Health Management Framework Research Articles

Decision process to manage useful life of multi-stacks fuel cell systems under service constraint

A management of multi-stacks fuel cell systems is proposed to extend systems useful life in a Prognostics and Health Management (PHM) framework. The problem consists in selecting at each time which fuel cell stacks have to run and which output power has to be chosen for each of them to satisfy a load demand as long as possible. Multi-stacks fuel cell system useful life depends not only on each stack useful life, but also on both the schedule and the operating conditions settings that define the contribution of each stack over time. As the impact of variable operating conditions on fuel cell lifetime is not well-known, a simplified representation of fuel cell behavior under wear and tear is used to estimate the available outputs over time and their associated Remaining Useful Lives (RUL). This health state prognostics model is configured to suit to Proton-Exchange Membrane Fuel Cells (PEMFC) specific characteristics. The proposed scheduling process makes use of an optimal approach based on a Mixed Integer Linear Program (MILP). Efficiency of the associated commitment strategy is assessed by comparison with basic intuitive strategies, considering constant and piecewise constant load demand profiles.

Condition-Based Maintenance With Scheduling Threshold and Maintenance Threshold

In order to arrange maintenance resources according to system condition, the lead time needs to be considered within the context of condition-based maintenance (CBM). Therefore, a scheduling threshold is introduced to replace the time to schedule, which is used as a decision variable in combination with a maintenance threshold and a failure threshold. The long-run expected cost rate for maintenance considers the maintenance cost, the cost of the waiting time of suppliers and customers. In this way, suppliers can schedule maintenance services in advance when the system condition reaches the scheduling threshold, and perform maintenance when the system condition exceeds the maintenance threshold. Furthermore, the optimal maintenance plan is updated dynamically in the framework of Prognostics and Health Management (PHM). Finally, a numerical example is provided to demonstrate the effectiveness and the dynamic nature of the proposed method.

Challenges in Concrete Structures Health Monitoring


 
 
 Structural health monitoring needs to produce actionable information regarding structural integrity that supports operational and maintenance decision making that is individualized for a given structure and its performance objectives. An effective Prognostics and Health Management (PHM) framework for aging structures (subjected to physical, chemical, environmental, and mechanical degradation) needs to integrate four elements – damage modeling, monitoring, data analytics, and uncertainty quantification. This paper briefly discusses available techniques and ongoing challenges in each of these four elements of PHM, in the context of concrete structures. A Bayesian network approach is discussed for integrating heterogeneous information from multi-physics computational models of degradation processes, full-field measurement techniques, big data analytics, and various data and model uncertainty sources. Such a comprehensive framework can quantitatively support decisions regarding appropriate risk management actions.
 
 

Accelerated life tests for prognostic and health management of MEMS devices

Microelectromechanical systems (MEMS) offer numerous applications thanks to their miniaturization, low power consumption and tight integration with control and sense electronics. They are used in automotive, biomedical, aerospace and communication technologies to achieve different functions in sensing, actuating and controlling. However, these microsystems are subject to degradations and failure mechanisms which occur during their operation and impact their performances and consequently the performances of the systems in which they are used. These failures are due to different influence factors such as temperature, humidity, etc. The reliability of MEMS is then considered as a major obstacle for their development. In this context, it is necessary to continuously monitor them to assess their health status, detect abrupt faults, diagnose the causes of the faults, anticipate incipient degradations which may lead to complete failures and take appropriate decisions to avoid abnormal situations or negative outcomes. These tasks can be performed within Prognostics and Health Management (PHM) framework. This paper presents a hybrid PHM method based on physical and data-driven models and applied to a microgripper. The MEMS is first modeled in a form of differential equations. In parallel, accelerated life tests are performed to derive its degradation model from the acquired data. The nominal behavior and the degradation models are then combined and used to monitor the microgripper, assess its health state and estimate its Remaining Useful Life (RUL).

A verification framework with application to a propulsion system

This paper introduces a novel verification framework for Prognostics and Health Management (PHM) systems. Critical aircraft, spacecraft and industrial systems are required to perform robustly, reliably and safely. They must integrate hardware and software tools intended to detect and identify incipient failures and predict the remaining useful life (RUL) of failing components. Furthermore, it is desirable that non-catastrophic faults be accommodated, that is fault tolerant or contingency management algorithms be developed that will safeguard the operational integrity of such assets for the duration of the emergency. It is imperative, therefore, that models and algorithms designed to achieve these objectives be verified before they are validated and implemented on-board an aircraft. This paper develops a verification approach that builds upon concepts from system analysis, specification definition, system modeling, and Monte Carlo simulations. The approach is implemented in a hierarchical structure at various levels from component to system safety. Salient features of the proposed methodology are illustrated through its application to a spacecraft propulsion system.

A framework for child safety and health management by analogy to occupational safety and health management

Child accidents and diseases are characterized by many factors. Thus, a system approach to child safety and health (CSH) including different management levels is indispensable. However, the literature is scarce in holistic approach to CSH management. In this paper, a unified framework for CSH is proposed by analogy to occupational safety and health (OSH) system. In this framework, CSH management comprises decisions and actions on global, macro, and micro-levels for a safe and healthy environment for children. Global level represents international organizations working for CSH, macro level represents national regulations, and micro-level represents home environments and public places. The decisions and actions at each level are linked to the subsequent level by input/feedback relation. The framework is illustrated by hypothetical examples, and provides a holistic practical approach to CSH management. Other OSH management approaches and best practices can also be adapted to the proposed CSH system.

An integrated framework for online diagnostic and prognostic health monitoring using a multistate deterioration process

Efficient asset management is of paramount importance, particularly for systems with costly downtime and failure. As in energy and capital-intensive industries, the economic loss of downtime and failure is huge, the need for a low-cost and integrated health monitoring system has increased significantly over the years. Timely detection of faults and failures through an efficient prognostics and health management (PHM) framework can lead to appropriate maintenance actions to be scheduled proactively to avoid catastrophic failures and minimize the overall maintenance cost of the systems. This paper aims at practical challenges of online diagnostics and prognostics of mechanical systems under unobservable degradation. First, the elements of a multistate degradation structure are reviewed and then a model selection framework is introduced. Important dynamic performance measures are introduced, which can be used for online diagnostics and prognostics. The effectiveness of the result of this paper is demonstrated with a case study on the health monitoring of turbofan engines.

Medicaid as a Model for Mental Health Service Delivery

Medicaid, the publicly funded insurance provider for low-income individuals, is the “single largest payer for mental health services” in the United States. In 2010, Medicaid financed 28% of all mental health services, spending over $31 billion, but accounted for only 17% of total health care outlays; these statistics demonstrate the program’s comparatively significant commitment to funding mental health treatments. Medicaid has expanded rapidly over the past quarter century: in 1986, the program accounted for only 16.1% of mental health service payments, or $7.5 billion. As Medicaid plays an increasingly significant role in financing mental health services, policymakers need to understand its payment mechanisms as well as eligibility requirements, and to address both the efficiencies and inefficiencies in the system. Jointly administered by the state and federal governments, Medicaid consists of numerous programs and incentive schemes aimed at financing mental health treatments. Three of the most prominent programs include home- and community-based services (HCBS), health homes and targeted case management (TCM). An evaluation of these programs indicates that their efficiency, measured by both cost-effectiveness and patient outcomes, varies significantly across states depending on the specific implementation techniques adopted by state officials. This paper analyzes the methods that states employ to provide insurance through Medicaid, examining the factors that have enabled some administrators to see significant declines in costs and increases in quality of care. Specifically, states that prioritize mental health services, provide for early-onset disease intervention and focus on holistic community-based care see the most efficient outcomes in treatment of mental health patients. This paper also aims to assess mental health pilot programs and promote implementation rationales based on clinical outcomes and cost effectiveness criteria. The analysis in this paper offers evidence that, when applied to the framework of mental health management, programs designed to integrate holistic care models offer greater potential than fragmented care systems to offset long-term spending and improve health outcomes.

A recursive Bayesian framework for structural health management using online monitoring and periodic inspections

The necessary information for developing a structural health diagnostic and prognostic solution is often obtained from various sources. This paper presents a Bayesian framework for online integration of the structural health assessment information obtained from empirical crack growth models, structural health monitoring and periodic inspections. The data used in Bayesian updating could be direct damage observations (e.g., observed crack sizes) and/or damage growth rate estimates (e.g., crack growth rate observations). An AE-based monitoring approach is used to obtain the crack growth rate observations in this paper. The outcome of this approach is updated crack size distribution as well as updated parameters for an empirical crack growth model. The model with updated parameters is used for prognosis given an assumed future usage profile.

Simulation Framework and Certification Guidance for Condition Monitoring and Prognostic Health Management

The most prominent challenges to the successful qualification of Integrated System Health Monitoring (ISHM) systems are appropriate technology development processes and Verification & Validation (V&V) methods towards certification. This paper outlines a survey of recent ISHM programs in diverse industrial sectors across the globe, offers guideline towards ISHM development at each Technology Readiness Level (TRL), and sets forth a V&V process and certification roadmap. This paper provides insight into Cassidian’s ISHM Simulation framework and emphasizes the relevance of this framework to an effective V&V solution of ISHM.

Structural fatigue prognosis using limited sensor data

In this paper, a general framework for concurrent structural fatigue prognosis using limited sensor data is developed. The Empirical Mode Decomposition method is employed to reconstruct the structural dynamical response for the critical spot susceptible to fatigue damage. The sensor data available at limited locations measured from the usage monitor system are decoupled into several Intrinsic Mode Functions using the Empirical Mode Decomposition method. Those IMFs are applied to extrapolate the dynamic response for the critical spot where the direct response measurements are unavailable. The extrapolated dynamic response time series for the critical spot is then integrated with a physical fatigue crack growth model for fatigue damage prognosis. The proposed procedure is demonstrated using a multi degree-of-freedom (MDOF) cantilever beam example. The proposed method has great potential for the real-time decision making in the vehicle health management framework due to its ability for the concurrent damage prognosis.

Using the Reference Framework for Good Measles Management in Practice - A Case Study from North Rhine-Westphalia

In 2005, WHO Europe reconfirmed the objective of eradicating measles and fixed a strategy plan for the years 2005 up to 2010. While a downward trend of measles infections in Germany between 2001 and 2004 could be observed, as many as 780 cases of measles were reported in 2005 and in 2006 even 2.281 cases. These high figures in 2006 were almost exclusively caused by an outbreak in the German region of North Rhine-Westphalia. This case study describes how a reference framework for good health management of measles prevention was applied for this region. As a result, various recommendations for action could be given, among them the recommendation to implement individual vaccination reminder systems for parents and bonus systems for parents. Based on these results, a comprehensive policy concept has been drawn up and has become the subject of a political agreement process in this region. Thus this case study shows a paradigm how reference frameworks for good health management can be utilised in practice.

Case illustration of a decision framework for health, environment, and safety management

This paper presents and discusses a case in order to illustrate the application of a recently developed decision framework for management of health, environment, and safety. The case relates to the implementation of new equipment on an offshore platform and shows how a regime based on predefined risk acceptance criteria is replaced by systematic risk reduction processes, emphasizing aspects of uncertainties and manageability in addition to the calculated risk results. Although the starting point is the offshore oil and gas industry, the problem and discussion are to a large extent general and could also be applied in other areas.

A risk analysis framework for aquatic animal health management in marine stock enhancement programmes

In light of limited supplies of fish from natural populations, stock enhancement is being considered as one means of helping to meet the demand for seafood products from an ever-increasing human population. The technology to produce large numbers of early-life stage aquatic organisms in hatcheries is well-developed, and the use of alien species, although controversial, has also created new fisheries in some countries. Stock enhancement often requires technical interventions in the rearing process of aquatic organisms that may substantially change how an organism interacts with pathogens. Aquatic animal health risk analysis in stock enhancement programmes involves consideration of: the source of animals to be released, the populations to be managed, hazard identification, risk assessment, risk management, quarantine, diagnostic and treatment procedures, mitigation measures, monitoring, reporting the disease status of hatchery and wild populations, and the establishment of aquatic animal health standards. Information and guidelines to assist in aquatic animal health management include the FAO Conduct for Responsible Fisheries, the ICES code of practice on introductions, the OIE aquatic animal health standards, the Asian regional guidelines on health management for the responsible movement of aquatic animals and the WTO's Sanitary and Phytosanitary Agreement.

It Pays to Manage Health Protection and Safety at Work

Under European Union directives, employers have responsibilities for the safety and health of their workers. Directive 89/391 provides the general framework for health and safety management, risk identification and prevention. The directive has been implemented in national legislation that may include additional requirements. In the Slovak Republic the health and safety work act 1996 required an employer to identify and to control risks to workers and others. An assessment of risk is nothing more than a careful examination of what, in work could cause harm to people, so that we can weight up whether wehave taken enough precautions or should do more to prevent harm.

Animal health and welfare in organic livestock production in Europe: current state and future challenges

Existing data on animal health and welfare in organic livestock production systems in the European Community countries are reviewed in the light of the demands and challenges of the recently implemented EU regulation on organic livestock production. The main conclusions and recommendations of a 3-year networking project on organic livestock production are summarised and the future challenges to organic livestock production in terms of welfare and health management are discussed. The authors conclude that, whilst the available data are limited and the implementation of the EC regulation is relatively recent, there is little evidence to suggest that organic livestock management causes major threats to animal health and welfare in comparison with conventional systems. There are, however, some well-identified areas, like parasite control and balanced ration formulation, where efforts are needed to find solutions that meet with organic standard requirements and guarantee high levels of health and welfare. It is suggested that, whilst organic standards offer a good framework for animal health and welfare management, there is a need to solve apparent conflicts between the organic farming objectives in regard to environment, public health, farmer income and animal health and welfare. The key challenges for the future of organic livestock production in Europe are related to the feasibility of implementing improved husbandry inputs and the development of evidence-based decision support systems for health and feeding management.

WWW+smart card: towards a mobile health care management system

This paper highlights the benefits of combining the World Wide Web and smart card technologies to support a highly mobile health management framework. In particular, we describe an approach using the SmartCard–Web Gateway Interface (SGI) as a common interface to communicate and access the medical records residing in a smart card. Importantly, by employing HTTP as the baseline protocol to access information on the smart card, SGI promotes the use of de facto standard web browsers as the common client user interface. The initial implementation of the framework has demonstrated the feasibility of the concept in facilitating a truly mobile access of patient’s medical records based on SGI.