Best Paper Award at the International Manufacturing Conference 2024

Ilabo team
May 22, 2024
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Best Paper Award at the International Manufacturing Conference 2024
Home > Blog > Best Paper Award at the International Manufacturing Conference 2024

On 14-16 May 2024, the MANUFACTURING 2024 conference was held in Poznań. The conference is organised by the Foundation for the Development of Poznan University of Technology and the Faculty of Mechanical Engineering at Poznan University of Technology.

The aim of the MANUFACTURING 2024 conference was to review the state of knowledge, present the results of scientific work, implementations and innovations, as well as to provide an international forum for the dissemination and exchange of experience in the field of design and machines building, manufacturing technologies, metrology, rapid prototyping and virtual reality as well as management and production management. Additional goals of the MANUFACTURING 2024 conference are the integration of the scientific community with the economic environment, enabling the establishment of cooperation with partners from industry and business, as well as with domestic and foreign research and development centers.

During the conference, ILABO team represented by Tomasz Bartkowiak received an award for the best article presented during the conference.

Article title: Manufacturing line-level root cause analysis and bottleneck detection using the digital shadow concept and cloud computing.

Below you can find an abstract of the article with selected views. The entire article is available under this link: https://link.springer.com/chapter/10.1007/978-3-031-56444-4_8

Also, you can find some more information on the subject discussed in the paper in our Knowledge base:

The paper introduces a method for online detection and root-cause analysis for production line bottlenecks in manufacturing systems, aiming to enhance reliability and productivity.

Key aspects covered in the study include:

  • Emphasizing the interconnectedness of manufacturing systems and the impact of equipment faults on overall performance.
  • Discussion on the existing fault propagation methods, highlighting the need for a comprehensive approach considering the entire production process.
  • Introducing a root-cause algorithm leveraging the digital shadow concept to analyze machine states and historical data for fault identification.
  • Presenting bottleneck detection methods such as analysis of active periods and an arrow method based on machine blockages and starvations.

The study focuses on machine work states, distinguishing between internal and external causes, thus determining the root-cause machine affecting the entire line. A Gantt chart-based approach considers the relative timing of events, enhancing accuracy in root-cause determination.

Gantt chart showing the sequence of events that were considered in determining the root cause of the failure.

Work spectrum downtime PackOS

A view of the work spectrum from LogiX – PackOS indicating the machine that caused the downtime on the line.

The study used a cloud-based system named LogiX, designed for real-time data processing and visualization, while seamlessly integrating the principles of Industry 4.0. Through a detailed case study, the effectiveness of the proposed methods was evaluated over an 8-hour shift period within a bottle filling and packaging line. Impressively, the root-cause analysis achieved a detection efficiency of 89.23%, showcasing its practical utility. Additionally, bottleneck detection methods, including both analysis of active periods and the arrow method, successfully identified the Labeller as a potential bottleneck in the production process.

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