Reliability evaluation and opportunistic maintenance policy based on a novel delay time model

Delay time modelling (DTM) has been developed and applied to industrial asset maintenance over the last 20 years. One of the key elements in DTM is the concept of the delay time which recognises an interval between the earliest point of defect identification and failure. Obviously the delay time is a random variable which varies depending upon the nature of defects and nature of inspections. If such a delay time can be captured by an appropriate distribution, various modelling options can be explored. This paper introduces the concept of delay time and its modelling techniques in the context of risk analysis of maintenance problems. It highlights the modelling for minimising the likelihood and consequence of economic or human risks associated with failures and maintenance activities under various maintenance strategies. Examples are presented, and the paper concludes with a summary of the key points discussed.

Optimal mission abort policy for systems subject to random shocks based on virtual age process

This work proposes the coefficient diagram method (CDM)-based two degree of freedom proportional integral (CDM-PI) controller tuning rules for stable and unstable first order plus time delay (FOPTD) processes and pure integrating processes with time delay (PIPTD). To derive the tuning rules, a general first order plus time delay (FOPTD) model, the first order Taylor denominator (TD) approximation technique and the pole allocation strategy named CDM is used. The tuning rules derived here are novel and they relate the controller parameters to the process model parameters directly. The performance of the CDM-PI controller utilising the proposed tuning rules is tested with numerical examples of stable, unstable and pure integrating processes with time delay models. The test results indicate that the proposed tuning rules yield promising results over the other PI controllers. Performance measures confirm the effectiveness of the proposed tuning method.

Ergodicity of forward times of the renewal process in a block-based inspection model using the delay time concept

A single component nonrepairable system suffering from both an internal stochastic degradation process and external random shocks is investigated in this paper. More specifically, the Wiener process with a positive drift coefficient is introduced to describe the gradual deterioration and the arrival number of external shocks is counted with a nonhomogeneous Poisson process (NHPP). Meanwhile, fault tolerant design is incorporated into the stochastically deterioration system so as to protect it from shock failures to some extent and is consummately addressed via a generalized m − δ shock model. From the actual engineering point of view, external shocks are typically classified into two distinct categories in this current research, that is, a minor shock (Type I shock) increasing the damage load on current degradation level and a traumatic shock (Type II shock) resulting in system catastrophic failure immediately. The closed‐form expression of system survival function is derived analytically and is viewed as the generalization of existing reliability function for systems subject to dependent and competing failure processes. Based on which, two time‐based maintenance (TBM) policies including an age replacement model and a block replacement model are scheduled, where the expected long‐run cost rate (ELRCR) in each model is, respectively, optimized to seek the optimal replacement interval. In the illustrative example part, a subsea blowout preventer (BOP) control system is arranged to validate the theoretical results numerically. To compare which policy is more profitable under different conditions, the relative gain on optimal maintenance cost rate of the two TBM policies is presented.

Auxiliary systems play a critical role in the reliable and safe operation of power plants, yet they remain a major source of unplanned downtime, maintenance cost escalation, and operational risk. Traditional maintenance approaches applied to these systems are often time-based or reactive, providing limited insight into failure behavior and inefficient allocation of maintenance resources. This study proposes an integrated maintenance strategy optimization framework that combines Reliability-Centered Maintenance (RCM) principles with stochastic failure modeling to enhance the reliability and cost-effectiveness of power plant auxiliary systems. A quantitative, reliability-based case study approach is adopted, focusing on key auxiliary systems including feedwater pumps, cooling water systems, lubrication units, air compressors, and ash handling systems. RCM analysis is used to identify critical components, dominant failure modes, and failure consequences, while stochastic failure models are developed to estimate failure rates, reliability functions, and system-level reliability profiles. Optimized maintenance intervals and policies are derived by balancing reliability, availability, cost, and risk considerations. The results demonstrate that the integrated RCM stochastic approach significantly improves Mean Time Between Failures (MTBF), system availability, and maintenance cost efficiency compared to conventional maintenance strategies. The study contributes a practical, data-driven framework for maintenance optimization and provides valuable insights for power plant asset management, particularly in environments characterized by aging equipment and resource constraints.

O.R. modelling of the deterioration and maintenance of concrete structures

A method to model a time delay by a finite impulse response filter is presented. It is useful in simulation work that involves time delays and transforms the time delay estimation problem into one of parameter estimation. The benefits of this approach are the elimination of spectral estimation, a choice of many parameter estimation algorithms, and the capability to track time-varying delays. Two examples of estimating nonstationary time delays are also given.

In this study, a revisited improved approach of an initial frequency response based autotuner is proposed to enable PID controller design based on S-shaped step response data. In prior autotuner, the critical frequency value is found using relay test whereas process frequency response and its derivative at this frequency are calculated via the sine test. With the proposed approach, these values are estimated using the first order plus time delay models, which are employed to characterize S-shaped step response. Firstly, an identification method is used to find the model parameters, i.e. time constant <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$T$</tex> and delay time L. Secondly, the required values are estimated using the first order plus time delay model. The remaining tuner design steps are the same as in the prior autotuner. The simulations are performed on four different types of dynamical systems to show effectiveness of the proposed approach. The simulation results suggest that the performance of the control system using the proposed approach improves in terms of achievable performance indicators such as overshoot and settling time.

Generalized eigenvalue minimization for uncertain first-order plus time-delay processes

In this paper, a calculation model for the breakdown time delay and jitter of gas switches under hundred-nanosecond pulses is proposed and applied in a self-triggered pre-ionized switch. The effects of injection time of pre-ionization, pulse rise time, and the pre-ionization jitter are discussed and verified through experiments. It indicates that the pre-ionization should be injected when the electric field is high enough in the gap, injection after 80% peak-time can ensure its effectiveness. Then the statistical time delay jitter will be determined by the pre-ionization jitter, which is an intrinsic restriction of the self-triggered switch. However, when the changing rate of the pulsed electric field exceeds a certain value, the breakdown time delay jitter can be partly offset in the formative stage because the formative time delay has an exponential relationship with the electric field. Therefore, lower time jitter can be obtained under pulses with a shorter pulse rise time. In general, the results of the calculation model agree with the experimental results, and the experimental parameters which lead to a low jitter can also be used as a reference.

Joint optimization of preventive maintenance and inventory management for standby systems with hybrid-deteriorating spare parts

Robotic teleoperation is a difficult task because of the inherent difficulty to model and control time-delay nonlinear models. In order to handle tractable models, typically there have been two ways to tackle this problem: i) The first approach is to assume that the system is fast enough and thus the time delay can be neglected, in this way time-delay-free differential equations are obtained such that the controller is time-delay-free. This approach needs further formal study to validate this assumption, and so far there is neither strict nor rigorous result that support this claim, when considering the full nonlinear telerobotic dyanmics. ii) In the second approach, the time delay is considered explicitly, however typically nonlinear dynamics is neglected and then linear models are used to derive time-delay-based control systems. The second approach ignores that the robots are nonlinear systems with strong nonlinear inertial couplings, and therefore controllers based on linear time-delay models render low performance. In this paper, the teleoperation of robots is modeled, including nonlinear dynamics in the continuous domain, without any time delay, and model-based nonlinear continuous second order sliding mode controllers are proposed which guarantee finite-time convergence. Thus, this approach attempts to propose a scheme for the second approach outlined above. The teleoperation system provides force reflection to the human operator, and a kinematic-based predictive display yields visual stimuli while the master robot yields kinesthetic feedback to the operator to allow planning better desired trajectories, including contact forces, in contrast to other predictive displays that have been proposed in the literature. Therefore, the theoretical foundations of finite-time convergent telecontrol system and its advantages are discussed.

Production systems are stopped due to malfunctions such as rotting equipment, imbalance of rotating parts, and high vibration, which leads to loss of customers, reduction of market share and unemployment of personnel. In this research, using the absorbing Markov process, a mathematical model is formulated to analyze the maintenance policy of the production process, through which one of the four states of new, old, or failure due to deterioration or sudden failure can be allocated to the machine. It is assumed that the machine changes from one state to another with different probabilities, which are determined using a discrete Markov chain. The different maintenance policies can be analyzed to minimize the average production cost. The mathematical model is obtained using discrete Markov chain equations, and the optimal maintenance and repair policy can be analyzed by considering all types of costs, including maintenance, production, and failure costs, so that the average cost of the production process can be minimized.

Various frequency bands of noises are contained in the actual signal. And it's difficult to eliminate the noise portion, which has a time delay and same spectrum with the original signal with conventional filtering methods. Based on the time delay and the multiplication delay characteristics of the fractional Fourier transform (FRFT), we put forward a FRFT time delay model, which can increase distance between the signal and the noise component. Through corresponding Fractional Fourier Transform to noise-containing signal, the distance between the signal and common frequency noises can be constantly increased within the transform domain, thus easily separating the noise component. The algorithm of the model can be simply deduced, easy realized and converged fast. In the experiment, we simulated the separating characteristics of the transform, and used the method to de-noise the grating signal. Compared with other traditional methods, we find that the FRFT acquired a better result.