Unit 4004 Managing a Professional Engineering Project Assignment Brief 2026-27: Artificial Intelligence Theme | Pearson BTEC HNC

Unit 4004 Managing a Professional Engineering Project Assignment Brief (2026-27 AI Theme)

This Unit 4004 brief asks HNC engineering students to choose, plan, run and present a real engineering project for their employer. For the 2026-27 academic year the Pearson-set theme is Artificial Intelligence, so the project must show how AI or data-driven methods solve an engineering or manufacturing problem while staying ethical, safe and accountable.

Submission Format

• An industry-standard technical project report (maximum 5,000 words)
• Observation of activities with questioning
• An outcomes presentation (15 minutes) to an audience, followed by questions (15 minutes)
• A professional discussion supported by a digital portfolio containing a project proposal (500 words), a project management plan with a Gantt chart (500 words), a project logbook (500-1,000 words), an interim technical report with background research, analysis, design and prototypes (2,000 words), feedback and action plan (500 words), a performance evaluation (500 words) and a personal reflection and development plan (500 words)

Unit Learning Outcomes

• LO1 Select a project that will provide a solution to an identified engineering/manufacturing problem
• LO2 Conduct planned project activities to generate outcomes which provide a solution to the identified engineering problem
• LO3 Produce a project report analysing the outcomes of each of the project processes and stages
• LO4 Present the project report drawing conclusions on the outcomes of the project

Vocational Scenario

You work as an engineering technician for Innovate Engineering Ltd (a fictional company; select an appropriate company to meet local needs), which has sponsored you to study an HNC. Your manager has asked you to formulate and plan an engineering project that recommends solutions to enhance company processes in line with a set theme, conduct the planned activities, produce a digital portfolio and a professional technical report, take part in observed activities and professional discussions, and present the outcomes to an audience. The set theme must match the Pearson-set theme, which for 2026-27 is Artificial Intelligence.

Phase 1: Project Proposal and Project Management Plan

• Give reasons for selecting the project topic and its suitability as an engineering project for the set theme.
• Undertake a feasibility study using methods such as SWOT, PESTLE, a Pugh matrix, stakeholder matrices, risk mapping or radar charts.
• Create a project plan defining how the project will be planned, executed and monitored.
• Illustrate the effect of relevant legislation and ethics on the plan (for example the Engineering Council and Royal Academy of Engineering Statement of Ethical Principles, UK-SPEC, the NSPE Code of Ethics, and international agreements such as the Washington, Dublin and Sydney Accords).

Phase 2: Project Implementation

• Review and finalise a project delivery and time management plan using a Gantt chart or similar.
• Keep a weekly project logbook showing how progress is monitored against milestones and timescales.
• Critically evaluate the project plan and recommend improvements with reference to outcomes, ethics, health and safety and professional standards (UK-SPEC, Statement of Ethical Principles, NSPE Code of Ethics).

Phase 3: Industry-Standard Technical Project Report

• All relevant information gathered in Phases 1 and 2
• Logical presentation of the findings and techniques used
• Critical analysis and evaluation of the project from initiation to completion, with recommendations for further development

Phase 4: Project Outcomes Presentation

Deliver a 15-minute presentation covering the project aims and objectives, key stages and outcomes, conclusions, recommendations for further work, lessons learned, analysis of your own behaviours and research quality, reflections on efficient performance, and a CPD plan (for example digital competences and sustainability). Complete the performance review checklist and add audience feedback and self-evaluation as an addendum to the report.

Pearson-Set Theme 2026-27: Artificial Intelligence

Pearson describes AI in engineering and manufacturing as the integration of machine learning and data-driven algorithms into the design, production and lifecycle management of complex systems. Projects should show AI literacy as a professional competency, including model transparency, validation of data and human-in-the-loop oversight to manage risks such as algorithmic bias, data security breaches and unsafe autonomous behaviour.

Learning Outcomes and Assessment Criteria

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