A full suite of reliability engineering and AI development services for mining, resources, and heavy industrial operations. 15+ years of field expertise, now augmented by intelligent systems.
Every engagement is grounded in engineering rigour — not generic advice. Each service is backed by real methodology, real tools, and real field experience.
Rigorous Reliability Centred Maintenance analysis using John Moubray's RCM2 methodology. Every failure mode is analysed function-first, with consequence categorisation preceding task selection — the only defensible order per RCM2 decision logic. Now AI-accelerated: what previously took 3–5 engineering days is delivered in hours, with the human effort focused on validation and facilitation rather than document generation.
Designing and implementing condition-based maintenance programmes that detect failures before they occur. From condition monitoring strategy design through to technology selection, data interpretation, and integration with your existing SAP or Maximo maintenance plans. Covers vibration analysis, oil analysis, thermography, ultrasound, and motor current signature analysis.
Customising, deploying, and training maintenance teams on SAP Plant Maintenance and IBM Maximo. Covers functional location hierarchy design aligned to your physical asset structure, equipment master data, maintenance plan configuration, work order workflows, and KPI dashboard setup. Ensures your CMMS reflects your actual maintenance strategy — not the default configuration.
Building intelligent maintenance agents that encode reliability engineering methodology as AI reasoning logic. The RCM2 FMEA Agent applies Moubray's decision diagram autonomously — consequence-first, task-selection second — and produces formatted, auditable outputs. Custom agents can be built for your specific assets, your SAP data structures, and your process environment.
Developing digital representations of physical assets to simulate performance, optimise maintenance planning, and support real-time decision-making. Integrates with condition monitoring data, process historian data, and maintenance records to create a living model of your equipment — one that updates as your plant operates.
Upskilling maintenance teams in reliability engineering methodology, CMMS systems, and data-driven maintenance practices. Training is practical and field-relevant — not classroom theory. Covers RCM2 methodology, FMEA facilitation, SAP PM and Maximo user training, condition monitoring interpretation, and reliability KPI management.
Traditional FMEA is time-consuming, expensive, and often incomplete because of the sheer effort involved. The result is that most organisations do one FMEA at commissioning, file it, and never update it. The document decays while the plant changes.
The RCM2 FMEA Agent changes this equation. Generation takes minutes. The human engineering effort shifts from writing to validation — which is where expert judgment actually adds value. And because the FMEA can be regenerated quickly, it stays current.
Every engagement follows a structured process that ensures the output is rigorous, site-specific, and actionable.
Understanding your asset base, maintenance challenges, CMMS environment, and specific objectives. Scoping the engagement and agreeing deliverables.
RCM2 analysis, condition assessment, data review, or CMMS audit — depending on the service. AI-assisted generation where applicable, validated by engineering judgment.
Facilitated review with your operators and maintainers. The people who run the equipment validate the analysis. Site-specific knowledge is captured and incorporated.
Delivering final outputs — FMEA workbooks, SAP PM plans, Work Instructions, agent deployments — and supporting your team to implement and sustain the improvements.
Tell me about your maintenance challenge. Whether it is a specific analysis, a system implementation, or a long-term reliability programme — let us talk about what is possible.