• ResearchGate
  • Zenodo
  • Twitter
  • LinkedIn
  • Instagram
  • Facebook
  • Youtube
  • Rss
Human-Computer Interaction & Visual Analyitics Reasearch Group (vis) at Darmstadt University of Applied Sciences (h_da)
  • Home
  • Research
    • Research Fields
    • Application Scenarios
    • Projects
    • Publications
  • Publications
  • Technologies
    • Scitics Trend Analytics Technology
    • SmartEval Evaluation Technology
    • Services
  • Teaching
    • Lectures
    • Practical Courses
    • Bachelor & Master Theses
  • Team
    • Offerings
    • Contact
  • Network
  • Search
  • Menu Menu
You are here: Home1 / Industry 4.0

Tag Archive for: Industry 4.0

Book Chapter published in Student Handbook “Praxishandbuch Forschungsdatenmanagement”

21/01/2021/in Allgemein, Lecture, Publication, Research, Teaching/by Dirk Burkhardt

We are glad to announce that our chapter to the student handbook “Praxishandbuch Forschungsdatenmanagement” (Engl.: practice handbook research data management) was accepted and got printed at De Gruyter. Our chapter addresses the foundations of Data Visualization, which is explained on behalf of selected examples.

The book covers nowadays societal research challenges in pespective of data management and how current approaches in research can helo to handle it. Therewith, events such as the entry into force of the code “Guidelines for Safeguarding Good Scientific Practice” of the German Research Foundation (DFG) or the establishment of the National Research Data Infrastructure (NFDI) and the European Open Science Cloud (EOSC) put providers, producers and users of research data in front of specialist, technical, legal and organizational challenges. The practical handbook for research data management comprehensively covers all relevant aspects of research data management and the current framework conditions in the data ecosystem.

In particular, the practical implications of data policy and law, the respective data market, data culture, personal qualification, data management and “FAIR” data transfer and reuse are examined. The practical handbook also provides an overview of projects, developments and challenges in Research data management.

https://vis.h-da.de/wp-content/uploads/2021/01/research-data-book-2020_banner.jpg 271 937 Dirk Burkhardt https://vis.h-da.de/wp-content/uploads/2019/10/LG0_vis_RG_light_Blue_huge_cutted-300x145.png Dirk Burkhardt2021-01-21 09:57:382021-01-22 15:37:13Book Chapter published in Student Handbook “Praxishandbuch Forschungsdatenmanagement”

Accepted Paper at International Conference on Industry 4.0 and Smart Manufacturing

30/09/2020/in Allgemein, Conference, h_da/by Kawa Nazemi

Over the past few years, the growing and intensive development of information technology in the manufacturing industry has led to a significant change in the methods and tools supporting the factories of the future. The hot topics around Industry 4.0 and smart manufacturing aim at the digital and organizational transformation of traditional factories and industrial systems as well as several other sectors. The International Conference on Industry 4.0 and Smart Manufacturing (ISM 2020) provides the perfect setting and a unique opportunity for knowledge exchange, the review and discussion of theoretical advances, research results, and industrial experiences, among scientists, researchers, decision makers, practitioners and students.

Paper: CONTEXT: An Industry 4.0 Dataset of Contextual Faults in a Smart Factory

Abstract:
Cyber-physical systems in smart factories get more and more integrated and interconnected. Industry 4.0 accelerates this trend even further. Through the broad interconnectivity a new class of faults arise, the contextual faults, where contextual knowledge is needed to find the underlying reason. Fully-automated systems and the production line in a smart factory form a complex environment making the fault diagnosis non-trivial. Along with the dataset, we give a first definition of contextual faults in the smart factory and name initial use cases. Additionally, the dataset encompasses all the data recorded in a current state-of-the-art smart factory. We also add additional information measured by our developed sensing units to enrich the smart factory data even further. In the end, we show a first approach to detect the contextual faults in a manual preliminary analysis of the recorded log data.

Link to Paper: DOI: 10.1016/j.procs.2021.01.265

 

The whole proceedings of the ISM 2020 are available under: Elsevier.

https://vis.h-da.de/wp-content/uploads/2020/09/ISM.png 434 1034 Kawa Nazemi https://vis.h-da.de/wp-content/uploads/2019/10/LG0_vis_RG_light_Blue_huge_cutted-300x145.png Kawa Nazemi2020-09-30 16:45:392022-02-03 01:58:00Accepted Paper at International Conference on Industry 4.0 and Smart Manufacturing

Two Paper Accepted at 24rd Internation Conference Information Visualization (iV 2020)

04/08/2020/in Allgemein, Event, Publication, Research, Scitics/by Dirk Burkhardt

We are very glad to be accepted for presenting our papers titled “Comparison of Full-text Articles and Abstracts for Visual Trend Analytics through Natural Language Processing” and “An Industry 4.0-Ready Visual Analytics Model for Context-Aware Diagnosis in Smart Manufacturing” at the high-class conference Information Visualisation Conference (iV 2020). Due to Corona epidemic the conference is hold virtually. The iV 2020 is an international conference that aims to provide a foundation for integrating the human-centered, technological and strategic aspects of information visualization to promote international exchange, cooperation and development.

Paper #1: Comparison of Full-text Articles and Abstracts for Visual Trend Analytics through Natural Language Processing

Abstract:
Scientific publications are an essential resource for detecting emerging trends and innovations in a very early stage, by far earlier than patents may allow. Thereby Visual Analytics systems enable a deep analysis by applying commonly unsupervised machine learning methods and investigating a mass amount of data. A main question from the Visual Analytics viewpoint in this context is, do abstracts of scientific publications provide a similar analysis capability compared to their corresponding full-texts? This would allow to extract a mass amount of text documents in a much faster manner. We compare in this paper the topic extraction methods LSI and LDA by using full text articles and their corresponding abstracts to obtain which method and which data are better suited for a Visual Analytics system for Technology and Corporate Foresight. Based on a easy replicable natural language processing approach, we further investigate the impact of lemmatization for LDA and LSI. The comparison will be performed qualitative and quantitative to gather both, the human perception in visual systems and coherence values. Based on an application scenario a visual trend analytics system will further illustrate the outcomes.

Link to paper/fulltext: DOI: 10.1109/10.1109/IV51561.2020.00065

More information about the technology: Scitics for Visual Trend Analytics

Paper#2: An Industry 4.0-Ready Visual Analytics Model for Context-Aware Diagnosis in Smart Manufacturing

Abstract:
The integrated cyber-physical systems in Smart Manufacturing generate continuously vast amount of data. These complex data are difficult to assess and gather knowledge about the data. Tasks like fault detection and diagnosis are therewith difficult to solve. Visual Analytics mitigates complexity through the combined use of algorithms and visualization methods that allow to perceive information in a more accurate way. Thereby, reasoning relies more and more on the given situation within a smart manufacturing environment, namely the context. Current general Visual Analytics approaches only provide a vague definition of context. We introduce in this paper a model that specifies the context in Visual Analytics for Smart Manufacturing. Additionally, our model bridges the latest advances in research on Smart Manufacturing and Visual Analytics. We combine and summarize methodologies, algorithms and specifications of both vital research fields with our previous findings and fuse them together. As a result, we propose our novel industry 4.0-ready Visual Analytics model for context-aware diagnosis in Smart Manufacturing.

Link to paper/fulltext: DOI: 10.1109/10.1109/IV51561.2020.00064

https://vis.h-da.de/wp-content/uploads/2020/05/IV2020_neu.jpg 1116 1920 Dirk Burkhardt https://vis.h-da.de/wp-content/uploads/2019/10/LG0_vis_RG_light_Blue_huge_cutted-300x145.png Dirk Burkhardt2020-08-04 08:23:082021-06-08 10:55:17Two Paper Accepted at 24rd Internation Conference Information Visualization (iV 2020)

Advanced Seminar toward Visual Analaytics in next Summer Semester at h_da/FBI (computer science)

09/03/2020/in h_da, Seminar, Teaching/by Dirk Burkhardt

In the upcoming summer semester 2020, our doctoral students provide an advanced seminar at the department of computer science at the Darmstadt University of Applied Sciences. The topic of the seminar will be toward “Visual Analytics for Smart Manufacturing and Trend Analysis”:

Due to the increasing digitization, analyzes are a constant necessity, which also applies to the identification of errors, problems or opportunities for improvement. With visual analytics, the combination of algorithmic and massive calculation opportunities of computer-based systems on the one side as well as the visual and cognitive skills of the users on the other side are used together. The seminar focuses on the use of visual analytics in the two current areas of smart manufacturing and trend analysis. On behalf of the given task, current approaches, methods and implementations should be researched and examined. The goal should be a scientific elaboration based on empirical and scientific standards.

Interested students are invited to register soon, since the number of places will be limited.

Due to virtual lecturing, please note the course information in Moodle!

https://vis.h-da.de/wp-content/uploads/2019/08/Teaching.jpg 900 1350 Dirk Burkhardt https://vis.h-da.de/wp-content/uploads/2019/10/LG0_vis_RG_light_Blue_huge_cutted-300x145.png Dirk Burkhardt2020-03-09 08:30:002022-02-02 11:12:31Advanced Seminar toward Visual Analaytics in next Summer Semester at h_da/FBI (computer science)

Categories

  • Allgemein (37)
  • Business (6)
    • Conference (4)
    • Workshop (1)
  • News (28)
    • Action (3)
    • Deadline (1)
    • Event (12)
  • Personal (1)
  • Research (48)
    • Action (7)
    • Book (1)
    • Conference (10)
    • EUT+ (1)
    • h_da (10)
    • Journal (4)
    • Project (8)
    • Prototype (2)
    • Publication (20)
    • Workshop (4)
  • Talk (3)
  • Teaching (29)
    • Demo (3)
    • h_da (15)
    • Lecture (6)
    • Practical Experience (1)
    • Seminar (1)
    • Thesis (10)
    • TU Darmstadt (5)
  • Technology (23)
    • Scitics (18)
    • SmartEval (1)

Tags

Artificial Intelligence (8) Big data Analytics (6) Business Analytics (17) Business Information Systems (5) Business Management (5) CERC (5) Collaboration (16) Conference (7) Data Analysis (9) Data Analytics (6) Data Mining (9) Data Science (5) Decision Making (6) Digital Libraries (7) eGovernance (6) eGovernment (9) Europe (7) Human-Computer Interaction (5) h_da (6) Information Visualization (19) Innovation Management (13) Intelligent Visualization (6) iV (8) Machine Learning (7) Master Thesis (5) Multimedia (5) Research (24) Research Networks (9) Research Project (9) Scientific Data (5) Simulation (5) Teaching (4) Technology Management (9) Text Mining (13) Thesis (5) Trend Analysis (11) Trend Analytics (8) User-Centered Design (18) Visual Analytics (46) Visual Computing (6) Visual Interfaces (6) Visualization (9) Visual Trend Analysis (30) Visual Trend Analytics (22) Workshop (4)

History

Recent News

  • Shahrukh Badar defended his Master Thesis on Process Mining for Workflow-Driven Assistance in Visual Trend Analytics27/04/2022 - 9:00
  • Sibgha Nazir defended her Master Thesis on Visual Analytics on Enterprise Reports for Investment and Strategical Analysis29/03/2022 - 8:31
  • Call for Articles to Special Issue in Journal of Electronics09/03/2022 - 9:37

About | Imprint | Data Privacy

© 2022 Research Group on Human-Computer Interaction & Visual Analytics (vis) – Darmstadt University of Applied Sciences (h_da)

Scroll to top

This website uses cookies to enhance its ease of use. Click "Learn More" to get detailed descriptions and further options!

OKLearn More

Cookie and Privacy Settings



How we use cookies

We may request cookies to be set on your device. We use cookies to let us know when you visit our websites, how you interact with us, to enrich your user experience, and to customize your relationship with our website.

Click on the different category headings to find out more. You can also change some of your preferences. Note that blocking some types of cookies may impact your experience on our websites and the services we are able to offer.

Essential Website Cookies

These cookies are strictly necessary to provide you with services available through our website and to use some of its features.

Because these cookies are strictly necessary to deliver the website, refusing them will have impact how our site functions. You always can block or delete cookies by changing your browser settings and force blocking all cookies on this website. But this will always prompt you to accept/refuse cookies when revisiting our site.

We fully respect if you want to refuse cookies but to avoid asking you again and again kindly allow us to store a cookie for that. You are free to opt out any time or opt in for other cookies to get a better experience. If you refuse cookies we will remove all set cookies in our domain.

We provide you with a list of stored cookies on your computer in our domain so you can check what we stored. Due to security reasons we are not able to show or modify cookies from other domains. You can check these in your browser security settings.

Other external services

We also use different external services like Google Webfonts, Google Maps, and external Video providers. Since these providers may collect personal data like your IP address we allow you to block them here. Please be aware that this might heavily reduce the functionality and appearance of our site. Changes will take effect once you reload the page.

Google Webfont Settings:

Google Map Settings:

Google reCaptcha Settings:

Vimeo and Youtube video embeds:

Privacy Policy

You can read about our cookies and privacy settings in detail on our Privacy Policy Page.

Datenschutzerklärung
Accept settingsHide notification only