Titled An Innovative Methodology for Designing Efficient Assembly Lines in Industry 5.0, this study focuses on enhancing the design and reconfiguration of assembly lines for large-scale products—such as automobiles and commercial vehicles. The research addresses critical challenges including layout planning, operator allocation, and task sequencing within modern manufacturing environments.​

Industry 5.0 emphasises human-centric manufacturing, promoting collaboration between human operators and advanced technologies like robots and collaborative robots (cobots). While automation offers significant potential, many businesses encounter obstacles such as high implementation costs, complex configurations, and inflexible systems. This research aims to develop a flexible and sustainable methodology that integrates human skills with automation, enhancing adaptability to evolving production demands.​

The University of Bedfordshire is seeking volunteer companies from the Automotive, Commercial Vehicles, Machinery, Construction Equipment, and Industrial Robotics sectors to support this academic research. Participation involves no financial cost; companies are simply asked to share specific, non-confidential data regarding one of their existing assembly lines. In return, participants will receive a comprehensive report of the study’s findings, providing early insights into innovative strategies for optimising assembly line performance in the Industry 5.0 era.​

What kind of information is required to support this study?

The information on the assembly line of one of your products, includes:

1. Product Specifications:

• CAD file of the product.
• Assembly sheet detailing the assembly process.
• Bill of Materials (BoM) listing all components required for assembly.

2. Assembly Task Specifications:

• Detailed specifications of each task performed on the assembly line, can be extracted from the Operation Process Chart (OPC).

3. Assembly Line Layout and Specifications:

• The complete layout of the assembly line.
• Line specifications, including:

➢ Number of operators assigned to each workstation.

➢ Types of robots used (if applicable), including industrial robots and collaborative robots (cobots).

If your company is interested in contributing to this university-led initiative at the forefront of Industry 5.0 research—and benefiting from early access to the study’s outcomes—we would be delighted to hear from you.​

For more information or to express interest in supporting this project, please contact Azadeh.Esfandyari@beds.ac.uk