Tyrone Machado’s Public Defence on A Path Towards Business Cases for Automated and Autonomous Heavy-Duty Mobile Machines will take place 22 November

MORE early stage researcher, Tyrone Machado will publicly defend his doctoral dissertation, A Path Towards Business Cases for Automated and Autonomous Heavy-Duty Mobile Machines: An Interdisciplinary Approach, at the Faculty of Engineering and Natural Sciences, Tampere University, on Friday, 22 November 2024, at 12:00. It will take place in auditorium K1702, Konetalo building, Hervanta campus, Tampere, with Professor Aki Mikkola from LUT University and Doctor Harri Kulmala from DIMECC Oy serving as Opponents. Professor Reza Ghabcheloo will act as the Custos.

Tyrone’s research, grounded in Automation Science and Engineering, tackles the limited commercialisation of autonomous heavy-duty mobile machines (HDMMs) beyond mining applications. While autonomous dump trucks have been effectively employed in mines for years, wider adoption for other HDMMs, like excavators and wheel loaders, remains limited. Through an interdisciplinary lens combining engineering, business, and management, Tyroneexplores new business frameworks that could drive broader adoption of these technologies.

Tyrone points out that the HDMM sector faces pressing labour shortages due to ageing workforces and the need for highly skilled operators. “Would you work in an environment where your body is subjected to adverse conditions like dust, snow, rain, loud noises, and vibrations?” Tyrone asks, highlighting the difficult conditions faced by HDMM operators. He contends that autonomous HDMMs can mitigate these labour issues, enhancing operational efficiency and safety while reducing costs.

Tyrone’s research emphasises that fostering interdisciplinary collaboration will be crucial in overcoming barriers to automation in the HDMM sector and unlocking its full potential.

The public defence will take place at 12:00 22 November 2024. The public defence can be followed via remote connection. 

Daniel Eriksson successfully defends PhD on AI for automating wheel loader operations

MORE Early Stage Researcher, Daniel Eriksson, has successfully defended his doctoral dissertation at Tampere University on Friday, 1 November 2024. His research focuses on using artificial intelligence (AI) to enhance the efficiency of wheel loaders in construction, addressing critical labour shortages in the industry.

In his dissertation, Automatic Bucket Filling: A Machine Learning Approach (available online), Daniel investigates how AI can automate the challenging task of loading materials. He developed AI models based on real-world data from expert operators, enabling wheel loaders to operate with human-level precision. His work also explores methods for adapting AI to handle various material types, offering innovative solutions to boost productivity on construction sites.

We extend our congratulations to Daniel on this impressive achievement.

Daniel Eriksson to defend his PhD on AI for automating wheel loader operations

MORE Early Stage Researcher, Daniel Eriksson will defend his doctoral dissertation on Friday, 1 November 2024, at Tampere University. His research focuses on using artificial intelligence (AI) to improve the efficiency of wheel loaders in construction, addressing labour shortages in the industry.

In his dissertation, Automatic Bucket Filling: A Machine Learning Approach, Eriksson investigates how AI can automate the challenging task of loading materials. He developed AI models based on real-world data from expert operators, enabling wheel loaders to perform with human-level precision. His work also explores methods for adapting AI to handle different types of materials, offering solutions for increasing productivity on construction sites.

The public defence will take place at 12:00 in the Tietotalo building, Hervanta campus, Tampere University (Auditorium TB109). The public defence can be followed via remote connection. 

New MORE publication published in Robotics and Autonomous Systems

A new MORE publication has just been published titled “An exploratory study of software engineering in heavy-duty mobile machine automation” in Robotics and Autonomous Systems. The article is fully open access and can be read online: https://www.sciencedirect.com/science/article/pii/S0921889023000635?via%3Dihub#d1e2742

Abstract

As the amount and complexity of software for automating heavy-duty mobile machinery is increasing, software engineering in this domain is becoming more important. To characterize the industry’s current state of software engineering and its issues to guide future research, we performed an empirical exploratory study. We interviewed 16 software engineering professionals from 13 different companies conducting business in heavy-duty mobile machines and their automation. The interviews were analyzed qualitatively, and quantification of the analysis results is presented. We first create an overview of software engineering in the heavy-duty mobile machinery industry. We then identify problem areas affecting software development and discuss some of the possible solutions found in literature. Our findings indicate that the major problem areas faced in the industry that require more research are its digital transformation, autonomous machine functional safety, low availability of workforce for developing software for robotic mobile machines and the lack of established software standards.