Paul Tu

Professor Yiliu (Paul) Tu

PhD

Positions

Professor

Schulich School of Engineering, Department of Mechanical and Manufacturing Engineering

Contact information

Phone number

Office: +1 (403) 220-4142

For media enquiries, contact

Joe McFarland
Media Relations and Communications Specialist

Cell: +1.403.671.2710
Email: Joe.Mcfarland@ucalgary.ca

Background

Credentials

P.Eng., Association of Professional Engineers and Geoscientists of Alberta (APEGA), 2005

Educational Background

BSc Electrical Engineering, Huazhong University of Science and Technology, 1982

MSc Mechanical Engineering , Huazhong University of Science and Technology, 1985

PhD Production Engineering, Aalborg University, 1993

Biography

Dr. Tu is a professor at Department of Mechanical and Manufacturing Engineering, University of Calgary, Canada. Before he joined University of Calgary, he was a lecturer at the Department of Mechanical Engineering (1) of Huazhong University of Science and Technology (HUST), post-doctoral research fellow at Aalborg University (AU), Denmark, assistant professor at the Department of Manufacturing Engineering and Engineering Management, City University of Hong Kong, a lecturer and senior lecturer at the Department of Mechanical Engineering, University of Canterbury, New Zealand. His present research interests are OKP (One-of-a-Kind Production) system modeling and optimization, ultra-fast laser micro/nano-machining, lifecycle quality control and assurance for complex products, data-driving computation and engineering optimization. He has published more than 200 research papers and 6 books. He is a senior member of SME (Society of Manufacture Engineers) and a professional engineer (P.Eng.) of APEGA (The Association of Professional Engineers and Geologists of Alberta)

Research

Areas of Research

Advanced manufacturing

One-of-a-kind production (OKP)

Micro Machining Technology

Supply Chain Integration

Manufacturing Systems

Data Analysis and Optimization

Quality Engineering

Statistic Economics

Artificial Intelligence

Data analysis and optimization

Micro machining technology

Intelligent machining technology in high precision machining, such as micro-machining technology

System engineering and design

Quality control methods for complex product production

Engineering optimization

Operations research and supply chain integration

 

Courses

Course number Course title Semester
 ENMF 514 Integrated Manufacturing Systems Fall
 ENMF 527 Project Engineering Winter
 ENME 624 Fundamentals of Pipeline Economics Fall and Winter
 ENMF 618 Manufacturing Optimization Winter

Projects

Data Driven One-of-a-Kind Production

One-of-a-Kind Production (OKP) aims at cost-effectively producing customized products through vertical connectivity from cloud to shop floors and horizontal connectivity from suppliers to customers as well as advanced manufacturing technology. The OKP paradigm and its methodology are particularly applicable to manufacturing businesses in developed countries such as Canada: these companies are often small- and medium-sized enterprises (SMEs) that produce customized products in very small (or single) batch sizes. Improvement of production efficiency, reduction of costs and increase in advanced manufacturing capability are critical for these SMEs to compete with large manufacturing companies (often conglomerates) overseas.  

 

My research group has been making significant contributions to the long-term goal of advancing OKP methodology and theory as well as the training of highly qualified personnel (HQP) as academia or entrepreneurs in advanced manufacturing (AM) to help Canadian manufacturing companies, particularly SMEs, improve their production efficiency, customer satisfaction and manufacturing technology level, and reduce costs and lead times. The proposed research over the next five years aims at continuing this goal through achieving the following research objectives: (1) Develop dilemma decision problem modelling method in OKP supply chain optimization; (2) Innovate novel work package planning and digital quality management in OKP project(s). (3) Develop a machine learning method in blockchain-based digital OKP platform. (4) Develop cloud quality monitoring and control technology for 3D printers. The development of methods, models, technology and theory through the research will place its emphasis on human centric, resilience and sustainability which are promoted by Industry Version 5.0. 

 

The proposed research program will generate novel methods, models, technology and theory in OKP through achieving these four objectives. Since the majority of Canadian manufacturing companies are SMEs or OKP companies, this program will widely benefit the Canadian manufacturing business sector and contribute to the economy of Canada. Moreover, HQPs will be trained in the multidisciplinary area of manufacturing systems and technology, engineering optimization, data analytics and machine learning, computer simulation and modeling, and management science through collaborations with industries and universities inside and outside of Canada. The training of HQP is critical in the AM industry because its growth is hampered by labour shortages, and women are particularly underrepresented in this industry. Canada's Economic Strategy Table for Advanced Manufacturing notes that increasing the number of women in AM is a target. Our team has been and will continue actively involving women in HQP training in advanced manufacturing.   

Awards

  • SCHULICH School of Engineering Teaching Achievement Award, University of Calgary. 2020
  • Mechanical and Manufacturing Engineering Research Excellence Award, SCHULICH School of Engineering, University of Calgary. 2007
  • CFI New Opportunity Fund Award, Canada Foundation for Innovation (CFI). 2003
  • SCHULICH School of Engineering Teaching Achievement Award, SCHULICH School of Engineering, University of Calgary. 2018

Publications