Active Economics & Business Engineering

University of Strathclyde and Fix Visual Effects Limited KTP 24_25 R1

In plain English

AI plain-English summary

A visual effects studio’s production pipeline is currently a patchwork of disconnected software systems, each handling a separate task—tracking shots, managing renders, logging client feedback—with no single view of the whole process. This project embeds operations management and business control technologies to link, streamline, automate, and visualise those systems. The problem is that post-production for film and television involves dozens of interdependent steps, and when they are not coordinated, delays and errors cascade through the pipeline. The gap is a lack of integrated, real-time visibility across the entire workflow. If successful, the collaboration between the University of Strathclyde and Fix Visual Effects Limited will create a unified digital control system for VFX production. This could reduce turnaround times, cut waste from redundant work, and allow studios to take on more complex projects without scaling headcount proportionally. For the film and advertising industries, that means faster delivery and lower costs. For the UK’s creative sector, it strengthens competitiveness in a global market where efficiency is a decisive advantage.

View original technical description
To embed operations management and business control technologies to link, streamline, automate and visualise the various systems required for post visual effects (VFX) production, and enhance efficiency across the end-to-end production pipeline.

View the original record at the funder ↗

Related Research

Grants with similar aims, by meaning.

Glasgow Caledonian University and CPA Engineered Solutions Limited KTP 21_22 R5
University College London and Mo-Sys Engineering KTP 21_22 R4
University of the West of Scotland and Smartify Holdings Limited KTP 24_25 R5
University of Strathclyde and Coolside Limited KTP 22_23 R4
Birmingham City University and King and Moffatt UK Limited KTP 22_23 R2

Original classification

Knowledge Transfer Partnership

Plain English summaries and category classifications on this site are generated by AI and may not perfectly reflect the original research.