Configuration Management Research Articles

Optimal Energy Management for a Mild Hybrid Vehicle With Electric and Hybrid Engine Boosting Systems

This paper investigates the utilization of two low-voltage hybrid mechanisms on fuel economy improvement of a vehicle with a downsized engine. The first mild hybrid system, configured with a motor, a planetary gear set, and a supercharger, permits switching between parallel hybrid operation and boosting but not both. This constrained flexibility offers additional degrees of freedom, yet it requires a highly optimized decision of which functionality, torque assist, or boost assist, in addition to how much energy to be used by each. The second mild hybrid system also supports supercharging and torque assist but with two separate motors, hence is more flexible. Both systems enable the use of a downsized engine as a competitive counterpart to widely used turbocharged and full hybrid electric powertrains. The optimal control problem for energy management of both configurations on a vehicle with an automatic transmission is formulated and solved using dynamic programming (DP) over standard drive cycles. The results indicate around 25% fuel consumption improvement compared to a baseline turbo-charged engine over the FTP75 cycle, which is around 80% of the full hybridization benefit. The supercharging versus torque assist share and its sensitivity to the drive cycle, battery size, and compressor efficiency, which influence the availability of electric energy and the losses of electrical and mechanical paths, is also investigated. Few causally implementable rules for selecting the single motor system operating mode are found by analysis of the DP solution, and their effectiveness is shown by incorporating into the DP formulation and comparing the resulting fuel consumption.

Optimal configuration and energy management scheme of an isolated micro-grid using Cuckoo search optimization algorithm

This paper proposes an optimization scheme for optimal configuration and energy management of the micro-grid (MG), using the Cuckoo search optimization algorithm (CSOA). The selected MG supplies a load profile located between 30.119 latitude and 31.605 longitude. The energy produced by the MG generation sources, according to meteorological data of the proposed location, is calculated using MATLAB. The objective/fitness function is modeled and designed for minimizing the total investment cost (TIC) including capital, investment, operation and maintenance costs. A novel weighted goal attainment function (WGAF) has been proposed to reduce CO2 emissions and their associated costs. Moreover, WGAF also applies higher taxes on the amount of emissions that exceed governmental approved limits. To investigate the effects of WGAF on the TIC ($/year), annual cost of energy ($/kWh), and CO2 emissions, various weighted coefficients are analyzed. The simulation results have shown that the designed optimization scheme can robustly and efficiently produce the optimal MG configuration that is both eco-friendly and generates economic benefits.

A new risk and issue management system to improve productivity, quality, and compliance in clinical trials.

ObjectiveWe present a new system to track, manage, and report on all risks and issues encountered during a clinical trial.Materials and MethodsOur solution utilizes JIRA, a popular issue and project tracking tool for software development, augmented by third-party and custom-built plugins to provide the additional functionality missing from the core product.ResultsThe new system integrates all issue types under a single tracking tool and offers a range of capabilities, including configurable issue management workflows, seamless integration with other clinical systems, extensive history, reporting, and trending, and an intuitive web interface.Discussion and ConclusionBy preserving the linkage between risks, issues, actions, decisions, and outcomes, the system allows study teams to assess the impact and effectiveness of their risk management strategies and present a coherent account of how the trial was conducted. Since the tool was put in production, we have observed an increase in the number of reported issues and a decrease in the median issue resolution time which, along with the positive user feedback, point to marked improvements in quality, transparency, productivity, and teamwork.

11 Reasons to Use Automated Metrology

<div class="section abstract"><div class="htmlview paragraph">Aerospace structures manufacturers find themselves frequently engaged in large-scale 3D metrology operations, conducting precision measurements over a volume expressed in meters or tens of meters. Such measurements are often done by metrologists or other measurement experts and may be done in a somewhat ad-hoc fashion, i.e., executed in the most appropriate method according to the lights of the individual conducting the measurement. This approach is certainly flexible but there are arguments for invoking a more rigorous process. Production processes, in particular, demand an automated process for all such “routine” measurements. Automated metrology offers a number of advantages including enabling data configuration management, de-skilling of operation, real time input data error checking, enforcement of standards, consistent process execution and automated data archiving. It also reduces training, setup time, data manipulation and analysis time and improves reporting.</div><div class="htmlview paragraph">This paper draws on experiences from a recent automated metrology project and examines some of the challenges and benefits of successful measurement automation.</div></div>

Perspectives of Optimization of Technical Services and Maintenances Using Risk-Informed Decision-Making at NPPs in Ukraine

In most cases, when it goes about maintenance and repair optimization, the repair concept based on technical state of equipment is considered. This article describes the approach to maintenance and repair optimization at nuclear power plants by their transfer from the outage period to unit operation at power. The analysis of maintenance and repair optimization at foreign NPPs is carried out. The U.S. experience in reducing the outage duration is described. The article presents information on the pilot maintenance and repair optimization project at Zaporizhzhya NPP unit 2. The US Department of Energy through Argonne National Laboratory provides support in the implementation of the project in Ukraine focused on maintenance optimization of safety important systems based on risk-informed configuration management. The scope of this Project involves technical engineering analyses, plant personnel training, a study of improved economic performance indicators, and development of new strategies for NPP configuration, maintenance and operation. In order to optimize plant oeration, it is necessary to analyze plant commitments and requirements using effective, unbiased engineering assessments. Plant specific Probabilistic Risk Assessment combined with other engineering analyses techniques will be used for these assessments. This article also describes the results of the analysis of the preparedness of the Ukrainian regulatory framework for the implementation of the Project on maintenance optimization. The analysis focused on the U.S. and Ukrainian regulations and documents of the IAEA and WENRA international organizations related to maintenance optimization using riskinformed management of plant configuration. Based on the comparative analysis results, the authors identified possible limitations stipulated by non-compliance of the Ukrainian nuclear and radiation safety regulatory framework with the U.S. regulatory and methodological documents used for maintenance and repair optimization at the U.S. NPPs. In particular, the overview of USA regulations leads to the conclusion that they contain exhaustive requirements for the application of maintenance using risk-informed plant configuration management at all stages of its implementation, starting with the requirements for the alternative approach to maintenance and ending with the requirements for maintenance performance monitoring. Ukrainian regulations in turn contain only general provisions and areas for potential application of risk-informed approaches in operation and inspection. It should also be noted that the U.S. maintenance optimization methodology uses criteria based on the core damage frequency and large early release frequency. However, besides core damage frequency Ukraine uses the emergency release frequency criterion that does not correspond to the definition for large early release frequency used in the U.S.

Framework for Analyzing Aircraft Community Noise Impacts of Advanced Operational Flight Procedures

A framework for analyzing the aircraft community noise impacts of advanced operational approach and departure procedures was developed. In this framework, the altitude, position, velocity, thrust, and configuration profiles of procedures to be assessed are specified by aircraft performance. These profiles are input to the NASA Aircraft NOise Prediction Program, which requires aerodynamic performance and engine state parameters, as well as generates airframe and engine noise throughout each procedure. Generated single-event surface noise grids are combined with population census data to estimate population noise exposure. The framework’s noise estimates agree to within effective perceived noise level of available certification noise data from six aircraft types. Use of the framework was demonstrated on example departure and approach cases to show how it can be used to assess the performance and noise impacts of varying the altitude, velocity, thrust, and configuration for various aircraft. One example shows the evaluation of the noise impacts of an increased thrust departure, in which the thrust and associated altitude were increased on departure. The second example analyzed the noise impacts of altered vertical path and configuration management approaches. These included altering conventional step-down approaches to continuous descent approaches at glide slopes of 3.0–3.2 deg, as well as delayed gear approaches.

The configuration management requirements for aviation, space and defense organizations

Certification of the quality management system for aviation, space and defense organizations, according to EN 9100: 2016 / AS 9100D standard requires compliance with the configuration management requirements. This article presents the implementation of Configuration management and documents control throughout the entire life cycle of product realization. Configuration management establishes a language of understanding between the client and the supplier both in predefined relationship (such as Built to Print) and those in which the supplier is given some freedom (such as Built to Spec), described in SR EN 16601-40: 2015 standard.

A step toward the standardization of maintenance and training services in C4I military systems with Mixed Reality application

This paper is a review of the work presented at the 5th IEEE International Workshop on Metrology for Aerospace, MetroAeroSpace 2018 (Piedimonte and Ullo, 2018) [1], enriched with some concepts on standardization for Mixed Reality applications.Nowadays, large organizations are looking for new procedures and configuration management in order to optimize operations for training and maintenance. The idea is to employ advanced techniques in order to handle budget constraints and reduction of human resources. At this aim, Virtual, Augmented and Mixed Realities are getting more and more exploited to support complex systems during their in-service phase. Nevertheless, the Mixed Reality has not formal standards available for the different application fields yet. This problem limits its utilization because it is not simple to deal with all the possible variations that can occur on the apparatus under maintenance or during a training process, which need to be suitably recorded and carried on. These themes are typically managed by the “Configuration Management” and are already harmonized in the norms, typically used in the discipline of the Integrated Logistic Support (ILS). Moreover, the new scenarios, where Virtual, Augmented or Mixed Realities are employed, lead to a maintenance “on condition”, rather than to an “established scheduled” maintenance. In this context, the traditional manuals for maintenance, which present a “constant visualization”, typically a.pdf-file, lose effectiveness. On the contrary, the manuals based on a “variable visualization”, such as the AeroSpace and Defense (ASD) S1000 D norm, integrated with logistic data based on ASD S 3000 L norm, offer a great competitive advantage. This paper aims to present first steps towards the standardization of Maintenance and Training Processes in Command Control Communications Computers and Intelligence (C4I) Military Systems of ITalian Air Force (ITAF) when Mixed Reality is applied. In order to understand the most suitable choice when the C4I systems are involved, ITAF is running a Proof of Concept (PoC) to evaluate and compare the different technologies based on Mixed Reality. It is worth to underline that the benefits of Augmented and Mixed Reality have been extended to other fields such as for instance: industrial, technical, social, medical, cultural, besides the military one. Therefore, the results of this paper and the efforts for implementing standardization procedures will be useful for exploitation actions in all application fields.

A Framework for Automated Cellular Network Tuning With Reinforcement Learning

Tuning cellular network performance against always occurring wireless impairments can dramatically improve reliability to end users. In this paper, we formulate cellular network performance tuning as a reinforcement learning (RL) problem and provide a solution to improve the performance for indoor and outdoor environments. By leveraging the ability of Q-learning to estimate future performance improvement rewards, we propose two algorithms: (1) closed loop power control (PC) for downlink voice over LTE (VoLTE) and (2) self-organizing network (SON) fault management. The VoLTE PC algorithm uses RL to adjust the indoor base station transmit power so that the signal to interference plus noise ratio (SINR) of a user equipment (UE) meets the target SINR. It does so without the UE having to send power control requests. The SON fault management algorithm uses RL to improve the performance of an outdoor base station cluster by resolving faults in the network through configuration management. Both algorithms exploit measurements from the connected users, wireless impairments, and relevant configuration parameters to solve a non-convex performance optimization problem using RL. Simulation results show that our proposed RL based algorithms outperform the industry standards today in realistic cellular communication environments.

Management Platforms and Protocols for Internet of Things: A Survey.

Internet of Things (IoT) management systems require scalability, standardized communication, and context-awareness to achieve the management of connected devices with security and accuracy in real environments. Interoperability and heterogeneity between hardware and application layers are also critical issues. To attend to the network requirements and different functionalities, a dynamic and context-sensitive configuration management system is required. Thus, reference architectures (RAs) represent a basic architecture and the definition of key characteristics for the construction of IoT environments. Therefore, choosing the best technologies of the IoT management platforms and protocols through comparison and evaluation is a hard task, since they are difficult to compare due to their lack of standardization. However, in the literature, there are no management platforms focused on addressing all IoT issues. For this purpose, this paper surveys the available policies and solutions for IoT Network Management and devices. Among the available technologies, an evaluation was performed using features such as heterogeneity, scalability, supported technologies, and security. Based on this evaluation, the most promising technologies were chosen for a detailed performance evaluation study (through simulation and deployment in real environments). In terms of contributions, these protocols and platforms were studied in detail, the main features of each approach are highlighted and discussed, open research issues are identified as well as the lessons learned on the topic.

Research on Construction Method of In-service Aircraft Configuration Data Model

In order to establish the basic data architecture for aircraft in-service configuration management, ensuring efficient implementation of it, the characteristics of configuration change caused by various maintenance and support operation during the service phase of large civil aircraft were analyzed. On this basis, formal classification of in-service aircraft configuration data was carried out. Based on the product structure tree, the architecture of the aircraft configuration data was constructed. The in-service aircraft configuration data schema was defined. By introducing the idea of Skyline query, the configuration change information filtering method was designed and implemented. Finally, method validation was performed by the maintenance and support data of an airline company. The results show that, the automatic extraction of configuration change information is realized effectively, ensuring the full integration of the in-service aircraft configuration data schema and production and maintenance information management, and ensuring the real-time and consistency of in-service aircraft configuration data management.

RULE OF THUMB TO DETERMINE THE LOCATION OF WI-FI MODULE ON PLASTIC OR METAL CHASSIS

In this study, a general rule of thumb was developed for an easier and more robust product configuration management containing more than one Wi-Fi modules. In the study, a television chassis is being used for two different models having different Wi-Fi modules in them. From manufacturing perspective, managing the product configuration as simple as it can improve the manufacturing costs drastically. Two Wi-Fi modules having different antenna characteristics will perform differently based on their locations on the chassis. Based on the distance of the antenna to the closest material of the chassis effects antenna characteristics of both Wi-Fi modules. We obtained a common minimum distance that does not disrupts the antenna performance of both Wi-Fi modules to out of Wi-Fi spectrum. For the particular case in this study, we obtained a safe distance which keeps the voltage standing wave ratio of the antennas of both Wi-Fi modules under two over Wi-Fi frequency spectrum.

Integrated automation for configuration management and operations in the ATLAS online computing farm

The online farm of the ATLAS experiment at the LHC, consisting of nearly 4000 PCs with various characteristics, provides configuration and control of the detector and performs the collection, processing, selection, and conveyance of event data from the front-end electronics to mass storage. Different aspects of the farm management are already accessible via several tools. The status and health of each node are monitored by a system based on Icinga 2 and Ganglia. PuppetDB gathers centrally all the status information from Puppet, the configuration management tool used to ensure configuration consistency of every node. The in-house Configuration Database (ConfDB) controls DHCP and PXE, while also integrating external information sources. In these proceedings we present our roadmap for integrating these and other data sources and systems, and building a higher level of abstraction on top of this foundation. An automation and orchestration tool will be able to use these systems and replace lengthy manual procedures, some of which also require interactions with other systems and teams, e.g. for the repair of a faulty node. Finally, an inventory and tracking system will complement the available data sources, keep track of node history, and improve the evaluation of long-term lifecycle management and purchase strategies.

Enabling complexity management through merging business process modeling with MBSE

Integral products are characterized by multiple functional use of components, resulting in more compact and lighter products. However, those benefits come along with a significant increase in development process complexity. This complexity represents a significant risk in the value-creation chain. For the efficient fulfilment of customer needs and market requirements, strategies are required to cope with the complexity of integral products. A promising approach in this context is Model Based Systems Engineering (MBSE). Through the formalized application of modeling, MBSE allows the development of a system model to support the development process. The model enables a visualization of the process complexity and thus an identification of the essential complexity drivers. This knowledge is mandatory for the coordinated initiation of countermeasures. However, MBSE is not yet fully integrated in today’s product development processes (PDP). One reason for this is an insufficient interconnection between system models and business processes. This paper presents an approach for merging MBSE with business processes. The procedure comprises the modeling of exemplary business processes in a product data management system (PDMS). These processes are linked to a MBSE modeling tool via a RESTful API. Synergetic potentials of this connection are pointed out, based on scenarios from requirements management, product configuration and risk management. Finally, a discussion takes place regarding the degree of maturity to master complexity in business processes with MBSE.

Evolving CERN’s Network Configuration Management System

CERN’s networks comprise several thousands network devices from multiple vendors and from different generations, fulfilling various purposes (campus network, data centre network, and dedicated networks for the LHC accelerator and experiments control). To ensure the reliability of the networks, the IT Communication Systems group has developed an in-house, Perl-based software called “cfmgr”, capable of deriving and enforcing the appropriate configuration on all these network devices, based on information from a central network database. Due to the decrease in popularity of the technologies it relies upon, maintaining and expanding the current network configuration management system has become increasingly challenging. Hence, we have evaluated the functionality of various open-source network configuration tools, in view of leveraging them for evolving the cfmgr platform. We will present the result of this evaluation, as well as the plan for evolving CERN’s network configuration management system by decoupling the configuration generation (CERN specific) from the configuration enforcement (generic problem, partially addressed by vendor or community Python based libraries).

Rule authoring for vehicle configuration management: an experimental study on graph-based representations

The purpose of this research is to determine whether the implementation of a visual rule authoring mechanism would increase the accuracy and/or consistency of the rules being implemented by conducting a user study. The researchers hypothesised that using the visual method for implementing rules would result in a higher degree of accuracy and consistency among the participants. However, the results showed a decrease in the response accuracy for implementing all of the rules in the system. This is likely due in part to the graphical representation method requiring more training than the standard text-based rule implementation method. The most significant limitation in this study was the difference in familiarity of the participants with their respective rule implementation systems. As a result of this limitation, an additional study was conducted in which a third group of participants were given the same questions, but were provided the visualisations with an extended (five-minute) training period. The results from the third group closely matched the results from the control group that used the spreadsheet-based method. Another major limitation is that both groups of participants implemented the changes by hand rather than through the use of a graphical user interface (GUI) software module, which is how the graphical method could be conducted in a real environment.

Automatic Real-Time Mining Software Process Activities From SVN Logs Using a Naive Bayes Classifier

The abundance of event data in current software configuration management systems makes it possible to discover software process models automatically by using actual observed behavior. However, traditional process mining algorithms cannot be applied to event logs recorded in software configuration management (SCM) systems, such as SVN, because of missing activity attributes. To address this problem, a software process activity classifier is proposed to build event-activity mapping relationships from software development event streams, revealing activity attributes and associating the activity to the original SVN log. The proposed approach extracts activity from the SVN log based on semantic features and introduces a novel technique based on a naive Bayes approach to associate event activities dynamically. The approach has been applied to two real-world software development process logs, ArgoUML and jEdit , consisting of more than 80,000 events, covering development information from 1998 to 2015. With the application of our approach to such data, activities can be extracted from event logs and a classifier can be constructed for adding activity attributes to new events. The results of the classification are evaluated in terms of precision rate , recall rate, and the F-measure . Overall, two real-world software development process logs are used to validate the method, and the experimental results show that the approach can mine software process activities from SVN log events automatically and in real-time.

Rule authoring for vehicle configuration management: an experimental study on graph-based representations

Rule authoring for vehicle configuration management: an experimental study on graph-based representations

Research on Human Resource Allocation Model Based on SOM Neural Network

With the fierce competition of the enterprise market, the human resource allocation of enterprises will face multiple risks. This article takes the connotation of human resource configuration management as the research object and establishes the human resource configuration model through SOM neural network. And the model is trained, learned, and tested. What's more, it is applied to human resources management to adjust the allocation of human resources for the enterprise in a timely manner. It provides a detailed basis for proposing coping strategies and has a great application value.

Using the Autopilot pattern to deploy container resources at a WLCG Tier-2

Containers are becoming ubiquitous within the WLCG, with CMS announcing a requirement for its sites to provide Singularity during 2018. The ubiquity of containers means it is now possible to reify the combination of an application and its configuration into a single easy-to-deploy unit, avoiding the need to make use of a myriad of configuration management tools such as Puppet, Ansible or Salt. This allows use to be made of industry-standard devops techniques within the operations domain, such as Continuous Integration (CI) and Continuous Deployment (CD), which can lead to faster upgrades and greater system security. One interesting technique is the Autopilot pattern, which provides mechanisms for application life-cycle management which are accessible from within the container itself. Using modern service discovery techniques, each container manages its own configuration, monitors its own health, and adapts to changing requirements through the use of event triggers. In this paper, we expand on previous work to create and deploy resources to a WLCG Tier-2 via containers, and investigate the viability of using the Autopilot pattern at a WLCG site to deploy and manage computational resources.