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Final Course Assignment
Brand
Brand

University of Cambridge

HCI (Human Computer Interaction) for AI Systems Design

AI-assisted Error Monitoring & Detection for Industrial Production Machinery

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Participation

Individual work

University Staff

Prof. Per Ola Kristensson
Alva Markelius
Elizabeth Barsotti

Duration

8 weeks (Part-time)

Year

Oct – Dec 2025

Tools

Figma
Miro
Microsoft Excel
Tableau
Apple Keynote

Project Overview

Real-world scenario

Design of an AI-assisted real-time error and fault monitoring and detection system for industrial production machinery within a factory, to:

  • minimise production downtime
  • monitor machine metrics
  • identfiy breaches of operating tolerance levels
  • identify errors and faults
  • idenitfy and recommend suitable replacement machines and skilled workers
  • allow human supervisors to dismiss or snooze system notifications and manually override AI recommendations
  • enable human-in-the-loop interactions, — such as dismissing, snoozing, and manual overrides (with rationale capture) — to create feedback loops that continuously informs and improves system behaviour.

Tasks

  • Derive a solution-neutral problem statement that motivates a human-AI system and arrive at a requirements specification that can be used to test the system
  • Design a function model of a human-AI system and analyse the types and levels of automation that can be used to address the solution-neutral problem statement
  • Perform a risk analysis and determine the types of risks are inherent in the human-AI system and propose mitigation activities
  • Create a verification cross-reference matrix that can be used to verify that system requirements have been met for all deployment contexts relevant to the human-AI system
  • Develop a strategy for managing the risks and governance issues of a human-AI system
  • Create a validation strategy to ensure the human-AI system is fit for purpose and addresses the overall function it is intended to perform.
Breakdown

Course scoring

Task Discussions

100%

Participation

95%

Final Project

86.7%

Final Course Grade

94%

Pass

Final Project

Submitted assignment

A 'contact sheet' gallery view of my submitted work.

Note: The image quality has been intentionally reduced to avoid sharing specific details of my submitted assignment and to prevent plagiarism.

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