Complex Repairable Systems Research Articles

Fiducial Approach for the Storage Reliability Assessment of Complex Repairable Systems

Fiducial Approach for the Storage Reliability Assessment of Complex Repairable Systems

Crosstalk between DNA Damage Repair and Metabolic Regulation in Hematopoietic Stem Cells.

Self-renewal and differentiation are two characteristics of hematopoietic stem cells (HSCs). Under steady physiological conditions, most primitive HSCs remain quiescent in the bone marrow (BM). They respond to different stimuli to refresh the blood system. The transition from quiescence to activation is accompanied by major changes in metabolism, a fundamental cellular process in living organisms that produces or consumes energy. Cellular metabolism is now considered to be a key regulator of HSC maintenance. Interestingly, HSCs possess a distinct metabolic profile with a preference for glycolysis rather than oxidative phosphorylation (OXPHOS) for energy production. Byproducts from the cellular metabolism can also damage DNA. To counteract such insults, mammalian cells have evolved a complex and efficient DNA damage repair (DDR) system to eliminate various DNA lesions and guard genomic stability. Given the enormous regenerative potential coupled with the lifetime persistence of HSCs, tight control of HSC genome stability is essential. The intersection of DDR and the HSC metabolism has recently emerged as an area of intense research interest, unraveling the profound connections between genomic stability and cellular energetics. In this brief review, we delve into the interplay between DDR deficiency and the metabolic reprogramming of HSCs, shedding light on the dynamic relationship that governs the fate and functionality of these remarkable stem cells. Understanding the crosstalk between DDR and the cellular metabolism will open a new avenue of research designed to target these interacting pathways for improving HSC function and treating hematologic disorders.

Liquiritigenin reverses skin aging by inhibiting UV-induced mitochondrial uncoupling and excessive energy consumption.

The accumulation of reactive oxygen species (ROS) generated by UV radiation can lead to lipid, protein, nucleic acid, and organelle damage, one of the core mechanisms mediating skin aging. In the photoaging process, how ROS drives the imbalance of the body's complex repair system to induce senescence-like features is not fully understood. We irradiated human epidermal keratinocytes with 12 J/cm2 of UVA to establish an in vitro photoaging model. Then we employed whole-transcriptome sequencing and O2K mitochondrial function assay to reveal the photoprotective mechanisms of liquiritigenin (LQ). We found that skin reduces endogenous ROS by promoting mitochondrial oxidative phosphorylation uncoupling in response to UVA-induced damage. However, this also causes excessive consumption and idling of nutrients, leading to the inhibition of cell proliferation, and ultimately accelerating the skin aging process. Here, we demonstrated that LQ can reduce stress in keratinocytes, increase oxidative phosphorylation and ATP production efficiency, and block the massive loss of skin nutrients and net energy stress. Furthermore, LQ can promote collagen synthesis and keratinocyte proliferation through the PI3K-AKT pathway, thereby reversing photoaging. This work provides a new skin aging mechanism and solution strategy with high clinical translation value.

Stochastic analysis of a complex repairable system comprises two subsystems in series configuration via multi-repair strategy

Stochastic analysis of a complex repairable system comprises two subsystems in series configuration via multi-repair strategy

Performance Assessment of Complex System Under the k-out-of-n: G Type Configuration with k Consecutive Degraded States through the Copula Repair Approach

This paper is the stochastic analysis of a complex repairable system comprising of subsystems in a series arrangement under the [Formula: see text]-out-of-[Formula: see text]: [Formula: see text] type configuration. Both of the subsystems are in series arrangement and having auto transfer switches when some unit fails. Subsystem 1 is supposed to work under the [Formula: see text]-out-of-[Formula: see text]: [Formula: see text], scheme, and subsystem 2 which has four indistinguishable units in parallel arrangement with an auto switch functioning under the 1-out-of-4: [Formula: see text] scheme. A catastrophic failure is characterized as causing damage to the entire system. Units’ failure, switch failures, and catastrophic failure rates are constant, but repair rates are treated as variables with two types of distributions: general distribution and copula distribution. The model is analyzed using a supplementary variables approach, with probabilistic measures such as availability, reliability, MTSF, and profit functions derived.

Mathematical model for analysing availability of threshing combine machine under reduced capacity

Obtaining system availability in an engineering design is trickish and challenging, especially when there is a reduction in capacity; however, it supports system maintainability. In this paper, a mathematical model for finding the availability under the reduced capacity has been proposed using the Chapman Kolmogorov approach with the help of transition diagrams associated with various possible combinations of probabilities. The paper observes the most critical subsystem by selecting variable failure and repair rates from different subsystems. It deals with the sensitivity analysis of a complex repairable threshing combined machine comprising subsystems in a series configuration and the threshing machine consisting of 21 subsystems. The device works in total capacity when the threshing drum and feeding Hooper work in the complete state, and the concave subsystem and blower work with reduced power. This study dealt with uncertain data and was analyzed analytically using a complex repairable system. The availability of the entire machine has been investigated analytically, and various availability indices such as subsystems extruder have been computed and reported. The study discovered that subsystem extruder has the most impact on some subsystems? overall system availability.

DNA damage and repair in the hematopoietic system.

Although hematopoietic stem cells (HSCs) in the bone marrow are in a state of quiescence, they harbor the self-renewal capacity and the pluripotency to differentiate into mature blood cells when needed, which is key to maintain hematopoietic homeostasis. Importantly, HSCs are characterized by their long lifespan ( e. g., up to 60 months for mice), display characteristics of aging, and are vulnerable to various endogenous and exogenous genotoxic stresses. Generally, DNA damage in HSCs is endogenous, which is typically induced by reactive oxygen species (ROS), aldehydes, and replication stress. Mammalian cells have evolved a complex and efficient DNA repair system to cope with various DNA lesions to maintain genomic stability. The repair machinery for DNA damage in HSCs has its own characteristics. For instance, the Fanconi anemia (FA)/BRCA pathway is particularly important for the hematopoietic system, as it can limit the damage caused by DNA inter-strand crosslinks, oxidative stress, and replication stress to HSCs to prevent FA occurrence. In addition, HSCs prefer to utilize the classical non-homologous end-joining pathway, which is essential for the V(D)J rearrangement in developing lymphocytes and is involved in double-strand break repair to maintain genomic stability in the long-term quiescent state. In contrast, the base excision repair pathway is less involved in the hematopoietic system. In this review, we summarize the impact of various types of DNA damage on HSC function and review our knowledge of the corresponding repair mechanisms and related human genetic diseases.

Modelling the Maintenance of Complex Repairable Systems based on Reliability by Comparing the Proportional Intensity Model and the Generalized Proportional Intensity Model

Modelling the Maintenance of Complex Repairable Systems based on Reliability by Comparing the Proportional Intensity Model and the Generalized Proportional Intensity Model

Performance Analysis of Complex Manufacturing System using Petri Nets Modeling Method

The Petri nets modeling method is a powerful tool for the performance analysis of industrial systems. The main factor which makes it more effective among the various popular simulation methods is the ability to deal with the real working conditions. The data obtained from such a manufacturing system is generally full of uncertainties and the Petri nets modeling method deals with this data to reflect the real behavioral pattern of different sub-systems installed in the plant. The Petri nets-based simulation method provides the availability of the sub-systems for a long time period by running the plant in virtual manners. The results obtained through the analysis can be utilized to identify those sub-systems which highly affect the system availability and separate maintenance planning for each sub-system can reduce the production loss due to unavailability of any sub-system for performing its intended task. The proposed methodology has been demonstrated in this paper using a complex repairable manufacturing system.

Performance assessment of the complex repairable system with n-identical units under (k-out-of-n: G) scheme and copula linguistic repair approach

PurposeThis paper analyzed a complex system consisting n-identical units under a k-out-of-n: G; configuration via a new method which has not been studied by previous researchers. The computed results are more supportable for repairable system performability analysis.Design/methodology/approachIn this paper, the authors have analyzed a complex system consisting n-identical units under a k-out-of-n: G; configuration via a new method which has not been studied by previous researchers. The supplementary variable technique has employed for analyzing the performance of the system.FindingsReliability measures have been computed for different types of configuration. It generalized the results for purely series and purely parallel configurations.Research limitations/implicationsThis research may be beneficial for industrial system performances whereas a k-out-of-n-type configuration exists.Practical implicationsNot sure as it is a theoretical assessment.Social implicationsThis research may not have social implications.Originality/valueThis work is the sole work of authors that have not been communicated to any other journal before.

Reliability analysis of a complex repairable system in series configuration with switch and catastrophic failure using copula repair

This paper describes an analytical framework for in-depth investigation of a complex system consisting of two subsystems (namely L and M) in series configuration. Subsystem-L is composed of three identical units in parallel configuration that are working under 1-out-of-3: G policy, while subsystem-M has two non-identical units that are working under 1-out-of-2: G: policy. In subsystem-M, priority in operation is given to M1 unit whereas M2 unit put into cold standby mode if not in use. Moreover, both the subsystems are connected with controllers that may be perfect or imperfect at the time of need. We have considered a catastrophic failure due to frequent change in environmental conditions or man-made disruption. Failure rates of units in both the subsystems are constant and assumed to follow exponential distribution, but their repair supports two types of distributions namely general distribution and Gumbel-Hougaard family copula distribution. The system is studied by using the supplementary variable technique, Laplace transformation and Gumbel-Hougaard family of copula to derive differential equations and obtain important reliability indexes such as availability of the system, reliability of the system and profit analysis. The results have shown by tables and graphs. Conclusive part have been discussed in the last section of this study.

Maximising availability of complex repairable systems and flexible selection of performance parameter using PSO

In this research study, particle swarm optimisation (PSO) has been implemented for availability analysis of a complex repairable industrial system namely mash kettle of an existing brewery plant. PSO algorithm is computationally simple and efficient. The mash kettle system is modelled structurally representing its various constituent elements/components and their interconnections. Probability relationship of different feasible state are generated using the transition diagram. Performance analysis is done to observe the criticality of the constituent elements/components. The particle swarm optimisation algorithm provides a varied and wide range of performance measures of various elements/components for a predetermined optimised value of the availability of the system. PSO algorithm is validated by comparing with genetic algorithm and Markov methods for the results of optimal availability. The consequences of this paper will be beneficial for the maintenance engineer and plant staff to accomplish best attainable system performance/availability and to plan appropriate maintenance strategies.

Reliability analysis of a complex repairable system in series configuration with switch and catastrophic failure using copula repair

This paper describes an analytical framework for in-depth investigation of a complex system consisting of two subsystems (namely L and M) in series configuration. Subsystem-L is composed of three identical units in parallel configuration that are working under 1-out-of-3: G policy, while subsystem-M has two non-identical units that are working under 1-out-of-2: G: policy. In subsystem-M, priority in operation is given to M1 unit whereas M2 unit put into cold standby mode if not in use. Moreover, both the subsystems are connected with controllers that may be perfect or imperfect at the time of need. We have considered a catastrophic failure due to frequent change in environmental conditions or man-made disruption. Failure rates of units in both the subsystems are constant and assumed to follow exponential distribution, but their repair supports two types of distributions namely general distribution and Gumbel-Hougaard family copula distribution. The system is studied by using the supplementary variable technique, Laplace transformation and Gumbel-Hougaard family of copula to derive differential equations and obtain important reliability indexes such as availability of the system, reliability of the system and profit analysis. The results have shown by tables and graphs. Conclusive part have been discussed in the last section of this study.

Risk-Based Threshold on Intensity Function of Repairable Systems: A Case Study on Aero Engines

Maintenance, repair and overhaul (MRO) facilities deal with situations where repairable systems and its components are required to be designated as high failure rate components (HFRCs). The shortlisted HFRCs are then selected for reliability improvement. The procedure of short listing components as HFRCs is commonly based on experts’ field experience or number of failures. In case of organizations dealing with complex and critical repairable systems like military aviation (MA) and nuclear industries, the subjectivity in the short listing of HFRCs can lead to prolonged unavailability of equipment and may incur financial loss. Thus, a scientific methodology is required to be developed for HFRC designation. The paper develops a methodology for HFRC designation through risk-based threshold on intensity function by considering combat aircraft engines as a case. To develop the threshold methodology, the paper uses generalized renewal process (GRP) for multiple repairable systems (MRS) considering both corrective and preventive maintenance as imperfect. The proposed methodology is duly validated with the help of field failure data of two variants of the same aero engine of a particular combat aircraft. The developed methodology in this paper is highly inspired by the problems faced by the various industries while operating the repairable systems and can be extended for systems which undergo periodic maintenance, repair and overhaul.

Age Based Overhaul Policy for Multiple Repairable Systems with Imperfect Maintenance: Case Study of Aero Engines

Reliability analysis of complex multiple repairable systems (MRS) such as aero engines, rolling stocks and nuclear power plants has always been an area of interest for the research fraternity. An appropriate age based overhaul maintenance policy for such systems can provide impetus to the operations. The paper proposes two different age based maintenance policies; Policy-I and Policy-II, to evaluate the overhaul time of an aero engine, where Policy-I considers MRS with imperfect corrective maintenance (CM), whereas Policy-II examines MRS with both imperfect CM and preventive maintenance (PM). The paper then provides a spare parts estimation model for both the policies. The developed policies and spares parts model are validated by considering field failure data of aero engines as a case and the obtained results are compared with the existing time based maintenance policy used for aero engines. The paper recommends the best policy to be used for MRS in general and the considered case in particular.

The PafBC-mediated response sensitizes a bistable DNA damage response in Mycobacteria

Due to the genotoxically challenging environments in which they live in, Mycobacteria have a complex DNA damage repair system that is governed by two major DNA damage responses, namely, the LexA/RecA-dependent response and the newly characterized PafBC-mediated response (Müller et al., 2018). The LexA/RecA-dependent response is a well-known bistable response found in different types of bacteria, and the Mycobacteria-specific PafBC-mediated response interacts with and modifies the LexA/RecA-dependent response (Müller et al., 2018). The interaction between the LexA/RecA-dependent response and the PafBC-mediated response has not been characterized mathematically. Our analysis shows that the addition of the PafBC-mediated response sensitizes the overall DNA damage response, effectively lowering the DNA damage rate threshold for activation.

Adaptive stochastic-filter-based failure prediction model for complex repairable systems under uncertainty conditions

Dynamical reliability assessment and failure prediction are effective tools for ensuring the efficiency, availability, and safety of repairable systems. To achieve better assessment performance, accurate modeling failure recurrence data are the core of prediction approaches. However, because of the uncertainties from the environmental conditions and repair activities, the failure counting model is usually not well established. To solve this problem, in this paper, we propose an adaptive recursive-filter-based dynamical failure prediction approach for complex repairable systems. First, based on the framework of the state space model, a fusion model that fuses Brownian motion into a nonhomogeneous Poisson process is proposed to characterize failure process under multiple uncertainty conditions. Then, an adaptive statistical inference method based on a Bayesian recursive filter and the EM algorithm is derived to update the model parameters and estimate the initial states adaptively. To verify the effectiveness of the proposed approach, a real gas pipeline compressors reliability prediction problem was implemented.

Availability Analysis of Machining System with Common Cause Failure, Inspection and Imperfect Repair

This investigation is concerned with the availability prediction of a non-Markovian model for the multi-component complex repairable manufacturing system. The system is prone to multiple types of failures, either due to an individual or common cause failure. The system can also fail catastrophically which may occur due to the incorrect start of the system or due to some errors by an untrained and inexperienced operator. When a system failure occurs, the recovery of the system is done by the inspection/repair process. The stochastic analysis is carried out using the supplementary variable technique and Laplace transformation for evaluating the system state probabilities. The performance indices such as availability, reliability, MTTF, MTTR, and cost–benefit analysis of the system are established analytically and then validated by taking a numerical example.

Optimization of a multilevel integrated preventive maintenance scheduling mathematical model using genetic algorithm

ABSTRACT This paper proposes a preventive maintenance scheduling model to optimize the cost and improve the effective age of machines in complex repairable systems. The objective of the developed model is to minimize the total maintenance costs while maintaining a defined level of availability and reliability. The maintenance costs include random failure cost, repair cost, replacement cost, and total planned downtime cost. Multilevel preventive maintenance actions such as inspection, repair, and replacement are considered through the whole planning horizon. A genetic algorithm was developed using a MATLAB program to provide a near-optimal solution for the optimization model. The proposed mathematical model was applied to a Chloride Sodium factory and the results show a reduction in the total maintenance cost by 34%.

Maximizing availability of complex repairable systems and Flexible selection of performance parameter using PSO

In this research study, particle swarm optimisation (PSO) has been implemented for availability analysis of a complex repairable industrial system namely mash kettle of an existing brewery plant. PSO algorithm is computationally simple and efficient. The mash kettle system is modelled structurally representing its various constituent elements/components and their interconnections. Probability relationship of different feasible state are generated using the transition diagram. Performance analysis is done to observe the criticality of the constituent elements/components. The particle swarm optimisation algorithm provides a varied and wide range of performance measures of various elements/components for a predetermined optimised value of the availability of the system. PSO algorithm is validated by comparing with genetic algorithm and Markov methods for the results of optimal availability. The consequences of this paper will be beneficial for the maintenance engineer and plant staff to accomplish best attainable system performance/availability and to plan appropriate maintenance strategies.