Correction: Prediction of remaining useful life (RUL) of Komatsu excavator under reliability analysis in the Weibull-frailty model.

[This corrects the article DOI: 10.1371/journal.pone.0236128.].

Spare-part management in a heterogeneous environment.

Spare-part management has a significant effect on the productivity of mining equipment. The required number of spare parts can be estimated using failure and repair data collected under the name of reliability data. In the mining industry, failure and repair times are decided by the operational environment, rock properties, and the technical and functional behavior of the system. These conditions are heterogeneous and may change significantly from time to time. Such heterogeneity can change equipment's reliability performance and, consequently, the required number of spare parts. Hence, it is necessary for effective spare-part planning to check the heterogeneity among the reliability data. After that, if needed, such heterogeneity should be modeled using an adequate statistical model. Heterogeneity can be categorized into observed and unobserved caused by risk factors. Most spare-part estimation studies ignore the effect of heterogeneity, which can lead to unrealistic estimations. In this study, we introduce the application of a frailty model for modeling the effect of observed and unobserved risk factors on the required number of spare parts for mining equipment. Studies indicate that ignoring the effect of unobservable risk factors can cause a significant bias in estimation.

Prediction of remaining useful life (RUL) of Komatsu excavator under reliability analysis in the Weibull-frailty model.

It is an essential task to estimate the remaining useful life (RUL) of machinery in the mining sector aimed at ensuring the production and the customer's satisfaction. In this study, a conceptual framework was used to determine the RUL under the reliability analysis in a frailty model. The proposed framework was implemented on a Komatsu PC-1250 excavator from the Sungun copper mine. Also, the Weibull-frailty model was selected to describe the failure behavior and compare it with the classical-exponential model. The frailty model was also used to evaluate the impact of unobserved environmental conditions on the RUL values. Both applied models were fitted to the obtained data from 80 operational hours of the Komatsu PC-1250 excavator. Plotting the results from the reliability analysis of two models demonstrated that the mine system with the frailty model performs better than the classical model before reaching the reliability of 80%. Besides, the frailty model shows a coherent with the operational time of the excavator, while the classical model demonstrates a sinusoid variation. The obtained results may be used for the development of maintenance, preventive repairs planning, and the spare parts replacement intervals.

Chaos-Based Analysis of Heart Rate Variability Time Series in Obstructive Sleep Apnea Subjects.

Obstructive sleep apnea (OSA) is a common disorder which can cause periodic fluctuations in heart rate. To diagnose sleep apnea, some studies analyze electrocardiogram (ECG) signals by adopting chaos-based analysis. This research is going to specifically focus on whether it is possible to use chaos-based analysis of heart rate variability (HRV) signals rather than using chaotic analysis of ECG signals to diagnose OSA. While conventional studies mostly use chaos-based analysis of ECG signals to detect OSA, here, we apply correlation dimension (CD) as a chaotic index to analyze HRV data in OSA patients. For this purpose, 17 patients with OSA and 9 healthy individuals referred to a sleep clinic in Isfahan/Iran are studied, and their HRV time series were extracted from 1-h ECG signals recorded overnight. The preliminary step to calculate CD is phase-space reconstruction of the system based on HRV time series. Corresponding parameters, including embedding dimension and lag time, are estimated optimally using enhanced related methods, and then CD is calculated using Grassberger-Procaccia algorithm. Moreover, to evaluate our results, detrended fluctuation analysis (DFA), one of the well-known nonlinear methods in HRV analysis to detect OSA, is also applied to our data and the result is compared with those obtained from CD analysis of HRV. CD index with P < 0.005 indicates a significant difference in nonlinear dynamics of HRV signals detected from OSA patients and healthy individuals.

Asymptotic stabilization of a class of nonlinear systems with long input delay in the presence of disturbance.

Asymptotic stabilization of a class of nonlinear systems with known constant long input delay is addressed in the presence of external disturbance by applying sliding mode control method. Modified prediction variable scheme is employed to compensate long delays in the input, where conventional prediction variable approaches cannot be employed. This is mainly due to the fact that the external disturbance appears in the prediction variable, which renders the controller dependent on the external disturbance. In order to tackle this problem, the nonlinear disturbance observer based predictor is used. A suitable disturbance observer is designed to estimate the external disturbance that appears in the prediction variable. Respected to some existing results, the prediction-based control for more general class of the nonlinear systems in the presence of external disturbance is the main contribution of this paper. Actuator and sensor delays exist in the most common dynamic systems. So, the proposed control scheme can be employed in many conventional systems. The simulation results indicate the robustness and efficiency of the proposed controller.

Fault tree analysis of failure cause of crushing plant and mixing bed hall at Khoy cement factory in Iran.

Evaluating and analyzing the risk in the mining industry is a new approach for improving the machinery performance. Reliability, safety, and maintenance management based on the risk analysis can enhance the overall availability and utilization of the mining technological systems. This study investigates the failure occurrence probability of the crushing and mixing bed hall department at Azarabadegan Khoy cement plant by using fault tree analysis (FTA) method. The results of the analysis in 200 h operating interval show that the probability of failure occurrence for crushing, conveyor systems, crushing and mixing bed hall department is 73, 64, and 95 percent respectively and the conveyor belt subsystem found as the most probable system for failure. Finally, maintenance as a method of control and prevent the occurrence of failure is proposed.

A coordinated MIMO control design for a power plant using improved sliding mode controller.

For the participation of the steam power plants in regulating the network frequency, boilers and turbines should be co-ordinately controlled in addition to the base load productions. Lack of coordinated control over boiler-turbine may lead to instability; oscillation in producing power and boiler parameters; reduction in the reliability of the unit; and inflicting thermodynamic tension on devices. This paper proposes a boiler-turbine coordinated multivariable control system based on improved sliding mode controller (ISMC). The system controls two main boiler-turbine parameters i.e., the turbine revolution and superheated steam pressure of the boiler output. For this purpose, a comprehensive model of the system including complete and exact description of the subsystems is extracted. The parameters of this model are determined according to our case study that is the 320MW unit of Islam-Abad power plant in Isfahan/Iran. The ISMC method is simulated on the power plant and its performance is compared with the related real PI (proportional-integral) controllers which have been used in this unit. The simulation results show the capability of the proposed controller system in controlling local network frequency and superheated steam pressure in the presence of load variations and disturbances of boiler.

Robust synchronization of a class of uncertain chaotic systems based on quadratic optimal theory and adaptive strategy.

This paper presents a chaos synchronization method for a class of uncertain chaotic systems using the combination of an optimal control theory and an adaptive strategy. A quadratic optimal regulator and an adaptive control are used to represent the controller's structure. The asymptotic stability of the corresponding error dynamical system is guaranteed through Lyapunov stability analysis. The proposed controller is employed in two uncertain chaotic Lu systems, and their promising performances are illustrated.