Demand Based Reliability: A Proposed Measurement Approach

2001 ◽  
Author(s):  
Robert F. Steele ◽  
Sal DellaVilla
Keyword(s):  
Real Time ◽  
Data Gathering ◽  
Strong Relationship ◽  
Global Market ◽  
Time Data ◽  
Environmental Friendliness ◽  
Real Time Data ◽  
The Impact ◽  
Measurement Approach ◽  
Reliability And Availability

Significant change is taking place in the power generation market. We are witnessing structural change as we move to a deregulated and competitive global market. And we can also see significant technological change, as new products are driven towards improved efficiencies, greater output and environmental friendliness. Measuring the impact of these changes in terms of efficiency, output and reduced emissions is a straightforward exercise, and the ability to judge if the change has been positive is relatively objective. However, these structural and technological changes have created challenges in terms of reliability and availability measurements. • First, our measurement approach is obsolete and has no consideration for duty cycle… The demand, the mission profile, which must be achieved for the unit to meet its economic contribution value, is the single most important issue for power producers today. • Second, if the measurements have no consideration for the demand that the unit must meet, then the measure is not tied to the profitability of the plant, and therefore the operators are forced to use non-standard measures to accommodate management reporting. • And third, the strong relationship between effective plant operations and profitability demands “real time” data gathering from the unit control or plant DCS, and transformation of the data points into meaningful information for effective decision support, specifically related to the availability and reliability of systems, components, and the full plant, with a specific focus on measuring “demand” based availability and reliability. This paper addresses the issue and the opportunities associated with developing both new standard for measuring demand related reliability and availability, as well as the focus on “real time” data capture.

Why Ecological Momentary Assessment Surveys Go Incomplete?: When It Happens and How It Impacts Data

2020 ◽  
Author(s):  
Yu-Hsiang Wu ◽  
Jingjing Xu ◽  
Elizabeth Stangl ◽  
Shareka Pentony ◽  
Dhruv Vyas ◽  
...  
Keyword(s):  
Real Time ◽  
Self Report ◽  
Data Logging ◽  
Time Data ◽  
Real Time Data ◽  
Report Data ◽  
Self Report Data ◽  
Ecological Momentary ◽  
The Impact ◽  
Momentary Assessment

Abstract Background Ecological momentary assessment (EMA) often requires respondents to complete surveys in the moment to report real-time experiences. Because EMA may seem disruptive or intrusive, respondents may not complete surveys as directed in certain circumstances. Purpose This article aims to determine the effect of environmental characteristics on the likelihood of instances where respondents do not complete EMA surveys (referred to as survey incompletion), and to estimate the impact of survey incompletion on EMA self-report data. Research Design An observational study. Study Sample Ten adults hearing aid (HA) users. Data Collection and Analysis Experienced, bilateral HA users were recruited and fit with study HAs. The study HAs were equipped with real-time data loggers, an algorithm that logged the data generated by HAs (e.g., overall sound level, environment classification, and feature status including microphone mode and amount of gain reduction). The study HAs were also connected via Bluetooth to a smartphone app, which collected the real-time data logging data as well as presented the participants with EMA surveys about their listening environments and experiences. The participants were sent out to wear the HAs and complete surveys for 1 week. Real-time data logging was triggered when participants completed surveys and when participants ignored or snoozed surveys. Data logging data were used to estimate the effect of environmental characteristics on the likelihood of survey incompletion, and to predict participants' responses to survey questions in the instances of survey incompletion. Results Across the 10 participants, 715 surveys were completed and survey incompletion occurred 228 times. Mixed effects logistic regression models indicated that survey incompletion was more likely to happen in the environments that were less quiet and contained more speech, noise, and machine sounds, and in the environments wherein directional microphones and noise reduction algorithms were enabled. The results of survey response prediction further indicated that the participants could have reported more challenging environments and more listening difficulty in the instances of survey incompletion. However, the difference in the distribution of survey responses between the observed responses and the combined observed and predicted responses was small. Conclusion The present study indicates that EMA survey incompletion occurs systematically. Although survey incompletion could bias EMA self-report data, the impact is likely to be small.

Leveraging on the Digital Twin for improving retail store daily operations management

2019 ◽  
Author(s):  
Yasmina Maizi ◽  
Ygal Bendavid
Keyword(s):  
Real Time ◽  
Operations Management ◽  
Impact Analysis ◽  
Manufacturing Sector ◽  
Research Work ◽  
Data Gathering ◽  
Time Data ◽  
Fast Development ◽  
The Face ◽  
The Impact

With the fast development of IoT technologies and the potential of real-time data gathering, allowing decision makers to take advantage of real-time visibility on their processes, the rise of Digital Twins (DT) has attracted several research interests. DT are among the highest technological trends for the near future and their evolution is expected to transform the face of several industries and applications and opens the door to a huge number of possibilities. However, DT concept application remains at a cradle stage and it is mainly restricted to the manufacturing sector. In fact, its true potential will be revealed in many other sectors. In this research paper, we aim to propose a DT prototype for instore daily operations management and test its impact on daily operations management performances. More specifically, for this specific research work, we focus the impact analysis of DT in the fitting rooms’ area.

scholarly journals Financing entrepreneurship in times of crisis: Exploring the impact of COVID-19 on the market for entrepreneurial finance in the United Kingdom

2020 ◽  
Vol 38 (5) ◽  
pp. 380-390 ◽  
Author(s):  
Ross Brown ◽  
Augusto Rocha ◽  
Marc Cowling
Keyword(s):  
United Kingdom ◽  
Real Time ◽  
Entrepreneurial Finance ◽  
Time Data ◽  
Face To Face ◽  
Policy Interventions ◽  
The United Kingdom ◽  
Real Time Data ◽  
Start Ups ◽  
The Impact

This commentary explores the manner in which the current COVID-19 crisis is affecting key sources of entrepreneurial finance in the United Kingdom. We posit that the unique relational nature of entrepreneurial finance may make it highly susceptible to such a shock owing to the need for face-to-face interaction between investors and entrepreneurs. The article explores this conjecture by scrutinising a real-time data source of equity investments. Our findings suggest that the volume of new equity transactions in the United Kingdom has declined markedly since the outbreak of the COVID-19 pandemic. It appears that seed finance is the main type of entrepreneurial finance most acutely affected by the crisis, which typically goes to the most nascent entrepreneurial start-ups facing the greatest obstacles obtaining finance. Policy makers can utilise these real-time data sources to help inform their strategic policy interventions to assist the firms most affected by crisis events.

Test and Analysis of Exhaust Pollutants from Automobiles Based on GPS Technology

2010 ◽  
Vol 40-41 ◽  
pp. 675-681
Author(s):  
Ming Li Xian ◽  
Qing Huang Yong
Keyword(s):  
Real Time ◽  
Data Gathering ◽  
Operating Conditions ◽  
Vehicle Emission ◽  
Testing System ◽  
Time Data ◽  
Gps Technology ◽  
Urban Road ◽  
Real Time Data ◽  
Object Of Study

Taking the actual running vehicles on the urban roads of Ningpo City as the object of study, by using the brand-new on-vehicle automobile exhaust real-time testing system, and through actual testing by tracking the running vehicles and real-time data gathering, The paper analyzed urban road operating conditions, the vehicle emission situation on the actual roads, obtained the relations between the operating conditions, the speed and emissions and the law by which the automobile operating conditions affect the automobile exhausts.

scholarly journals Internet of Things based Customer Relationship Management – A Research Perspective

2018 ◽  
Vol 7 (2.7) ◽  
pp. 444 ◽  
Author(s):  
Samir Yerpude ◽  
Dr Tarun Kumar Singhal
Keyword(s):  
Internet Of Things ◽  
Real Time ◽  
Customer Relationship Management ◽  
Relationship Management ◽  
Mobile Internet ◽  
Customer Relationship ◽  
Time Data ◽  
Crm System ◽  
Real Time Data ◽  
The Impact

Objectives: To study the impact of Internet of things (IoT) on the Customer Relationship Management process and evaluate the benefits in terms of customer satisfaction and customer retention. Methods: An extensive literature review was conducting wherein the constructs of CRM and IoT are studied. Various preliminary information on IoT and CRM system along with the components of Digital enablers have been evaluated. References from research papers, journals, Internet sites, statistical data sites and books were used to collate the relevant content on the subject. The study of all the relevant scenarios where there is a possible impact of IoT origin real time data on CRM was undertaken. Findings: Customer demands are continuously evolving and it is very relevant for all the organizations to align and keep pace with the change. Organizations need to be customer centric and agile to the changing market scenarios. Evaluation of the trends in mobile internet vs desktop internet was also conducted to validate the findings. Application: The usage of real time data emerging out of the IoT landscape has become a reality with the data transmitted over the Internet and consumed by the CRM system. It improves the control on the customer relationship function helping the organizations to operate within healthy and sustained profit  

scholarly journals Real-time data gathering in sensor networks

2010 ◽  
Vol 158 (5) ◽  
pp. 543-550 ◽  
Author(s):  
Yoram Revah ◽  
Michael Segal ◽  
Liron Yedidsion
Keyword(s):  
Sensor Networks ◽  
Real Time ◽  
Data Gathering ◽  
Time Data ◽  
Real Time Data

scholarly journals Metamorphosis of COVID-19 Pandemic

2020 ◽  
Author(s):  
Farhan Saif
Keyword(s):  
Real Time ◽  
Growth Model ◽  
Exponential Growth ◽  
Impact Point ◽  
Time Data ◽  
Slowing Down ◽  
Real Time Data ◽  
The Usa ◽  
Mathematical Techniques ◽  
The Impact

We show phase-wise growth of COVID 19 pandemic and explain it by comparing real time data with Discrete Generalized Growth model and Discrete Generalized Richard Model. The comparison of COVID 19 is made for China, Italy, Japan and the USA. The mathematical techniques makes it possible to calculate the rate of exponential growth of active cases, estimates the size of the outbreak, and measures the deviation from the exponential growth indicating slowing down effect. The phase-wise pandemic evolution following the real time data of active cases defines the impact-point when the preventive steps, taken to eradicate the pandemic, becomes effective. The study is important to devise the measures to handle emerging threat of similar COVID-19 outbreaks in other countries, especially in the absence of a medicine.

scholarly journals Adoption of Cloud-based E-Health Record through the Technology, Organization and Environment Perspective

2018 ◽  
Vol 7 (4.35) ◽  
pp. 609 ◽  
Author(s):  
Hidayah Sulaiman ◽  
Asma Magaireh ◽  
Rohaini Ramli
Keyword(s):  
Cloud Computing ◽  
Real Time ◽  
Data Access ◽  
Healthcare Setting ◽  
Easy Access ◽  
Management Support ◽  
Computing Technology ◽  
Time Data ◽  
Real Time Data ◽  
The Impact

With the ever increasing cost of investing in technological innovations and the amount of patient data to be processed on daily basis, healthcare organizations are in dire need for solutions that could provide easy access and better management of real time data with lower cost.  The emerging trend of organizations optimizing cost in investing less on physical hardware has brought about the use of cloud computing technology in various industries including healthcare.  The use of cloud computing technology has brought better efficiency in providing real time data access, bigger storage capacity and reduction of cost in terms of maintenance. Although numerous benefits have been publicized for organizations to adopt the technology, nevertheless the rate of adoption is still at is infancy. Hence, this study explores factors that may affect the adoption of cloud-based technology particularly within the healthcare context. A quantitative study was conducted through the distribution of survey in Jordanian healthcare facilities. The survey was conducted to gauge the understanding of cloud-based EHR concepts identified through literature and validate the factors that could potentially provide an impact towards the cloud-based EHR adoption. The theoretical underpinnings of Technology-Organization-Environment (TOE) were investigated in studying the impact towards the adoption of cloud-based EHR. Results indicate that Technology-Organization-Environment factors such as privacy, reliability, security, top management support, organizational readiness, competition and regulatory environment are critical factors towards the adoption of cloud technology within a healthcare setting.

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