ProMentoHR

Assessing Cognitive Workload in Human-Robot Collaboration and Cooperative Assembly Systems

Collaborative robotics is a vital technology in Industry 4.0, particularly in the rapidly expanding market of collaborative assembly. This area of industrial human-robot interaction (HRI) not only focuses on mechanical safety but increasingly recognizes the importance of cognitive ergonomics and human factors, which are critical for operator safety, well-being, and performance. Addressing these aspects requires a human-centered approach to developing Collaborative Assembly Systems (CASs), highlighting the need for interdisciplinary research.

The project PromentorHR aims to enhance human factors in industrial HRI by developing and validating a new cognitive workload (CWL) assessment method, building on the Cognitive Load Assessment for Manufacturing model (CLAM) proposed by Thorvald et al. in 2017. The updated method, named “ProMentoHR,” seeks to minimize subjective biases in CAS design and specifically address how design elements affect operator CWL.

Additionally, the project will develop a practical tool based on the enhanced CLAM methodology, intended for use by assembly system experts who may not specialize in human factors. This tool will undergo experimental validation through a case study in a realistic setting, ensuring it effectively integrates cognitive requirements into human-centered CASs.

ProMentoHR aims to improve operators’ working conditions, safety, and well-being, while also enhancing production performance. The project will utilize both qualitative and quantitative methods and maintain a user-centered design approach. Feedback and recommendations will be collected through surveys and interviews with experts in manufacturing systems, robotics, and human factors. This input will inform the development of the methodology and the integration of cognitive ergonomics into CAS features and HRI patterns.

Ultimately, the project focuses on advancing theoretical understanding and practical applications of how operators’ CWL can be managed in manufacturing settings, aiming to improve worker conditions and optimize the effectiveness of collaborative robotics in industrial environments.

News Release: Delphi Study Round 2 is about to begin!

October 9, 2024

With the successful completion of the first round, we are excited to announce the start of our second ProMentoHR Delphi Study.
Our research team has engaged a diverse group of global experts in this field to critically assess and provide feedback on our newly developed methodology for evaluating the cognitive workload of assembly operators working with collaborative workstations.
The participants' expertise and insights from their respective domains were invaluable in ensuring the tool’s accuracy and relevance, ensuring its effectiveness in real-world applications.
With these revisions now in place, we are ready to initiate the second round of the Delphi Study.

We extend our gratitude to all participating experts for their time, effort, and commitment to this study. We look forward to the ongoing collaboration and further validation of our methodology.

Stay tuned for more updates as we continue this exciting journey!

The ProMentoHR Delphi Methodology

Thanks to the Delphi Study methodology, experts in the Human Factors, Human-Robot Collaboration and Industrial Engineering fields are going to contribute to the development of a new Cognitive Workload assessment tool in the context of industrial collaborative assembly systems.
The process began by crafting a comprehensive questionnaire aimed at eliciting a broad range of insights and opinions. This initial survey, which will be distributed electronically, comprises open-ended questions designed to gather diverse perspectives.
Additionally, the online format facilitates efficient data collection and allows for a geographically dispersed group of experts to participate, ensuring a rich and varied pool of knowledge.

The expert panel, selected for their extensive knowledge and experience, will be asked to provide detailed responses based on their individual expertise. The primary goal of this round is to collect a wide array of qualitative data, identifying common themes, potential challenges, and innovative ideas. This information serves as the foundation for subsequent rounds, where these insights will be analyzed and refined through iterative feedback, ultimately converging towards a consensus.
This iterative process will allow the refinement of the assessment tool based on the constructive feedback received. The ultimate goal is to achieve a high level of agreement among the experts, ensuring that the final tool is a comprehensive and reliable measure for the assessment of cognitive workload in collaborative assembly systems.