Purpose
The purpose of this paper is to demonstrate how Internet of Things (IoT) technology can enable highly distributed elevator equipment servicing by using remote-monitoring technology to ...facilitate a shift from traditional corrective maintenance (CM) and time-based maintenance (TBM) to more predictive, condition-based maintenance (CBM) in order to achieve various benefits.
Design/methodology/approach
Literature review indicates that CBM has advantages over conventional CM and TBM from a theoretical perspective, but it depends on continuous monitoring enhancement via advanced IoT technology. An in-depth case study was carried out to provide practical evidence that IoT enables elevator firms to achieve CBM.
Findings
From a theoretical perspective, the CBM of elevators makes business sense. The challenges lie in data collection, data analysis and decision making in real-world business contexts. The main findings of this study suggest that CBM can be commercialized via IoT in the case of elevators and would improve the safety and reliability of equipment. It would, thus, make sense from technological, process and economic perspectives.
Practical implications
Our longitudinal real-world case study demonstrates a practical way of making the CBM of elevators widespread. Integrating IoT and other advanced technology would improve the safety and reliability of elevator equipment, prolong its useful life, minimize inconvenience and business interruptions due to equipment downtime and reduce or eliminate major repairs, thus greatly reducing maintenance costs.
Originality/value
The main contribution of this paper lies in the empirical demonstration of the benefits and challenges of CBM via IoT relative to conventional CM and TBM in the case of elevators. The authors believe that this study is timely and will be valuable to firms working on similar research or commercialization strategies.
High reliability (and availability) with low life-cycle costs are general goals for all maintenance programs. An effective preventative maintenance (PM) regime balances the cost of maintenance with ...the elimination of degradation failure mechanisms through preemptive intervention. Failures in operation require corrective maintenance (CM) and are often the most expensive to repair. PM is conducted to reduce the probability of specific failures and hence reduce the CM burden and cost. However, PM actions can themselves introduce additional damage and failure mechanisms. Determining the optimum PM frequency requires these competing factors to be quantified. Too little PM allows sub-systems and components to wear out, decreasing overall system reliability. Conversely, too much PM will introduce an inordinate amount of damage (and failure mechanisms) that decreases system reliability, along with increasing the overall cost. To optimize maintenance, the failure modes of the individual components need to be analyzed and the maintenance program matched to how the equipment fails, how predictable the failure is and what the overall impact the failure has to the mission of the system it is a part of.
Traditionally, generator maintenance scheduling has been implemented using highly conservative maintenance policies based on manufacturing specifications and engineering expertise on the type of ...generators. However, recent advances in sensor technology, signal processing, and embedded online diagnosis provide more unit-specific information on the degradation characteristics of the generators. In this two-paper study, we propose a new generation maintenance framework that integrates the sensor-driven predictive maintenance technologies with optimal maintenance scheduling models. In Part I, we propose a new mixed-integer optimization model for generation maintenance scheduling, which effectively incorporate the dynamic information of generators' health and maintenance cost provided by the Bayesian prognostic models. In Part II, we propose a framework that extends the maintenance model presented herein, and consider the effects of maintenance on network operation by coordinating generator maintenance schedules with the unit commitment and dispatch decisions. We introduce new reformulations and efficient algorithms for solving large-scale instances of the proposed maintenance scheduling model. Extensive computational studies using real-world degradation data demonstrates the effectiveness of the new framework.
•Proposing maintenance schedules for cost-effectiveness of offshore wind systems in Taiwan.•Determining optimal individual and grouping maintenance schedules.•Considering various parameters such as ...weather condition, maintenance duration, power loss.•Investigating impact of location on effectiveness of maintenance schedules.•Saving 4.56% of maintenance cost over the baseline maintenance schedule.
This paper proposes approaches to determine the optimal maintenance schedules for offshore wind system such that maintenance cost is minimized. The proposed approaches aim to provide the optimal maintenance schedules for each component using a dynamic approach and for multiple components by proposing an algorithm to optimize grouping multiple maintenance schedules. To increase the accuracy of estimating the maintenance cost in the proposed approaches, a number of impacted parameters such as system reliability, cost–effective, weather condition, maintenance duration, power generation loss during maintenance, market electricity price and offshore wind system location are all considered. Firstly, a dynamic maintenance strategy is proposed to determine an optimal individual maintenance schedule for each component in an offshore wind turbine, in which the failure rate and maintenance cost are critical parameters for the cost model. Then, a grouping maintenance optimization strategy is proposed to determine the grouping maintenance schedule which groups multiple maintenance activities to a grouping maintenance activity. The results indicate that the proposed individual maintenance schedule and grouping maintenance schedule may save an average of 2.33% and 4.56% on maintenance cost over baseline maintenance schedule.
From the mistakes of industrial past, from the needs of today's manufacturing industry, from the knowledge accumulations of theoreticians, researchers and practitioners in the field presented in ...scientifical papers and reviews, the future directions of R & D in the field of maintenance were outlined in this paper.
Purpose - The purpose of this paper is to provide an overview of research and development in the measurement of maintenance performance. It considers the problems of various measuring parameters and ...comments on the lack of structure in and references for the measurement of maintenance performance. The main focus is to determine how value can be created for organizations by measuring maintenance performance, examining such maintenance strategies as condition-based maintenance, reliability-centred maintenance, e-maintenance, etc. In other words, the objectives are to find frameworks or models that can be used to evaluate different maintenance strategies and determine the value of these frameworks for an organization.Design methodology approach - A state-of-the-art literature review has been carried out to answer the following two research questions. First, what approaches and techniques are used for maintenance performance measurement (MPM) and which MPM techniques are optimal for evaluating maintenance strategies? Second, in general, how can MPM create value for organizations and, more specifically, which system of measurement is best for which maintenance strategy?Findings - The body of knowledge on maintenance performance is both quantitatively and qualitatively based. Quantitative approaches include economic and technical ratios, value-based and balanced scorecards, system audits, composite formulations, and statistical and partial maintenance productivity indices. Qualitative approaches include human factors, amongst other aspects. Qualitatively based approaches are adopted because of the inherent limitations of effectively measuring a complex function such as maintenance through quantitative models. Maintenance decision makers often come to the best conclusion using heuristics, backed up by qualitative assessment, supported by quantitative measures. Both maintenance performance perspectives are included in this overview.Originality value - A comprehensive review of maintenance performance metrics is offered, aiming to give, in a condensed form, an extensive introduction to MPM and a presentation of the state of the art in this field.
This paper investigates the problem of optimally integrating production quality and condition-based maintenance in a stochastically deteriorating single- product, single-machine production system. ...Inspections are periodically performed on the system to assess its actual degradation status. The system is considered to be in 'fail mode' whenever its degradation level exceeds a predetermined threshold. The proportion of non-conforming items, those that are produced during the time interval where the degradation is beyond the specification threshold, are replaced either via overtime production or spot market purchases. To optimise preventive maintenance costs and at the same time reduce production of non-conforming items, the degradation of the system must be optimally monitored so that preventive maintenance is carried out at appropriate time intervals. In this paper, an integrated optimisation model is developed to determine the optimal inspection cycle and the degradation threshold level, beyond which preventive maintenance should be carried out, while minimising the sum of inspection and maintenance costs, in addition to the production of non-conforming items and inventory costs. An expression for the total expected cost rate over an infinite time horizon is developed and solution method for the resulting model is discussed. Numerical experiments are provided to illustrate the proposed approach.
•A novel OM model is proposed for multi-unit series systems subject to random production waits.•The arrival and the duration of the production waits are both stochastic.•Maintenance Gravity Window ...(MGW) is developed to group the PM activities of the units.•MGW is suitable for the circumstance the pre-scheduled PM time for each unit is a time window.•The MGW based OM policy is more cost-effective than the other two maintenance policies.
This paper proposes an Opportunistic Maintenance (OM) scheduling model for the multi-unit serial system subject to random production waits. With the stochastic nature of production waits involved, the pre-scheduled Preventive Maintenance (PM) time for each unit changes from a specific time to a time window. To effectively group the PM activities of the units with a series of time windows, a new concept called Maintenance Gravity Window (MGW) is introduced and then a novel MGW based OM policy is developed. Whenever one of the units reaches its PM threshold or accepts a production wait to conduct PM, a PM opportunity for the system arises. At that time, all the other units, which also reach their own PM thresholds or accept this production wait, or whose gravity related to the current PM opportunity is within the MGW, will be preventively maintained together with this unit. The optimal MGW for the system is obtained by minimizing the total maintenance cost per unit time throughout the PM scheduling horizon. Finally, numerical examples and comparisons are illustrated to show the cost-effectiveness of the proposed MGW based OM policy.
Insomnia Buysse, Daniel J
JAMA : the journal of the American Medical Association,
02/2013, Volume:
309, Issue:
7
Journal Article
Peer reviewed
Open access
Insomnia is one of the most prevalent health concerns in the population and in clinical practice. Clinicians may be reluctant to address insomnia because of its many potential causes, unfamiliarity ...with behavioral treatments, and concerns about pharmacologic treatments.
To review the assessment, diagnosis, and treatment of insomnia in adults.
Systematic review to identify and summarize previously published quantitative reviews (meta-analyses) of behavioral and pharmacologic treatments for insomnia.
Insomnia is a common clinical condition characterized by difficulty initiating or maintaining sleep, accompanied by symptoms such as irritability or fatigue during wakefulness. The prevalence of insomnia disorder is approximately 10% to 20%, with approximately 50% having a chronic course. Insomnia is a risk factor for impaired function, development of other medical and mental disorders, and increased health care costs. The etiology and pathophysiology of insomnia involve genetic, environmental, behavioral, and physiological factors culminating in hyperarousal. The diagnosis of insomnia is established by a thorough history of sleep behaviors, medical and psychiatric problems, and medications, supplemented by a prospective record of sleep patterns (sleep diary). Quantitative literature reviews (meta-analyses) support the efficacy of behavioral, cognitive, and pharmacologic interventions for insomnia. Brief behavioral interventions and Internet-based cognitive-behavioral therapy both show promise for use in primary care settings. Among pharmacologic interventions, the most evidence exists for benzodiazepine receptor agonist drugs, although persistent concerns focus on their safety relative to modest efficacy. Behavioral treatments should be used whenever possible, and medications should be limited to the lowest necessary dose and shortest necessary duration.
Clinicians should recognize insomnia because of its effects on function and health. A thorough clinical history is often sufficient to identify factors that contribute to insomnia. Behavioral treatments should be used when possible. Hypnotic medications are also efficacious but must be carefully monitored for adverse effects.
Oil and gas (O&G) pipelines are expensive assets that cross through both the ecologically sensitive and densely populated urban areas. The pipeline failure may have potentially significant ...consequences for both the natural and human environments. In order to maintain the integrity of O&G pipelines, inspection and maintenance processes should be governed by efficient policies. The objective of this paper is to conduct a state-of-the-art review of maintenance policies of O&G pipelines to investigate their advantages, limitations, and associated implementation issues. Maintenance policies can be categorised into corrective, preventive, predictive and proactive. Corrective maintenance policies (1940s) were based on the 'repair when broke' philosophy. Economic considerations shifted practice towards preventive maintenance (1970s to 1990s); later with improved inspection techniques and environmental regulations, predictive and proactive or risk-based maintenance (RBM) policies were developed. This review explicates different methodologies for RBM and related issues, e.g. uncertainties and variability, conservative assumptions, etc. Uncertainties associated with investigation and prediction of defects have been more frequently reported in the literature so far. Moreover, existing studies primarily focused on reducing the likelihood and cost of failure, whereas consideration of environmental factors in overall risk has been a relatively less addressed issue.
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