Visualization approaches for understanding uncertainty in flow diagrams

Vosough, Zana; Kammer, Dietrich; Keck, Mandy; Groh, Rainer

doi:10.1016/j.cola.2019.03.002

Cited by 8 publications

(4 citation statements)

References 22 publications

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“…Certain innovations in the graphica l display of data particularly lend themselves to the visualiza tion and snapshot analysis of streaming sensor data. Vosough et al [74] introduce a refinement to the display of ribbon flow diagrams involving the communication of uncertainty; the work involves the utilization of a case study based on data sets relating to an industrial pump product, mixing both technical parameters with market data in the sa me graph. Qin et al [75] explore the possibility to automate the process of matching data with appropriate diagrammatic visu a liza tio n types.…”

Section: Visualization and Interactionmentioning

confidence: 99%

Human in the Loop: Industry 4.0 Technologies and Scenarios for Worker Mediation of Automated Manufacturing

Turner

Chen

et al. 2021

IEEE Access

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Industry 4.0 derived technologies have the potential to enable a new wave of digital manufacturing solutions for semi and fully automated production. In addition, this paradigm enco m p a s ses the use of communication technologies to transmit data to processing stations as well as the utilization of cloud based computational resources for data mining. Despite the rise in automation, future manufactu rin g systems will initially still require humans in the loop to provide supervisory level mediation for even the most autonomous production scenarios. Through a structured review, this paper details a number of key technologies that are most likely to shape this future and describes a range of scenarios for their use in delivering human mediated automated and autonomous production. This paper argues that in all cases of future manufacturing management it is key that the human has oversight of critical information flows and remains an active participant in the delivery of the next generation of production systems.

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Section: Visualization and Interactionmentioning

confidence: 99%

Human in the Loop: Industry 4.0 Technologies and Scenarios for Worker Mediation of Automated Manufacturing

Turner

Chen

et al. 2021

IEEE Access

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“…In our experience, using different shades of the same color palette creates challenges and confusion in interpreting data, as the arcs overlap. A diverging color palette for the nodes on the y-axis and distinct non-gradient colors may ease visualization [13]. For specific transitions, adjusting transparency allows arcs to fade into the background while others are highlighted.…”

Section: Creating Sankey Flow Diagramsmentioning

confidence: 99%

Overview of Sankey flow diagrams: Focusing on symptom trajectories in older adults with advanced cancer

Otto

Culakova

Meng

et al. 2022

Journal of Geriatric Oncology

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This perspectives paper provides an overview of how to read and interpret a Sankey, examples using symptom data from older adults with advanced cancer, a synopsis of medical literature, and comments on creating and using the diagram for presentation of data. From prior reports and our own, we conclude Sankeys are an excellent tool for visualizing the changing status of older patients with cancer. Older adult symptom data is used as an example with data dispalyed in a range of Sankey flow diagrams. Because there is large heterogeneity in aging, different subgroups can be examined. In a single diagram, Sankey can show both the likelihood and variability of patients' future status from their current status.

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“…Islam et al [16] proposed a new visualization methodology to enable supply chain operators to collaborate effectively in the design process of the FTS, which enables the maintenance of a streamlined flow of information, minimizes information loss, and improves supply chain performance. Vosough et al [17] investigated three visualization techniques that are applicable to convey uncertainty information in the strips of a flow diagram.…”

Section: Introductionmentioning

confidence: 99%

Visual evaluation and information improvement method of smart factory layout based on information value added

Wang,

Dou,

Ouyang

et al. 2024

J. Phys.: Conf. Ser.

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The process of Industry 4.0 is constantly promoted. In order to realize the high-quality connotation development of enterprises, manufacturing enterprises need to carry out information transformation and upgrading. The technology of information flow analysis can consistently assess the worth of the factory, overcome existing technical challenges, and achieve intelligent modernization and enhancement of the system. This study presents a visualization and evaluation of the factory’s layout, production lines, and workstation from three perspectives: macro, meso, and micro. To begin, a value added heat map (VAHM) is created by examining the visualization technique for information value added information (IVA). This analysis aims to assess the extent of information wastage in terms of the factory’s physical space, resources, and staff. Additionally, a method for analyzing the information gain of a production line, which is based on the concept of distributed cognition, is introduced. This method evaluates the production line by integrating the economic principle of information processing (EPIP). Furthermore, when assessing complexity, the volume of information in workstations is measured and enhanced by applying the principle of information processing economy. Ultimately, the method’s validity and feasibility are confirmed by applying it to real-world manufacturing industry scenarios.

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Visualization approaches for understanding uncertainty in flow diagrams

Cited by 8 publications

References 22 publications

Human in the Loop: Industry 4.0 Technologies and Scenarios for Worker Mediation of Automated Manufacturing

Human in the Loop: Industry 4.0 Technologies and Scenarios for Worker Mediation of Automated Manufacturing

Overview of Sankey flow diagrams: Focusing on symptom trajectories in older adults with advanced cancer

Visual evaluation and information improvement method of smart factory layout based on information value added

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