sh...

Adopting a closed-loop supply chain enhances spare part provisioning through repair, remanufacturing, and recycling. However, poor maintenance of components can have severe consequences. Unlike traditional opportunistic maintenance methods that assume regular inspections or precise degradation monitoring, we propose a model that leverages historica...

Electric vertical takeoff and landing (eVTOL) aircraft are a futuristic, sustainable transportation mode aimed at reducing traffic congestion. The health management of eVTOL batteries is key for the deployment of such aircraft. In this paper, we consider the continuous monitoring of eVTOL batteries, with streams of measurements related to the charg...

Closed loop supply chains (CLSC) have become necessary to advance sustainable practices in the medical systems industry [5, 2]. The recovery processes, including repair, remanufacturing, and recycling, have been established as key drivers in reducing the demand for virgin materials, curtailing energy use, and limiting waste, thereby contributing to...

System reliability optimization combines the rigorous disciplines of probability theory and optimization. While there are many relevant problem formulations depending on user requirements, a typical problem is to maximize system reliability or minimize a cost rate, by determining the best system structure or architecture and/or maintenance plan, gi...

Interest and associated research for reliability and health prediction and maintenance of infrastructure and industrial products have increased continuously. The study of reliability and health prognosis has become an indispensable field in the overall design and evaluation of systems, industrial products and engineering projects. Previously, the c...

Efficient operation of modern society is largely dependent upon the reliable functioning of critical infrastructure with networked structures. The resilience of these network systems becomes a matter of great concern since the increasingly complex network dependency contributes to, although uncommon, devastating cascading failures in real-world net...

Despite the promising outlook, the numerous economic and environmental benefits of offshore wind energy are still compromised by its high operations and maintenance (O&M) expenditures. On one hand, offshore-specific challenges such as site remoteness, harsh weather, transportation requirements, and production losses, significantly inflate the O&M c...

Because of the increasing importance and dependencies of infrastructure networks and the potential for massive cascading failures in real-world network systems, maintenance optimization to effectively reduce system performance loss caused by diverse disruptions is of significant interest among researchers and practitioners. In this work, a new reco...

Despite the promising outlook, the numerous economic and environmental benefits of offshore wind energy are still compromised by its high operations and maintenance (O&M) expenditures. On one hand, offshore-specific challenges such as site remoteness, harsh weather, high transportation requirements, and production losses, significantly inflate the...

Previous researchers have made impressive strides in developing algorithms and solution methodologies to address multi-objective optimization (MOO) problems in industrial engineering and associated fields. One traditional approach is to determine a Pareto optimal set that represents the trade-off between objectives. However, this approach could res...

The tourist trip design problem (TTDP) helps the trip planners, such as tourists, tour companies, and government agencies, automate their trip planning. TTDP solver chooses and sequences an optimal subset of point of interest (POIs), which adhere to the POIs attributes and tourist preferences, and then generates a travel itinerary that maximizes th...

Maintenance and inventory control of spare parts are of great importance for efficiently managing onshore wind farms. Considering the economic and graphical dependencies among wind turbines and the stochastic degradations of the components in the turbines, this article studies the joint optimization of opportunistic condition-based maintenance and...

Opportunistic maintenance (OM), which shows its superiority on complex multi-component systems by integrating the maintenance activities of multiple components to reduce the maintenance cost, has been widely studied over the past decade. To our knowledge, most of the existing OM works are developed based on fixed maintenance thresholds without full...

Neural network-based techniques have been used extensively by researchers and practitioners in the energy sector for the last few decades, to solve specific problems such as unit commitment, battery scheduling, energy trading, load forecasting. In particular, the energy load forecasting is vital to enhance the flexibility in energy management. Howe...

Using artificial intelligence for maintenance planning is useful for many industries to have a smart decision-making tool that delivers the best maintenance policy to minimize the expected maintenance costs. In this paper, a deep reinforcement learning method is used to provide a new dynamic maintenance model for a degrading repairable system subje...

Operations and Maintenance (O&M) constitute a major contributor to offshore wind's cost of energy. Due to the harsh and remote environment in which offshore turbines operate, there has been a growing interest in opportunistic maintenance scheduling for offshore wind farms, wherein grouping maintenance tasks is incentivized at times of opportunity...

In this paper, a new control limit maintenance policy is proposed for a production system with multiple process states. The process state can be obtained by quality information or other measurable indicators from the production process, when the process state by itself provides an insufficient indication or measure of the actual machine state. This...

In the wake of the highly electrified future ahead of us, the role of energy storage is crucial wherever distributed generation is abundant, such as in microgrid settings. Given the variety of storage options that are becoming more and more economical, determining which type of storage technology to invest in, along with the appropriate timing and...

This Special Issue is motivated by novel decision-making settings entailed in supply chain resilience in the wake of the COVID-19 pandemic and characterized by crisis-like environment, epistemic and deep uncertainty, and adaptability as a “new normal” instead of stability and long-term planning.

Due to the increasing importance of large-scale and complex network systems and the potential for massive cascading failures in these real-world systems, modeling of system resiliency and optimization of restoration strategies to mitigate system performance loss caused by diverse disruptions is of significant interest among researchers and practiti...

We use general Markov additive processes (Markov modulated Lévy processes) to integrally handle the complexity of degradation including internally‐induced and externally‐induced stochastic properties with complex jump mechanisms. The background component of the Markov additive process is a Markov chain defined on a finite state space; the additive...

Operations and Maintenance (O&M) constitute a major contributor to offshore wind's cost of energy. Due to the harsh and remote environment in which offshore turbines operate, there has been a growing interest in opportunistic maintenance scheduling for offshore wind farms, wherein grouping maintenance tasks is incentivized at times of opportunity....

Many products degrade over time and their degradation processes could be affected by instantaneous shocks during field usage. Instantaneous shocks can cause incremental increases to the degradation signals through shock damages, and can also increase the degradation rates of products. In practice, some kinds of products can recover fully or partial...

Many engineering problems have multiple conflicting objectives, and they are also stochastic due to inherent uncertainties. One way to represent the multi-objective nature of problems is to use the Pareto optimality to show the trade-off between objectives. Pareto optimality involves the identification of solutions that are not dominated by other s...

In this article, a reinforcement learning approach is used to develop a new dynamic maintenance policy for multi-component systems with individually repairable components, where each component experiences two competing failure processes of degradation and random shocks. The gamma process is used to model the degradation path of each component in th...

In this paper, a repairable multi-component system is studied where all the components can be repaired individually within the system. The whole system is inspected at inspection intervals and the failed components are detected and replaced with a new one, while the other components continue functioning. Replacing components individually within the...

This paper presents a multi-objective redundancy allocation problem (MORAP) for maximizing system reliability and simultaneously minimizing system cost with limitations on system entropy, which is essential for achieving system stability and sustainability. Entropy is an important part of this new model because it provides a measure of randomness,...

In this paper, a repairable multi-component system is studied where all the components can be repaired individually within the system. The whole system is inspected at inspection intervals and the failed components are detected and replaced with a new one, while the other components continue functioning. Replacing components individually within the...

Implementing an appropriate maintenance policy would help us to have a more reliable system and reduce the total costs. In this paper, a dynamic maintenance plan is proposed for repairable multi-component systems, where each component is subject to two competing failure processes of degradation and random shock. For systems with individually repair...

Expansion planning problems refer to the monetary and unit investment needed for energy production or storage. An inherent element in these problems is the element of stochasticity in various aspects, such as the generation output of the units, climate change or frequency and duration of grid outages. Especially for the latter one, outage modeling...

A model and expansion plan have been developed to optimally determine microgrid designs as they evolve to dynamically react to changing conditions and to exploit energy storage capabilities. In the wake of the highly electrified future ahead of us, the role of energy storage is crucial wherever distributed generation is abundant, such as microgrid...

A significant amount of recent research effort has been put on the modeling of renewable energy systems (RES) consisting of various sources that incorporate storage capabilities. The reasons behind this trend are mainly the decreasing unit price of battery systems and the increasing need for adding resilience in the modern power systems. In this co...

Real-world network systems, for example, power grids, are critical to modern economies. Due to the increasing system scale and complex dependencies inside of these networks, system failures can widely spread and cause severe damage. We have experienced massive cascading failures in power grids, such as major U.S. western grid failures in 1996 and t...

This paper investigates the trade-off between two critical factors that influence, or even dictate, the rate of adoption of battery systems used to support photovoltaic arrays. The value of lost load and battery price greatly influence the island mode generation capability and the economic viability of photovoltaic + battery systems to provide ener...

For some design applications, the environment in actual field conditions does not remain constant but instead changes dynamically. In addition, stress levels might change sharply, and if the change happens for a long enough time and at a high enough rate, it could act as a shock to the product, although it is not actually a shock that occurs instan...

The failure of high-consequence systems, such as highspeed railways, can result in a series of severe damages. Due to the volatility of real circumstances, stochastic optimization methods are needed to aid decisions on reliability design and maintenance for the high-consequence systems. Traditionally, risk-neutral approaches are used by considering...

In this paper, a new reliability model has been developed for a single system degrading stochastically which experiences soft and hard failure. Soft failure occurs when the physical deterioration level of the system is greater than a predefined failure threshold, and hard failure occurs when the instantaneous stress caused by a shock process is gre...

Generation expansion planning is the framework under which power grid capacity expansions are made. Under this framework, mathematical optimization tools are used to determine the type of generation technology to invest in, and when and where these investments should be made in order to minimize market costs such as investment costs, fixed and vari...

In this paper, we present an analytical framework to establish a closed-form relationship between electricity generation expansion planning decisions and the resulting negative health externalities. Typical electricity generation expansion planning models determine the optimal technology-capacity-investment strategy that minimizes total investment...

In this paper a multi-component system is studied where each component can be repaired within the system. We consider that each component is subject to two dependent competing failure processes due to degradation and random shocks and each shock increases the total degradation of each component. For systems with individual repairable components, ea...

In this paper, a new reliability model has been developed for a single system degrading stochastically which experiences soft and hard failure. Soft failure occurs when the physical deterioration level of the system is greater than a predefined failure threshold, and hard failure occurs when the instantaneous stress caused by a shock process is gre...

An optimization model has been formulated and solved to determine on-condition failure thresholds and inspection intervals for multi-component systems with each component experiencing multiple failure processes due to simultaneous exposure to degradation and shock loads. In this new model, we consider on-condition maintenance optimization for syste...

The first and most important purpose of the current research work is to investigate the effects that different battery types have on the optimal configuration of photovoltaic (PV) and battery systems, from both economic and resilience perspectives. Many industry reports, as well as research papers, have already highlighted the crucial role that sto...

Electricity generation expansion planning models determine the optimal technology-capacity-investment strategy that minimizes market costs including investment costs, and fixed and variable operating & maintenance costs over a long-term planning horizon. From a market cost perspective, fossil fuels are among the most economical sources of electrici...

Power systems with photovoltaic (PV) arrays combined with battery backup storage are becoming increasingly used because of their capability of working in power island mode, especially during grid outages. The problem is to decide the optimal battery sizes for PV + battery systems with given solar array sizes, from both power supply reliability and...

This paper revisits the redundancy allocation problem, a well-known problem in reliability optimization, and implements a novel redundancy strategy, called K-mixed, to improve system reliability. The K-mixed strategy is a general form of a mixed strategy. The mixed strategy is a combination of active and standby redundancy strategies which was intr...

System reliability optimization is a living problem, with solutions methodologies that have evolved with the advancements of mathematics, development of new engineering technology, and changes in management perspectives. In this paper, we consider the different types of system reliability optimization problems, including as examples, the redundancy...

A modeling framework based on resiliency is proposed for the evaluation and optimization of restoration policies for electric power distribution systems subject to extreme weather events. In order to quantify resiliency, understood as a property of a power distribution system that allows it to be restored from a disrupted state to a predefined leve...

A start-up demonstration test is a mechanism that is often applied to determine the acceptability of equipment. Two new start-up demonstration tests are derived and demonstrated with the intent of equipment classification based on the testing results. The two new tests are called the CSTSCFTF_AMGC and CS <sup xmlns:mml="http://www.w3.org/1998/Math/...

The redundancy allocation problem (RAP) for series-parallel system is a system design problem by selecting an appropriate number of components from multiple choices for desired objectives, such as maximizing system reliability, minimizing system cost. RAP has been extensively studied in the last decades. The majority of existing RAP models assume t...

A two-stage optimization model has been developed for an offshore wind farm that integrates layout design and turbine maintenance policy-making. In Stage 1, first, the optimal development of the offshore wind resource aims to maximize the wind energy production by seeking the optimal turbine layout under uncertainty of wind conditions, in which the...

This paper presents a two-stage stochastic programming model with recourse for integrating the design and sequential preventive maintenance schedule of a system, which is subject to uncertain aperiodic-changing future usage stresses. Specifically, the usage stresses change as the system operates and preventive maintenance is conducted. The system u...

The two-sided assembly line becomes very popular in recent years. In this paper, a priority rules-based algorithmic design is developed for optimizing two-sided assembly line. Five elementary rules and 90 composite rules are tested on the benchmark data sets and their performance are provided. Two enumerative principles, which are specific to two-s...

A wireless sensor network is applied for detecting information, by nodes, then generates and transfers the packets to the clustering head for further transmission. In practice, due to the influence of environmental factors, traffic loads of nodes and barrier, a node may fail to detect the information which occurs within its sensing area. Thus, the...

A new model has been developed to analyze mixed cascading failures in network systems. The new model offers distinct advantages to analyze the combined impact of network load dynamics and network dependency on failure propagation, and to investigate specific effects of common types of network dependency on network robustness. Previous cascading fai...

A combinatorial system reliability modeling method is proposed to consider the effects of correlated probabilistic competing failures caused by the probabilistic–functional-dependence (PFD) behavior. PFD exists in many real-world systems, such as sensor networks and computer systems, where functions of some system components (referred to as depende...

A new modeling approach is presented to optimally and simultaneously design the configuration of a multicomponent system and determine a maintenance plan with uncertain future stress exposure. Traditionally, analytical models for system design and maintenance planning are applied sequentially, but this new model provides an integrated approach to m...

In this paper, a new cost optimization model has been developed and demonstrated to determine cost-effective maintenance plans specifically for performance-based contracting. Maintenance, repair and overhaul (MRO) has become more critical in many industries as the global economy continues to be more service-based. Traditionally, the MRO services ar...

We study an m-consecutive-k, l-out-of-n system with non-homogenous Markov-dependent components. The m-consecutive-k, l-out-of-n:F system fails if and only if there are at least m runs of k consecutive failed components and each of the runs may have at most l components overlapping with the previous run of k consecutive failed components. Using prob...

The establishment of the optimal time interval between inspections for multistate redundant systems considering availability and costs related to maintenance and production losses is a challenging issue. This paper extends previous research for redundant multistate systems where the time-to-repair cannot be neglected. Discrete-time Markov chains ar...

This article extends the finite Markov chain imbedding approach to evaluate the system reliability of a dynamic k-out-of-n:F system operating under two cyclic alternating conditions, and this article presents a method to obtain the optimal replacement interval of the system according to age-based replacement policy. In terms of the “dynamic k-out-o...

For some engineering design and manufacturing applications, particularly for evolving and new technologies, there can exist substantial heterogeneity in populations of manufactured components. The co-existence of n subpopulations and unit-to-unit heterogeneity can be common in devices when the manufacturing process is still maturing or highly varia...

In this study, we introduce reliability models for a device with two dependent failure processes: soft failure due to degradation and hard failure due to random shocks, by considering the declining hard failure threshold according to changes in degradation. Owing to the nature of degradation for complex devices such as microelectromechanical system...

This paper investigates reliability modeling for systems subject to dependent competing risks considering the impact from a new generalized mixed shock model. Two dependent competing risks are soft failure due to a degradation process, and hard failure due to random shocks. The shock process contains fatal shocks that can cause hard failure instant...

In this paper, we present a new reliability model and a unique condition-based maintenance model for complex systems with dependent components subject to respective degradation processes, and the dependence among components is established through environmental factors. Common environmental factors, such as temperature, can create the dependence in...

We study decentralized decisions among resiliency investors for hardening electric distribution systems with governance, which could coordinate the achievement of social optimums. Significant investments are being made to build resilient infrastructure for society well-being by hardening electric distribution networks. However, whether independent...

We propose the consecutive-k <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">r</sub> -out-of-n <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">r</sub> :F linear zigzag structure and circular polygon structure, which extend the consecutive-k-out-of-n:F syst...

This research is dedicated to the study of electric power system generation expansion planning considering uncertainty of climate change. Policy makers are increasingly concerned about the effects of climate change and its impact on human systems when making decisions. Electric power generation expansion planning (GEP) problems that determine the o...

This paper presents a new interpretation and formulation of the reliability-redundancy allocation problem (RRAP) and demonstrates that solutions to this new problem provide distinct advantages compared to traditional approaches. Using redundant components is a common method to increase the reliability of a system. In order to add the redundant comp...

System reliability design optimization models have been developed for systems exposed to changing and diverse stress and usage conditions. Uncertainty is addressed through defining a future operating environment where component stresses have shifted or changed for different future usage scenarios. Due to unplanned variations or changing environment...

New reliability models have been developed for systems subject to competing hard and soft failure processes with shocks that have dependent shock effects. In the new model, hard failure occurs when transmitted system shocks are large enough to cause any component in a series system to fail immediately, and soft failure occurs when any component det...

This paper focused on solving electricity generation expansion planning problems where there are uncertainties associated with the electricity demand forecasts. The electricity expansion plans are long-term commitments and affects people’s living conditions and business prosperity deeply. Therefore it is reasonable that the decision makers may be r...