Enabling Deployment of an AI-Enabled Nuclear Waste Sorting System 

Context 

An SME specialising in advanced robotic engineering developed an AI-enabled system for autonomous nuclear waste sorting and segregation

The platform used machine vision and machine learning to identify, characterise, and sort heterogeneous waste streams. Unlike conventional approaches, the system combined: 

  • Autonomous identification and handling of waste items  

  • Multi-sensor analysis including radiation detection, LiDAR, and high-definition imaging  

  • Algorithm-driven optimisation of waste segregation and packing  

  • Formal mathematical verification to guarantee system behaviour and eliminate uncertainty  

The system was designed to significantly improve safety and efficiency by removing operators from hazardous environments and enabling continuous, high-accuracy operation. 

The technology had reached prototype stage and was ready for deployment testing within a live nuclear environment at Sellafield Limited. 

Problem 

Despite the strength and sophistication of the technology, the company faced the same fundamental barrier: nuclear acceptance

The system introduced a combination of emerging technologies—including artificial intelligence, autonomous robotics, and formal methods—which are not easily accommodated within traditional nuclear assurance frameworks

To be deployed, the system needed to demonstrate: 

  • Compliance with established safety and engineering standards  

  • Justification as Best Available Technology  

  • Deterministic and auditable behaviour in a safety-critical environment  

Sellafield required a rigorous, standards-based approach aligned with recognised frameworks such as Safety Case, CE Marking, ISO 12100 Design Risk Assessment, supported by comprehensive, audit-ready documentation and structured assurance processes. 

For the SME, this created significant challenges: 

  • Limited experience with nuclear-grade quality assurance and compliance  

  • Difficulty translating advanced AI concepts into deterministic, auditable evidence  

  • Lack of systems to support full traceability, validation, and regulatory engagement  

This created substantial risk: 

  • The technology could not be deployed despite being technically advanced  

  • Failure to meet assurance expectations could result in delay, rework, or rejection  

  • The company risked failing to enter the nuclear market entirely  

Without a structured approach, the innovation—despite its potential—would remain unusable in a regulated nuclear environment

Approach 

Moongate Consultancy was engaged to enable the transition from innovative concept to nuclear-ready solution. 

The engagement began with a detailed contract and requirements review, followed by a structured gap analysis of the company’s technical, quality, and organisational capability. 

A comprehensive compliance framework was implemented, integrating nuclear requirements into a fully aligned Quality, Health, Safety and Environmental (QHSE) management system

Delivery was managed using structured change control aligned with the Association for Project Management framework, ensuring a controlled and auditable path to deployment readiness. 

Key elements included: 

  • Development of technical and safety justification aligned with ISO 12100  

  • Creation of audit-ready documentation compliant with ISO 9001:2015  

  • Structuring evidence to support nuclear expectations for deterministic system behaviour, including alignment with formal methods assurance  

  • Alignment with Sellafield Limited supplier qualification and audit processes  

A critical element of the work was translating complex AI and autonomous system behaviour into forms that could be understood, justified, and accepted within a nuclear regulatory context

This required: 

  • Bridging the gap between advanced technology and traditional nuclear assurance expectations  

  • Embedding traceability, validation, and verification into system development  

  • Supporting organisational change across leadership, engineering teams, and suppliers  

  • Establishing compliant working practices and governance structures  

Moongate Consultancy also acted as the interface between the SME and the nuclear client, leading communications, structuring submissions, and ensuring alignment with expectations at every stage. 

 

Result 

The system was successfully progressed to deployment readiness within a regulated nuclear environment at Sellafield Limited. 

A structured, standards-based approach ensured that: 

  • The system’s behaviour could be demonstrated, justified, and assured in line with nuclear expectations  

  • All technical, quality, and organisational documentation was complete, auditable, and compliant  

  • The technology aligned with requirements for safety, assurance, and Best Available Technology  

All required assurance activities were completed, enabling the system to progress through the necessary stages of review and acceptance. 

Impact

This engagement enabled the company to transition from an innovative technology developer into a credible supplier of advanced solutions to the nuclear sector

As a result, the company: 

  • Achieved alignment with the requirements of Sellafield Limited for supplier engagement and deployment  

  • Established the capability to deploy AI-enabled systems within regulated nuclear environments  

  • Built the quality, assurance, and organisational systems required to operate within the nuclear supply chain  

  • Positioned itself to access future opportunities in robotics, AI, and advanced decommissioning technologies  

Crucially, this work enabled the translation of a highly complex AI-driven system into a form that could be accepted within a conservative, safety-critical industry

Without this structured approach, the technology—despite its advanced capabilities—would not have been deployed.

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