Advancing Human-Machine Interfaces in Circular Manufacturing

Written By Core Innovation

By UNIMORE (Università degli Studi di Modena e Reggio Emilia)

The latest advancements in the DaCapo Project involve the development of Human-Machine Interfaces (HMI) and User Experience (UX) solutions by UNIMORE (University of Modena and Reggio Emilia), aimed at enhancing industrial processes in circular manufacturing. A significant milestone has been achieved with the delivery of the alpha version of the HMIs, designed to optimise interaction between operators and digital tools, improving efficiency and decision-making.

The Approach

The methodology adopted is based on a human-centered design philosophy, ensuring that interfaces are tailored to real operational needs. The focus remains on creating adaptive, proactive interfaces that integrate Augmented Reality (AR) and Artificial Intelligence (AI)-driven insights. These tools are designed to guide operators through inspection and maintenance processes, facilitating informed decision-making while reducing operational errors.

The Interface Concept

The newly developed HMI solutions feature a tablet-based XR (Extended Reality) system, structured around:

• Step-by-step guidance – Ensuring operators follow optimal workflows with interactive, intuitive digital support.

• AR overlays – Highlighting key areas for inspection and analysis, improving accuracy in defect detection.

• Real-time AI support – Providing contextual recommendations and instant feedback based on machine learning algorithms.

• Impact Analysis Panels – Assisting operators in evaluating different actions based on ESG (enviromental, social and governance) parameters, ensuring data-driven decision-making.

Industry Use Cases

These developments have been applied to two use cases in industrial scenarios.

GKN Aerospace

An XR-based inspection system has been developed for blade assessment, integrating defect recognition tool and real-time AR guidance to support operators in efficiently identifying and addressing manufacturing issues. The interface is designed to assist with:

  • Defect Recognition: Automated scanning and identification of blade imperfections, with visual zones displayed in AR.

  • Inspection Workflow: A structured, interactive workflow to ensure all critical steps are followed correctly.

  • Measurement and Evaluation: Real-time measurements are provided to ensure defects fall within acceptable tolerance levels.

  • Decision Support System: AI-driven insights recommend corrective actions, minimising waste and maximising efficiency.

XR Inspection Tool during the Defect Recognition Step for GKN Use Case

Pesmel

The HMI solutions for warehouse maintenance include alarm prioritisation tools, AI-assisted root cause analysis, and decision-support systems (DSS) to ensure rapid and effective responses to machine failures. The interface includes:

  • Alarm Dashboard: A centralised, list of alarms ranked by severity, ensuring the most critical issues are addressed first.

  • Root Cause Analysis: Analyses historical data to suggest the most probable causes of failures, reducing troubleshooting time.

  • Maintenance Support: Maintenance operators utilise AR-guided overlays to locate faulty components and visualize corrective actions.

  • Impact Analysis: Evaluation of different repair strategies based on cost, downtime, and environmental impact, aiding strategic decision-making.

XR Inspection Tool during Warehouse Inspection for PESMEL Use Case

Next Steps

Efforts are now directed toward refining these interfaces further, integrating real-world operational data, and enhancing user feedback loops. The objective is to ensure that HMIs remain intuitive, user-friendly, and highly effective in optimising industrial workflows while promoting sustainability.

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