Digital Systems and AI Improvement Intern
About The Business: Foams 4 Sports manufactures sports equipment, protective padding and specialist foam products. The business has successfully digitised the cut files used to produce PVC covers; however, much of the manufacturing knowledge relating to foam cutting, product assembly and production best practice remains undocumented or held within employee experience and paper-based records.
Overview: The internship will focus on transforming existing manufacturing knowledge into structured digital assets, developing standardised manufacturing specifications, creating supporting CAD documentation and establishing a scalable framework that supports future automation and AI-enabled process improvement.
Desirable Skills: Intern Skills Required - Essential • Engineering, manufacturing, product design or related discipline. • Strong analytical and organisational skills. • Excellent attention to detail. • Ability to communicate effectively with shop-floor and management personnel. • Ability to document technical processes clearly and accurately. • Basic CAD experience. • Competent use of Microsoft Office applications. Intern Skills Required - Desirable • Knowledge of manufacturing environments. • Experience of ERP or business systems. • Understanding of data management and document control principles. • Familiarity with digital manufacturing concepts. • Interest in AI and emerging manufacturing technologies. Expected Outcomes and Success Metrics - Business Outcomes • Reduced reliance on undocumented manufacturing knowledge. • Improved consistency of production processes and work instructions. • Enhanced knowledge retention and business resilience. • Creation of structured manufacturing data suitable for ERP integration. • Improved accessibility of manufacturing information. • Foundation established for future manufacturing automation and AI initiatives. Success Metrics • Minimum of 20 manufacturing specifications completed and approved. • Number of CAD drawings created or updated. • Percentage of priority products documented. • Central digital repository established and operational. • Successful pilot storage and retrieval of manufacturing specifications within Odoo. • Number of staff trained in specification maintenance and management. • Positive management and production team feedback on usability. • Delivery of an AI readiness and recommendations report. Timeline with Milestones Hours Activities Hours 1-50 Company induction and health and safety training; manufacturing process observations; stakeholder interviews; collection and review of existing documentation; selection of priority product ranges. Hours 51-125 Manufacturing knowledge capture; manufacturing data analysis; development of specification templates; definition of document management structure; initial CAD review. Hours 126-200 Creation of manufacturing specifications; CAD drawing development and refinement; production team reviews and validation; establishment of digital repository. Hours 201-250 Odoo structure review and pilot testing; manufacturing data organisation; upload and accessibility testing; staff feedback and refinement. Hours 251-300 AI readiness and feasibility assessment; recommendations report; staff training sessions; final presentation and project handover.
Job Description:
Project Goals and Objectives - SMART
• Capture and digitise manufacturing knowledge for priority foam product ranges within the 12-week internship programme.
• Develop a standardised manufacturing specification template and complete a minimum of 20 digital manufacturing specifications containing material information, cutting sequences, tolerances, quality requirements and visual work instructions by project completion.
• Create or update CAD-based manufacturing drawings for documented products and link these to manufacturing specifications within a structured digital filing system.
• Design and implement a central digital manufacturing repository with defined version control and document management processes to support future business use.
• Develop a manufacturing data structure suitable for use within Odoo and test the storage and retrieval of manufacturing specifications for at least one pilot product range.
• Assess the data requirements, opportunities and challenges associated with future AI-assisted specification generation and produce a recommendations report for management.
• Train nominated employees on maintaining, updating and managing manufacturing specifications following project completion.
Scope of Work, Methods, and Tools
Manufacturing Knowledge Capture
• Interview production operators, supervisors and management staff.
• Observe manufacturing activities and foam cutting processes.
• Review existing documentation, sketches, production notes and manufacturing records.
• Capture undocumented manufacturing knowledge and best practice.
• Identify variations in production methods and opportunities for standardisation.
Manufacturing Data and Specification Development
• Design a standard manufacturing specification template.
• Define required manufacturing data fields and document structures.
• Create digital manufacturing specifications for priority products.
• Document materials, dimensions, cutting methods, tolerances and quality requirements.
• Produce visual work instructions to support production consistency.
• Establish document naming, version control and review processes.
CAD and Digital Manufacturing Documentation
• Create or update CAD drawings illustrating cutting layouts and manufacturing methods.
• Review material utilisation and identify opportunities to improve yield.
• Link CAD documentation to manufacturing specifications.
• Develop a consistent digital structure for storing engineering documentation.
Odoo Data and Systems Integration
• Review current Odoo manufacturing and document management capabilities.
• Define how manufacturing specifications can be structured within Odoo.
• Organise manufacturing data to support future ERP integration.
• Test the upload, access and management of sample specifications.
• Document recommendations for future deployment across additional product ranges.
Future AI Enablement Assessment
• Assess how structured manufacturing data could support future AI applications.
• Map information flows required for automated specification generation.
• Identify data quality and standardisation requirements.
• Develop a future-state process map demonstrating how AI-assisted specification creation could operate.
• Present findings and recommendations to management.
Upskilling and Knowledge Transfer
• Work with nominated employees throughout the project so they understand the new manufacturing specification structure, digital repository and document-control approach.
• Develop clear guidance and user-friendly training materials for maintaining, updating and managing manufacturing specifications after the internship.
• Deliver practical handover and training sessions to nominated employees, incorporating feedback to support confident ongoing use of the new digital processes.
Intern Roles and Responsibilities
• Gather and analyse manufacturing knowledge from employees.
• Create and maintain digital manufacturing specifications.
• Produce CAD-based manufacturing documentation.
• Organise manufacturing information within a structured digital repository.
• Support manufacturing data preparation for ERP integration.
• Identify opportunities for process standardisation and improved consistency.
• Assess future AI-enabled opportunities for manufacturing documentation.
• Develop supporting guidance and training materials, and deliver knowledge-transfer sessions to nominated employees so they can maintain and update the digital manufacturing information after project completion.
• Present project findings and recommendations to management.