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The purpose of this paper is to propose a predictive maintenance (PdM) system for hybrid degradation processes with continuous degradation and sudden damage to improve maintenance effectiveness.

The PdM system updates the degradation model using partial condition monitoring information based on degradation type judgment. In addition, an extended multi-step-ahead updating stopping condition is adopted for performance enhancement of the PdM system.

An extensive numerical investigation compares the performance of the PdM system with the corresponding preventive maintenance (PM) policy. By carefully choosing the updating stopping condition, the PdM policy performs better than the corresponding PM policy.

The proposed PdM system is applicable to single-unit systems. And the continuous degradation process should be well modeled by the stochastic linear degradation model (Gebraeel et al., 2009).

In literature, there are abundant studies on PdM policies for continuous degradation processes. However, research on hybrid degradation processes still focuses on condition-based maintenance policy and a PdM policy for a hybrid degradation process is still unreported. In this paper, a PdM system for hybrid degradation processes with continuous degradation and sudden damage is proposed. The PdM system decides PM schedules by fully utilizing the condition monitoring data of each specific product, and can hopefully improve maintenance effectiveness.

The purpose of this paper is to develop a risk‐based integrity model for the optimal replacement of offshore process components, based on the likelihood and consequence of failure arising from time‐dependent degradation mechanisms.

Risk is a combination of the probability of failure and its likely consequences. Offshore process component degradation mechanisms are modeled using Bayesian prior‐posterior analysis. The failure consequences are developed in terms of the cost incurred as a result of failure, inspection and maintenance. By combining the cumulative posterior probability of failure and the equivalent cost of degradations, the operational life‐risk curve is produced. The optimal replacement strategy is obtained as the global minimum of the operational risk curve.

The offshore process component degradation mechanisms are random processes. The proposed risk‐based integrity model can be used to model these processes effectively to obtain an optimal replacement strategy. Bayesian analysis can be used to model the uncertainty in the degradation data. The Bayesian posterior estimation using an M‐H algorithm converged to satisfactory results using 10,000 simulations. The computed operational risk curve is observed to be a convex function of the service life. Furthermore, it is observed that the application of this model will reduce the risk of operation close to an ALARP level and consequently will promote the safety of operation.

The developed model is applicable to offshore process components which suffer time‐dependent stochastic degradation mechanisms. Furthermore, this model is developed based on an assumption that the component degradation processes are independent. In reality, the degradation processes may not be independent.

The developed methodology and models will assist asset integrity engineers/managers in estimating optimal replacement intervals for offshore process components. This can reduce operating costs and resources required for inspection and maintenance (IM) tasks.

The frequent replacement of offshore process components involves higher cost and risk. Similarly, the late replacement of components may result in failure and costly breakdown maintenance. The developed model estimates an optimal replacement strategy for offshore process components suffering stochastic degradation. Implementation of the developed model improves component integrity, increases safety, reduces potential shutdown and reduces operational cost.

The purpose of this study to investigate acetaminophen (ACT) degradation efficiencies by using ozone/persulfate oxidation process in a batch reactor. In addition, the effects of various parameters on the ACT removal efficiency toward pathway inference of ACT degradation were investigated.

The experiments were in the 2 L glass vessels. Ozone gas with flow rate at 70 L.h⁻¹ was produced by ozone generator. After the adjustment of the pH, various dosages of persulfate (1, 3, 5, 7 and 9 mmol.L⁻¹) were then added to the 500 mL ACT-containing solution with 150 mg.L⁻¹ of concentration. Afterward, ozone gas was diffused in glass vessels. The solution after reaction flowed into the storage tank for the detection. The investigated parameters included pH and the amount of ozone and persulfate addition. For comparison of the ACT degradation efficiency, ozone/persulfate, ozone and persulfate oxidation in reactor was carried out. The ACT concentration using a HPLC system equipped with 2998 PDA detector was determined at an absorbance of 242 nm.

ACT degradation percentage by using ozone or persulfate in the process were at 63.7% and 22.3%, respectively, whereas O₃/persulfate oxidation process achieved degradation percentage at 91.4% in 30 min. Degradation efficiency of ACT was affected by different parameter like pH and addition of ozone or persulfate, and highest degradation obtained when pH and concentrations of persulfate and ozone was 10 and 3 mmol.L⁻¹ and 60 mg.L⁻¹, respectively. O₃, OH^• and SO⁴⁻ were evidenced to be the radicals for degradation of ACT through direct and indirect oxidation. Gas chromatography–mass spectrometer analysis showed intermediates including N-(3,4-dihydroxyphenyl) formamide, hydroquinone, benzoic acid, 4-methylbenzene-1,2-diol, 4-aminophenol.

This study provided a simple and effective way for degradation of activated ACT as emerging contaminants from aqueous solution. This way was conducted to protect environment from one of the most important and abundant pharmaceutical and personal care product in aquatic environments.

There are two main innovations. One is that the novel process is performed successfully for pharmaceutical degradation. The other is that the optimized conditions are obtained. In addition, the effects of various parameters on the ACT removal efficiency toward pathway inference of ACT degradation were investigated.

This paper aims to study peroxymonosulfate (PMS) activation in the ultraviolet (UV)/ozone process for toxic cyanide degradation from aqueous solution by a novel and simple method.

Photocatalytic degradation of cyanide (CN^-) was carried out using a bench-scale photoreactor. Optimization of the UV/ozone process for the highest removal of cyanide was obtained. The effect of parameters such as ozone concentration, PMS concentration, temperature, cations (Cu²⁺, Co²⁺ and Fe²⁺), cyanide concentration, anions (bicarbonate, carbonate, chloride, nitrite, nitrate and sulfate [SO42−]) and scavengers (ethanol [EtOH], humic acid, TBA and NaN₃) was investigated for CN- degradation.

Complete removal of 50 mg/L cyanide was obtained in 4 min in an ozone/UV/PMS process. The cyanide removal increased from 49.3% to 100% by adding the persulfate dosage up to 100 mg/L. The effect of various cations (II) on the cyanide degradation was enhanced in the order Cu²⁺ > Co²⁺ > Fe²⁺. Hydroxyl radical based on different radical quenchers such as salicylic acid proved as the main oxidizing radical for oxidation. The application of ozone/UV/PMS to treat wastewater containing cyanide shows high degradation efficiency.

The ozone/UV/PMS system could be a process for degradation and detoxification of cyanide.

This study provided a simple and effective method for degradation of cyanide from aqueous solution. This method was applicable to protect environment from a huge amount of toxic cyanide wastewater produced by different industrial processes.

The PMS activation is done via a simple and effective method, which is carried out with the ozone/UV system. There are two main innovations. One is that the novel catalytic role of bimetallic ions in the ozone reaction with cyanide and the further decomposition of intermediate products is investigated. The other is that the optimized conditions were obtained for the removal of cyanide as a water contaminant. Furthermore, predominant oxidizing species by PMS activation are identified.

The authors consider systems that generate damage to environment as they get older and degrade. The purpose of this paper is to develop an optimal condition-based maintenance strategy for such systems in situations where they have a finite operational time requirement. The authors determine simultaneously the optimal number of inspections and the threshold level of environmental damage which minimize the total expected cost over the considered finite time horizon.

The environmental degradation level is monitored through periodic inspections. The authors model the environmental degradation process due to the equipment’s degradation by the Wiener process. A mathematical model and a numerical procedure are developed. Numerical calculations are performed and the influence of the variation of key parameters on the optimal solution is investigated.

Numerical tests indicate that as the cost of the penalty related to the generation of an excess damage to environment increases, inspections should become more frequent and the threshold level should be lowered in order to favor preventive actions reducing the probability to pay the penalty.

Given the complexity of the cost function to be minimized, it is difficult to derive analytically the optimal solution. A numerical procedure is designed to obtain the optimal condition-based maintenance policy. Also, the developed model is based on the assumption that the degradation follows a process with stationary independent increments. This may not be appropriate for all types of degradation processes.

The proposed optimal maintenance policy may be relevant and very useful in the perspective of green operations. In fact, this paper offers to decision-makers a comprehensive approach to implement a green maintenance policy and to rapidly understand the net effect of the maintenance policy with respect to environmental regulation requirements.

The main contribution consists in the modeling and optimization of the condition-based maintenance policy over a finite time horizon. Indeed, existing condition-based maintenance models over an infinite time horizon are not applicable for systems with a finite operational time requirement.

The purpose of this paper is to highlight the need for degradation data in order to improve the reliability and the mean residual life estimation of a specific item of equipment and to adapt the preventive maintenance tasks accordingly.

An initial reliability model which uses a degradation-based reliability model that is built from the collection of hitting times of a failure threshold. The proposed maintenance model is based on the cost/availability criterion. The estimation of both reliability and optimum time for preventive maintenance are updated with all new degradation data that are collected during operating time.

An improvement for the occurrences of maintenance tasks which minimizes the mean cost per unit of time and increases the availability.

Inspection tasks to measure the degradation level should be realized at least one time for each item of equipment at a specific time determined by the proposed methodology.

The introduction of a criterion which helps the maintainer to decide to postpone or not the preventive replacement time depending on the measured degradation level of a specific item of equipment.

The purpose of this paper is to analyze the dependent competing failure reliability of harmonic drive (HD) with strength failure and degradation failure.

Based on life tests and stiffness degradation experiments, Wiener process is used to establish the accelerated performance degradation model of HD. Model parameter distribution is estimated by Bayesian inference and Markov Chain Monte Carlo (MCMC) and stiffness degradation failure samples are obtained by a three-step sampling method. Combined with strength failure samples of HD, copula function is used to describe the dependence between strength failure and stiffness degradation failure.

Strength failure occurred earlier than degradation failure under high level accelerated condition; degradation failure occurred earlier than strength failure under medium- or low-level accelerated condition. Gumbel copula is the optimum copula function for dependence modeling of strength failure and stiffness degradation failure. Dependent competing failure reliability of HD is larger than independent competing failure reliability.

The reliability evaluation method of dependent competing failure of HD with strength failure and degradation failure is first proposed. Performance degradation experiments during accelerated life test (ALT), step-down ALT and life test under rated condition are conducted for Wiener process based step-down accelerated performance degradation modeling.

The purpose of this paper is the reliability analysis for systems with dependent gamma degradation process and Weibull failure time.

Consider a life testing experiment in which a sample of n devices starts to operate at t=0 and the data are available on failure time and failure-evolving process on each individual, called in some contents wear or degradation. Ignoring the between performance characteristics dependency structure may lead us to different reliability estimations, while the dependency justly exists. In previous research, dependency between the degradation process and hard failure time has been studied in limited detail (special closed form expression). Thereafter, the dependency between two degradation processes with the same structure (gamma process) in a system is considered using the copula function.

The results indicate that ignoring the dependency structure may lead us to different reliability estimations while the dependency justly exists.

This study gives some contributions that evaluate reliability metrics with more than one failure mechanism that may not be independent and possibly follow a different distribution function. The authors have used the copula function as a basis to develop a proposal model and analysis methods. In addition, the authors discussed the identifiability of the copula. Finally, simulation data were used to review the suggested approach.

In some environments, the failure rate of a system depends not only on time but also on the system condition, such as vibrational level, efficiency and the number of random shocks, each of which causes failure. In this situation, systems can keep working, though they fail gradually. So, the purpose of this paper is modeling multi-state system reliability analysis in capacitor bank under fatal and nonfatal shocks by a simulation approach.

In some situations, there may be several levels of failure where the system performance diminishes gradually. However, if the level of failure is beyond a certain threshold, the system may stop working. Transition from one faulty stage to the next can lead the system to more rapid degradation. Thus, in failure analysis, the authors need to consider the transition rate from these stages in order to model the failure process.

This study aims to perform multi-state system reliability analysis in energy storage facilities of SAIPA Corporation. This is performed to extract a predictive model for failure behavior as well as to analyze the effect of shocks on deterioration. The results indicate that the reliability of the system improved by 6%.

The results of this study can provide more confidence for critical system designers who are engaged on the proper system performance beyond economic design.

This research fills a gap in process science by defining and explaining entropy and the increase of entropy in processes.

This is a theoretical treatment that begins with a conceptual understanding of entropy in thermodynamics and information theory and extends it to the study of degradation and improvement in a transformation process.

A transformation process with three inputs: demand volume, throughput and product design, utilizes a system composed of processors, stores, configuration, human actors, stored data and controllers to provide a product. Elements of the system are aligned with the inputs and each other with a purpose to raise standard of living. Lack of alignment is entropy. Primary causes of increased entropy are changes in inputs and disordering of the system components. Secondary causes result from changes made to cope with the primary causes. Improvement and innovation reduce entropy by providing better alignments and new ways of aligning resources.

This is the first detailed theoretical treatment of entropy in a process science context.