Service Engineering Research Articles

Creep Parameters Determination by Omega Model to Norton Bailey Law by Regression Analysis for Austenitic Steel SS-304

In the material’s creep failure analysis, the difficulty of assessing the applied thermo-mechanical boundary conditions makes it critically important. Numerous creep laws have been established over the years to predict the creep deformation, damage evolution and rupture of the materials subjected to creep phenomena. The omega model developed by the American Petroleum Institute and Material Properties Council is one of the most commonly used creep material models for numerical analysis over the years. It is good in defining the fitness of mechanical equipment for service engineering evaluation to ensure the reliable service life of the equipment. The Omega model, however, is not readily accessible and specifically incorporated for creep evaluation in FEA software codes and creep data is always scarce for the complete analysis. Therefore, extrapolation of creep behavior was performed by fitting various types of creep models with a limited amount of creep data and then simulating them, beyond the available data points. In conjunction with the Norton Bailey model, based on API-579/ASME FFS-1 standards, a curve fitting technique was employed called regression analysis. From the MPC project omega model, different creep strain rates were obtained based on material, stress and temperature-dependent data. In addition, as the strain rates increased exponentially with the increase in stresses, regression analysis was used for predicting creep parameters, that can curve fit the data into the embedded Norton Bailey model. The uncertainties in extrapolations and material constants has highlighted to necessitate conservative safety factors for design requirement. In this case study, FEA creep assessment was performed on the material SS-304 dog bone specimen, considered as a material coupon to predict time-dependent plastic deformation along with creep behavior at elevated temperatures and under constant stresses. The results indicated that the specimen underwent secondary creep deformation for most of the period.

Sensitivity analysis for building energy audit calculation methods: Handling the uncertainties in small power load estimation

The use of static calculation models in building energy audits typically requires estimation of power loads, as appliance load monitoring is both expensive and intrusive. Small power loads are particularly difficult to monitor in detail and so, with increasing proportional contribution to overall building energy consumption, constitute a significant source of uncertainty in estimations. Little research has been conducted on how uncertainty in audit estimations (particularly of small power loads) should be handled and to what extent this impacts on what information is of most value in reducing audit uncertainties. The Morris method for sensitivity analysis has been adapted for small power load estimation to identify which inputs in static calculation models the output estimations are most sensitive to. The method is applied to the TM22 and TM54 audit calculation models from the Chartered Institute of Building Service Engineers (CIBSE); widely used in industry. Results demonstrate how the weight of input uncertainties differs according to the calculation model used. By providing uncertainty estimation in the audit process, auditors can choose an optimal energy assessment strategy for small power load estimations whilst also better understanding the significance of input uncertainty within the different energy calculation models.

Fault Detection and Troubleshooting in a PV Grid-Tied Inverter

Objectives: Present work envisages fault detection along with troubleshooting methodologies confirmed in solar photovoltaic workshop for grid-tied three-phase inverters. Only innovative inventions are not only necessary for the society to become advanced but also to continue the modern electrical evolution with zero carbon. Methods: Here with the help of sungrow software DSP1_20_VA_J & IDM- AC Fm ver the inverter sends a notification about the fault with a fault status code to the HMU/LCD display. As per fault severity it may completely shut down or partially operate the inverter with reduced load. After the fault rectification manually by the site operator again it restores the power and inject power to the grid. Finding: Here with the help of sungrow software DSP1_20_VA_J &IDM- AC Fm ver we find various types of faults with the nature of faults i.e. insulation fault, leakage current fault, over voltage/under voltage fault, frequency faults, temperature fault, islanding with its rectification process. The major, minor, and cautionary faults and their troubleshooting procedures are elucidated in the present study with coding of faults, and its alarm level. Novelty: In previous researches, the fault identification was not done properly; as a result the inverters are tripping frequently. The present software helps to detect fault of the inverter within 0.023 millisecond and send a message to the service engineer for rectification. The present research can be of immense help to the service engineers and field workers working on solar photo voltaic sector considering popularity of photovoltaic units. Keywords Solar power plant, Grid tied inverters, Fault finding, Trouble shooting

사용자 중심의 대화형 IoT 서비스 매쉬업 모델과 엔진

IoT 환경에서 사용자들은 IoT 기기를 활용한 서비스를 제공받을 뿐만 아니라 서비스 매쉬업을 통해 자신만의 애플리케이션을 생성하고자 한다. 이를 위해 시각적인 방식으로 IoT 서비스 매쉬업을 생성하는 방법들이 제안되었으나, 시각적으로 표현되는 매쉬업의 실행 흐름을 이해하는 것은 쉽지 않기 때문에 사용자들은 매쉬업을 만드는 데 어려움을 겪는다. 본 연구에서는 프로그래밍 경험이 없는 일반 사용자들이 IoT 서비스 매쉬업을 생성하도록 자연어를 통해 상호작용하는 대화형 서비스 매쉬업 모델 및 엔진을 제안한다. 대화형 서비스 매쉬업 모델은 사용자 명령을 파악하기 위한 네 종류 키워드로 구성되며, 엔진은 인터랙션 관리자, 시맨틱 매칭 모듈, 서비스 매쉬업 모듈로 구성된다. 본 연구에서는 스마트 홈 환경에서의 시나리오를 바탕으로 사례 연구를 진행하여, 일반 사용자들이 대화형 서비스 매쉬업 모델 및 엔진을 통해 더 쉽고 편리하게 필요한 서비스 매쉬업을 생성할 수 있음을 확인하였다.

Pathway-Driven Coordinated Telehealth System for Management of Patients With Single or Multiple Chronic Diseases in China: System Development and Retrospective Study

BackgroundIntegrated care enhanced with information technology has emerged as a means to transform health services to meet the long-term care needs of patients with chronic diseases. However, the feasibility of applying integrated care to the emerging “three-manager” mode in China remains to be explored. Moreover, few studies have attempted to integrate multiple types of chronic diseases into a single system.ObjectiveThe aim of this study was to develop a coordinated telehealth system that addresses the existing challenges of the “three-manager” mode in China while supporting the management of single or multiple chronic diseases.MethodsThe system was designed based on a tailored integrated care model. The model was constructed at the individual scale, mainly focusing on specifying the involved roles and responsibilities through a universal care pathway. A custom ontology was developed to represent the knowledge contained in the model. The system consists of a service engine for data storage and decision support, as well as different forms of clients for care providers and patients. Currently, the system supports management of three single chronic diseases (hypertension, type 2 diabetes mellitus, and chronic obstructive pulmonary disease) and one type of multiple chronic conditions (hypertension with type 2 diabetes mellitus). A retrospective study was performed based on the long-term observational data extracted from the database to evaluate system usability, treatment effect, and quality of care.ResultsThe retrospective analysis involved 6964 patients with chronic diseases and 249 care providers who have registered in our system since its deployment in 2015. A total of 519,598 self-monitoring records have been submitted by the patients. The engine could generate different types of records regularly based on the specific care pathway. Results of the comparison tests and causal inference showed that a part of patient outcomes improved after receiving management through the system, especially the systolic blood pressure of patients with hypertension (P<.001 in all comparison tests and an approximately 5 mmHg decrease after intervention via causal inference). A regional case study showed that the work efficiency of care providers differed among individuals.ConclusionsOur system has potential to provide effective management support for single or multiple chronic conditions simultaneously. The tailored closed-loop care pathway was feasible and effective under the “three-manager” mode in China. One direction for future work is to introduce advanced artificial intelligence techniques to construct a more personalized care pathway.

Admission control mechanism for quality of service and security in H.323 voice gateway

AbstractThe rapid demand on the VOIP communication lead to the increase of the development of information security and the offered quality. Therefore, information technology has increased the deepening and developing of call admission control (CAC). In which, admission decisions and resource reservations are taken at the edge voice gateway, rather than resources or individual routers within the network. This means that, CAC decision is made before a voice call is established and it depends on the availability of the required call resources to provide suitable quality of service (QoS) for the new call. In this article, a new model for voice network, in order to achieve QoS along with security, is proposed. In the proposed model, the admission control decision is taken place at H.323 voice gateways using resource reservation protocol. It is shown that the admission control decision should be taken at edge H.323 voice gateways. This will lead to provide the accepted security for both, source and destination nodes which were previously authenticated through the identity services engine. It is concluded from the simulation results that the packet loss rate of call flows after implementing the mechanism is almost 0%. In addition, there is no jitter although there is some delay for packet delivery “Latency.” The latency observed by the proposed model is still accepted according to the ITU G.114 standard which recommends a maximum of a 150 ms one‐way latency. All results are tested in GNS3 based simulation to evaluate the performance of voice gateway based upon CAC.

MEDIATION ACTS FROM EMPLOYEE ENGAGEMENT WHICH AFFECTS THE EMPLOYEE COMPETENCIES AND INNOVATIVE WORK BEHAVIOUR ON EMPLOYEE PERFORMANCE AT PT TETRA PAK INDONESIA

These research was intend to discovered the mediate acts from employee engagement in influencing the affect of employee competence and innovative behaviour on Employees' performance at PT Tetra Pak Indonesia. These research population here used saturated sample from all service engineer employees, with a total sample of 76 service engineers. The data analysis method used Structural Equation Model-Partial Least Square (SEM PLS). The research outcomes showed that innovative behaviour did not have an significant affect towards Employee performance. Competence had an positive impact in increasing the employee engagement and also this employee engagement could be able to motivate the Innovative behaviour and Employee performance

Intelligent system for fault detection of phase failure and temperature

Recently, most countries began utilizing Electronic governance (EG), which is the application of intelligence technique (IT) for delivering government services, exchange information, communicate transactions, and integrate various stand-alone systems between governments and citizen. The lack of electricity (from unstable power supply) tends to severely interrupt e-governance, as EG needs power in 24 hours per day. The phase failure, over-voltage, and frequency instability can result in the lack of electricity. This paper details the design and implementation of an intelligent fault detection system that controls the feeding power for IT equipment by calling the engineer or utilizing another power source. The system was implemented based on the Global System for Mobile communication (GSM)-sim900and Arduino microcontroller, where the Arduino code is used to implement the software. The result show that the system will try feeding the IT system the power via other power sources line until the service engineers arrive to address the problems. The intelligent system improves the reliability and stability of EG, which improves its performance and the delivery of public services to citizens.

Patient routing and process approach implementation for regional oncology service

Background . Cancer care involves a multidisciplinary approach to diagnosis and treatment of patients. A complex interaction of actors in the deployment of oncology services dictates usage of modern management technologies for improving the quality and efficiency of patient care through processes optimisation. Objectives. Provision of recommendations for patient routing based on research into the oncology service inter-level information exchange, integration of the process approach and electronic services. The lack of a unified information space with a regional oncology service has been explained. Measures are proposed for the patient routing optimisation as part of establishing a unified digital oncology service circuit. Methods . The oncology service was effectively remodelled through functional and information engineering of electronic services and the process management integration to establish a horizontal decision flow between facilities and employees on a process level bypassing the supervisor coordination. Statistical approaches were used to analyse the oncological patient population. Results . The following electronic services have been implemented: specialised patient referral routing, telemedicine and teleradiology. A comprehensive information framework has been created comprising medical, laboratory and radiological information subsystems integrated through regional electronic services of the unified state healthcare information platform. The goals, objectives, general principles, architecture and expected social economic impact on healthcare of Krasnodar Krai have been defined. Conclusion . Use of electronic services ensures an improved quality of specialised care and effective routing of patients. We perceive prospects of the integrated information platform in the extension and improvement of its subsystems’ functionality and content, sourcing more data providers and the circuit expansion to the federal and regional levels.

RAN Engine: Service-Oriented RAN Through Containerized Micro-Services

Network slicing is considered to be the enabler for a coexistence of a multitude of services with heterogeneous requirements on a multi-tenant 5G infrastructure. In the core network, it has shown its potential in customizing and extending service-specific functionality beyond a mere configuration. In the radio access network (RAN) however, service customization and functionality extension remain a challenge due to the rigid and complex nature of the RAN and the fact that all services have to be mapped onto the scarce radio resources. In this article, we present the RAN service engine that allows services to customize and extend RAN functionality using containerized micro-services. This is achieved through micro-SDKs that abstract key RAN control endpoints, and which can then be used by the services to flexibly customize and extend the RAN in order to steer control plane behavior. Through these micro-SDKs, the engine can enforce isolation between services while multiplexing them efficiently onto the infrastructure. We also present a concrete implementation of the engine with its key micro-SDKs, and demonstrate the feasibility through a prototype for the MAC scheduling control endpoint, showing the versatility of the RAN engine.

Determining threshold values of operating motor oils to diagnose internal combustion engines

Technical fluids (engine oil, antifreeze) have to meet their requirements during the standard operating life to ensure the standard service life of combustion engine systems and mechanisms. The stability of the engine oil during engine operation depends on many factors. Motor oil touches all the processes in the internal combustion engine and can serve as a source of diagnostic information, which will make it possible to carry out maintenance and repair of engine parts as needed, to increase the reliability and durability of the internal combustion engine. The results of the oil sample analysis for each indicator allow us to draw distribution density curves for the serviceable and faulty engine condition. Following the results of the analysis, it is necessary to compare the value of the index with its threshold values, separating the zone of operation condition from the zone of the engine faulty condition. Since the number of serviceable engines under operating conditions is always greater than the number of faulty ones, at the first stage of oil quality control, it is possible to determine the threshold values of indicators separating the zone of normal wear (engine serviceable condition) from the zone of increased wear. The research has resulted in an algorithm for calculating and determining the threshold values of motor oils for tractor engines operated on farms in the Omsk region. The authors selected the values based on two oil indicators: kinematic viscosity at 1000 C and flashpoint. The distribution and probability integral of these indicators are better smoothed out by the normal Gauss law. The researchers obtained the maximum and minimum values of indicators corresponding to the 5% boundary of the probability integral.

Evaluation of Student’s Performance on a T-Shaped Degree

<italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Contribution:</i> From prior studies on models and strategies used to study the academic performance of university students, it is evident that none of them either evaluates T-shaped degrees or does so according to the profile of the students’ high school provenance. The study provided in this article employs a well-established model and strategy to show the monitoring of university students’ performance in the first academic year with the premise that their heterogeneity in terms of the modalities of their high school provenance may be a determining factor as regards their performance in the various disciplines on a T-shaped degree. <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Background:</i> Universities are beginning to offer T-shaped degrees in response to the growing demand for professionals with this profile. The variety of disciplines taught on these degrees means that the students enrolled on them originate from various high school modalities, which implies a difference in their respective knowledge that may affect their performance. <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Research Questions:</i> Are a student’s high school provenance modalities a determining factor in their performance in various disciplines on a T-shaped degree? <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Methodology:</i> This study has employed the goal-oriented, context-aware, measurement, evaluation and monitoring strategy to monitor students’ performance on a Service Science, Management and Engineering degree. The five years of monitoring has made it possible to characterize students from the different modalities of provenance. <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Findings:</i> It was possible to characterize the performance in the different high school modalities using the model attributes evaluated, with the objective of proposing instruments that could help improve the students’ performance when unsatisfactory indicator results are detected.

Dynamic Inference Approach Based on Rules Engine in Intelligent Edge Computing for Building Environment Control.

Computation offloading enables intensive computational tasks in edge computing to be separated into multiple computing resources of the server to overcome hardware limitations. Deep learning derives the inference approach based on the learning approach with a volume of data using a sufficient computing resource. However, deploying the domain-specific inference approaches to edge computing provides intelligent services close to the edge of the networks. In this paper, we propose intelligent edge computing by providing a dynamic inference approach for building environment control. The dynamic inference approach is provided based on the rules engine that is deployed on the edge gateway to select an inference function by the triggered rule. The edge gateway is deployed in the entry of a network edge and provides comprehensive functions, including device management, device proxy, client service, intelligent service and rules engine. The functions are provided by microservices provider modules that enable flexibility, extensibility and light weight for offloading domain-specific solutions to the edge gateway. Additionally, the intelligent services can be updated through offloading the microservices provider module with the inference models. Then, using the rules engine, the edge gateway operates an intelligent scenario based on the deployed rule profile by requesting the inference model of the intelligent service provider. The inference models are derived by training the building user data with the deep learning model using the edge server, which provides a high-performance computing resource. The intelligent service provider includes inference models and provides intelligent functions in the edge gateway using a constrained hardware resource based on microservices. Moreover, for bridging the Internet of Things (IoT) device network to the Internet, the gateway provides device management and proxy to enable device access to web clients.

Toward a better understanding of intentionality in service engineering: a systematic review

Putting intentionality adaptation and context-awareness into service in a user transparent way is a critical concern for the pervasive computing paradigm. Several approaches have already been tested to incorporate intentionality in service engineering. However, there are limited results in terms of user intention understanding and context awareness. This systematic literature review interprets available approaches, especially those considered relevant for particular concern: intention representation, intention matching, and context influence on intention. It explains the pros and cons inherent to each proposed method. A total of 51 papers published between 2010 and 2020 were rigorously selected. The current review results demonstrate that the available literature suggests multiple approaches to intentionality adaptation. But with many gaps remaining, especially when it comes to modelling intentionality. Furthermore, this study reveals that little effort is given to handle the close relationship between context and intention.

Vehicle diagnostic system of the car engine

Support of the established technical characteristics of engines is reached by its regular service and diagnostics in particular - existence of the diagnostic programs built in the onboard computer of the car which carry out constant control of the main parameters of the engine.Based on the algorithm of vibroacoustic diagnostics, a system of vibration and vibroacoustic diagnostics of the internal combustion engine (ICE) is proposed, which can be integrated into the intelligent environment of self - diagnostics of the car (Check - Engine). The algorithm takes into account the normalized parameters and criteria for assessing the vibration state: the absolute values of displacements, velocities and accelerations and their changes.For the self-diagnostic system, it is important to develop a classifier of engine states also to determine and / or predict the failure of its parts or units. Engine vibrations can be attributed to the following types: imbalance of the 1st and 2nd order of the engine; vibration associated with combustion in the engine; auxiliary units.The analysis of a vibroacoustic signal at work of the serviceable and faulty engine is carried out, influence of various elements of a design, placement of the gauge in horizontal and vertical directions is shown on it.

Classificação de tráfego entrante em uma topologia SDN

Computer networks have become a vital tool for transporting information. The use of Software Defined Networks can enable the development of techniques to improve network performance with respect to security, quality of service and traffic engineering. The implementation of these techniques can be facilitated by classifying incoming traffic on the network. This work proposed a comparative study of machine learning algorithms for the classification of incoming traffic in an SDN topology. The classifiers' performance was assessed using the metrics accuracy, precision, recall and f1-score, in addition to the training and validation times of the models. The Random Forest algorithm was considered the most efficient in the considered traffic classification scenario. He achieved values ​​similar to the best results regarding the metrics accuracy, precision, recall and f1-score, but obtained lower values ​​in the training and validation times.

Effectiveness of Engineering Service Organizations in Global Projects Execution

Possibilities to maximize the efficiency of Service Engineering Organizations involvement are evaluated. Highlighted the importance to consider several specific features of Engineering Service companies in order to maintain the high efficiency of the global Engineering Services model. Noted that building the global Engineering Services model stimulates the development of Product Lifecycle Management systems, which require maximum formalization of all processes, which include many components, and, therefore, we are talking about a complex system. The need to model such a complex system with a purpose to determine its optimal configuration is justified. It was assumed that the Systems approach can be used to build a functional model of the Engineering Service organization, and then the identification and evaluation of available alternatives will help to find the optimal configuration of the system. Solution to quickly assess the Key Performance Indicators of the Engineering Services being created by using a model that is based on the Systems approach is proposed. Determined that the System Engineering is the most known and useful among all methods of modelling the complex systems.

Investigating the Potential Impact of Future Climate Change on UK Supermarket Building Performance

The large-scale shifts in weather patterns and an unprecedented change in climate have given rise to the interest in how climate change will affect the carbon emissions of supermarkets. This study investigates the implications of future climatic conditions on the operation of supermarkets in the UK. The investigation was conducted by performing a series of energy modelling simulations on a LIDL supermarket model in London, based on the UK Climate Projections (UKCP09) future weather years provided by the Chartered Institution of Building Services Engineers (CIBSE). Computational fluid dynamic (CFD) simulations were used to perform the experiment, and the baseline model was validated against the actual data. This investigation ascertains and quantifies the annual energy consumption, carbon emissions, and cooling and heating demand of the supermarket under different climatic projections, which further validate the scientific theory of annual temperature rise as a result of long-term climatic variation. The maximum percentage increase for the annual energy consumption for current and future weather data sets observed was 7.01 and 6.45 for the 2050s medium emissions scenario, (90th) percentile and high emissions scenario, (90th) percentile, respectively, and 11.05, 14.07, and 17.68 for the 2080s low emissions scenario, (90th) percentile, medium (90th) percentile and high emissions scenario (90th) percentile, respectively. A similar inclining trend in the case of annual CO2 emissions was observed where the peak increase percentage was 6.80 and 6.24 for the 2050s medium emissions scenario, (90th) percentile and high (90th) percentile, respectively and 10.84, 13.84, and 17.45 for the 2080s low emissions scenario, (90th) percentile, medium emissions scenario (90th) percentile and high emissions scenario (90th) percentile, respectively. The study also analyses the future heating and cooling demands of the three warmest months and three coldest months of the year, respectively, to determine future variance in their relative values.

A New Generation of Thermal Energy Benchmarks for University Buildings

In 2008, the Chartered Institution of Building Services Engineers (CIBSE TM46 UC) presented an annual-fixed thermal energy benchmark of 240 kWh/m2/yr for university campus (UC) buildings as an attempt to reduce energy consumption in public buildings. However, the CIBSE TM46 UC benchmark fails to consider the difference between energy demand in warm and cold months, as the thermal performance of buildings largely depends on the ambient temperature. This paper presents a new generation of monthly thermal energy benchmarks (MTEBs) using two computational methods including mixed-use model and converter model, which consider the variations of thermal demand throughout a year. MTEBs were generated using five basic variables, including mixed activities in the typical college buildings, university campus revised benchmark (UCrb), typical operation of heating systems, activities impact, and heating degree days. The results showed that MTEBs vary from 24 kWh/m2/yr in January to one and nearly zero kWh/m2/yr in June and July, respectively. Based on the detailed assessments, a typical college building was defined in terms of the percentage of its component activities. Compared with the 100% estimation error of the TM46 UC benchmark, the maximum 21% error of the developed methodologies is a significant achievement. The R-squared value of 99% confirms the reliability of the new generation of benchmarks.

Strategic determinants of big data analytics in the AEC sector: a multi-perspective framework

With constant flow of large data sets generated by different organisations, big data analytics promises to be a revolutionary game changer for Architecture, Engineering and Construction (AEC) industry. Despite the potential of Big Data, there has been little research conducted thus far to understand the Big Data phenomenon, specifically in the AEC industry. The objective of this research therefore is to understand the contributing factors for adopting big data in AEC firms. The investigation combined the perceived strategic value of BDA with the TOE framework (technology, organization, and environment), to develop and test a holistic model on big data adoption. A set of hypotheses derived from the extant literature was tested on data from structured surveys of about 365 firms, categorised as construction service firms (engineering and architecture) and construction firms (firms engaged in managing construction projects). The results indicated that the inhibitors and facilitators of BDA adoption are different in the construction services (architecture and engineering) and construction firms. For effective adoption of BDA solutions, the findings will guide the business managers to have realistic expectations of BDA integration challenges in AEC sector.