Prøveforelesning og disputas – MSc Beibei Shu

Beibei Shu disputerer for ph.d.-graden i ingeniørvitenskap og vil offentlig forsvare avhandlingen / Beibei Shu will defend his thesis for the PhD degree in Engineering Science:

“Architectures and technologies for increased agility in small-scale manufacturing systems”

Avhandlingen er tilgjengelig her / The doctoral thesis is available here. 

Auditoriet er åpent for publikum. Disputasen vil også bli strømmet. Opptak av disputasen vil være tilgjengelig i en måned.
The auditorium is open to the public. The defense will be streamed. A recording of the defense will be available for one month.

Prøveforelesningen starter kl. 10:15 / The trial lecture starts at 10:15. Tittel / title:

“The future of augmented reality in robotics and manufacturing systems”

Disputasen starter kl. 12:15 / The defense starts at 12:15.

Prøveforelesning og disputas strømmes her / The trial lecture and defense will be streamed here.

Sammendrag av avhandlingen / Summary of the thesis:

The rapid booming of industry 4.0 technologies has been boosting further development of industrial manufacturing systems in the recent two decades. An increasing number of disruptive yet enabling technologies are becoming available for industrial applications. However, while the factories becoming more complex, a proliferation of incompatible systems that have been developed by different vendors or suppliers become a huge challenge to enterprises in reaping the technological advantages. A generalized architecture for integrating various manufacturing systems will be valuable as it’s effectively and efficiently facilitating technology planning, system designing, implementation, maintenance, and upgrading.

From the Small and Medium-sized Enterprises’ (SMEs) perspective, the implementation of advanced industry 4.0 technologies is crucial to their business survival. It seems impossible to develop a system that can help all SMEs businesses, however, when the vital technology can be developed as a module, more SMEs can quickly get the benefit. Therefore, a generalized architecture for the manufacturing system is needed, so the different vital technologies can be developed as modules and combined to form the various manufacturing systems with the same architecture.

There are several novel industry 4.0 technologies that have been studied during this PhD project: in paper 1, a digitized production system control method is introduced for system remote monitoring/supervision and reducing the hardware configuration; in paper 2, a digital twinmodule with the simulation is designed to enhance the development of high level Human-Robot Collaboration (HRC) tasks; in paper 3, various interaction methods between digital twin with human have been proposed to promote the usage of the digital twin; in paper 4, a flexible HRC architecture with its demonstration has been proposed to ease the difficulty of the emerging industry 4.0 technologies’ fusion and upgrading; in paper5, an industrial robot universal remote control graphical user interface has been proposed and the experiment showed the operator could program the robot regardless of the geographic distance.

This study is directed especially towards SMEs in order to strengthen their business operation and contributes to a sustainable development. The dissertation proposes and develops generalized architectures and selected technologies that can be applied to most current and future manufacturing tasks. The main contributions and effects of my work are:

1. Introducing generalized architectures gives a unified and common framework for enterprises, developers and system integrators to work within. A common language and understanding and a holistic view on the manufacturing operation.
2. Analyzing several Industry 4.0 technologies in terms of availability, complexity and readiness will guide small-scale manufacturing enterprises in their choice of direction when developing their manufacturing system.
3. Presenting several system demonstrations offers a glance at the architecture’s flexibility and gives insight in the power of selected technologies.

Veiledere / Supervisors:

Hovedveileder / Main supervisor:
Professor Bjørn Solvang, Department of Industrial Engineering, UiT The Arctic University of Norway.

Medveiledere / Co-supervisors:
Professor Arne Lakså, Department of Computer Science and Computational Engineering, UiT The Arctic University of Norway.

Bedømmelseskomité / Evaluation committee:

Professor Knut Sørby, Department of Mechanical and Industrial Engineering, NTNU (1st opponent),

Dr. Mikko Sallinen, Convergent Information Technologies GmbH (2nd opponent),

Associate Professor Tanita Fossli Brustad, Department of Computer Science and Computational Engineering, UiT The Arctic University of Norway (administrator of the committee).

Prøveforelesning og disputas ledes av prodekan for forskning, Svein-Erik Sveen / The trial lecture and defense is led by Vice Dean of research, Svein-Erik Sveen.

De som ønsker å opponere ex auditorio kan sende e-post til Svein-Erik Sveen / Opponents ex auditorio should contact Svein-Erik Sveen.

Når: 16. juni 2022 kl. 10.15–16.00
Hvor: Auditorium 1
Studiested: Digitalt, Narvik
Målgruppe: Ansatte, Studenter, Gjester / eksterne, inviterte
Kontakt: Audun Reigstad
E-post: audun.reigstad@uit.no
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