Human Factors Evaluation of Energy Visualization Dashboards

Nimbarte, Ashish D.; Smith, Nathaniel; Gopalakrishnan, Bhaskaran

doi:10.1177/10648046211028693

Cited by 3 publications

(9 citation statements)

References 11 publications

(13 reference statements)

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“…Although this approach already lowers the barrier for the integration of visualisations by manufacturing practitioners, there is still a challenge on deciding which visualisations are most appropriate for the application at hand; which ones can deliver the highest value for better decision making. Recent studies have shown how visualisations' "pre-attentive attributes" allow users to quickly identify differences in data without much cognitive processing [17]. Future work will include the development of pre-defined solutions made available through the solution configurator, providing the user with a selection of the most suitable visualisation components for a given application.…”

Section: Discussion and Future Workmentioning

confidence: 99%

Visualisation on a Shoestring: A Low-Cost Approach for Building Visualisation Components of Industrial Digital Solutions

Martínez-Arellano

McNally

Chaplin

et al. 2022

Service Oriented, Holonic and Multi-Agent Manufacturing Systems for Industry of the Future

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The rate of adoption of digital solutions in manufacturing environments remains low despite the benefits these can bring. This is particularly acute among industrial small and medium enterprises (SMEs), who typically do not have the confidence to adopt new technologies and for which cost and a lack of skills remain key barriers. Most digital solutions require some type of visualisation component, being a vital way to the interpret and use effectively the data. Data visualisation on its own provides an opportunity to bridge the gap of digitalisation in SMEs by providing them invaluable process insights in an efficient manner without requiring high levels of training or expertise. However, as with other digital technologies, software components such as data analytics and visualisation are commonly developed, deployed, and maintained by a third party, and SMEs lack the expertise to understand how to implement or change visualisations and how they can be applied in the manufacturing domain. The Digital Manufacturing on a Shoestring approach proposes using off-the-shelf components, both hardware and software, to develop low-cost digital solutions with minimal expert knowledge. The underlying Shoestring architecture enables the incremental connectivity of different solution components using a service-oriented approach. This paper introduces the implementation of visualisation-as-a-service, where the visual components of a digital solution is dynamically created by a set of reusable, configurable and modular elements. We also introduce the use of templates for the no-code creation of visual solutions, taking advantage of the re-usability of visual components across different digital solutions.

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Section: Discussion and Future Workmentioning

confidence: 99%

Visualisation on a Shoestring: A Low-Cost Approach for Building Visualisation Components of Industrial Digital Solutions

Martínez-Arellano

McNally

Chaplin

et al. 2022

Service Oriented, Holonic and Multi-Agent Manufacturing Systems for Industry of the Future

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“…More than half of the tools (53%) present energy results in isolated and unrelated visualizations, while the other half (47%) have designed a dashboard-like interface that allows for exploring data in an organized way, contextualizing the information and hierarchizing graphics. In the latter case, the interface allows the user to interact with the information [44][45][46][47][48][49][50], choose parameters [10,33,[51][52][53][54][55][56][57], and analyze the context through 3D visualizations [10,[50][51][52][56][57][58] or floor plans of the building [10,44,53,56,58]. It is also noted that the dynamic capacity of data visualization is an underutilized feature in the tools.…”

Section: Scientific Literaturementioning

confidence: 99%

“…Regarding the third LOD of data analysis, 40% of the tools allow the user to delve into the specific value and, through interactions such as clicks, identify the variables that influence the metrics according to time periods [2,53,59,60]. Moreover, they allow the association of these variables with consumption ranges [1,55,59,61], presenting data divided by zones or environments [33,53,58] and parameters or categories [44][45][46]49]. Likewise, at this same level, it is possible to compare metrics to a performance time-scale [47,48,51,55,59,61,62], showing values by seasons, months, days, hours, and sub-hours.…”

Section: Scientific Literaturementioning

confidence: 99%

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Building Energy Simulation and Monitoring: A Review of Graphical Data Representation

2022

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Data visualization has become relevant in the framework of the evolution of big data analysis. Being able to understand data collected in a dynamic, interactive, and personalized way allows for better decisions to be made when optimizing and improving performance. Although its importance is known, there is a gap in the research regarding its design, choice criteria, and uses in the field of building energy consumption. Therefore, this review discusses the state-of-the-art of visualization techniques used in the field of energy performance, in particular by considering two types of building analysis: simulation and monitoring. Likewise, data visualizations are categorized according to goals, level of detail and target users. Visualization tools published in the scientific literature, as well as those currently used in the IoT platforms and visualization software, were analyzed. This overview can be used as a starting point when choosing the most efficient data visualization for a specific type of building energy analysis.

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“…In the power plants, neglecting PSFs, including human factors, and sustainable integration with workplace energy management performance EMP resulted in an evident weakness in the energy management performance of power plants. Therefore, the integration between CSFs of PSFs and CSFs of EMP remains a research gap and an urgent problem that needs to be solved according to previous studies [3,4]. Poor performance in the industrial sector, especially in the electricity sector, negatively affects the power plant and contributes to the increase in human errors and the weakness of human factors [5].…”

Section: Introductionmentioning

confidence: 99%

Novel Approach to Energy Management via Performance Shaping Factors in燩ower Plants

Ajmi¹,

Mahmood²,

Jamaludin³

et al. 2022

Computers, Materials &Amp; Continua

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The literature that a lack of integration between the performance shaping factors (PSFs) and the energy management performance (EMP) is one of the critical problems that prevent performance improvement and reduces the power plant's efficiency. To solve this problem, this article aims to achieve two main objectives: (1) Systematically investigate and identify the critical success factors (CSFs) for integration with PSFs and EMP; (2) Develop a novel modelling approach to predict the performance of power plants based on innovative integrated strategies. The research methodology is grounded on the theoretical and practical approach to improving performance. The Newcastle Ottawa Scale (NOS) was used to assess the quality of the literature that met the criteria. To ensure the reliability and accuracy of the proposed model, the researchers developed a hypothesis and evaluated the CSFs via a case study in the Iraqi power plants. The findings of this study succeeded in developing a novel modeling approach to predict the performance by integrating the CSFs of both the PSFs and EMP to increase the positive interaction and energy efficiency of power plants. The results confirmed the validity of the selected hypotheses and verified the positive and important relationship with the success and improvement of the performance in power plants. However, the lack of consistency and balance in the current studies indicates that the performance strategy in power plants did not receive sufficient attention and needs further investigations.

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Human Factors Evaluation of Energy Visualization Dashboards

Cited by 3 publications

References 11 publications

Visualisation on a Shoestring: A Low-Cost Approach for Building Visualisation Components of Industrial Digital Solutions

Visualisation on a Shoestring: A Low-Cost Approach for Building Visualisation Components of Industrial Digital Solutions

Building Energy Simulation and Monitoring: A Review of Graphical Data Representation

Novel Approach to Energy Management via Performance Shaping Factors in燩ower Plants

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