DMAIC, VSM, kaizen, SIPOC, fishbone, Pareto, control charts. We benchmark your Lean Six Sigma maturity, then engineer AI capabilities into every DMAIC phase — accelerating root-cause analysis, automating measurement, and bringing rigorous statistical control to processes once thought too variable to control.
Lean Six Sigma is the proven discipline of process improvement — but its traditional cycle time is slow. A typical DMAIC project takes 4-6 months. Measurement is manual. Root-cause analysis is workshop-driven. The Pentaaxis Lean Six Sigma practice retains the methodology’s rigour while compressing every phase with AI: automated measurement, ML-driven RCA, simulation-validated improvement, and continuous AI-monitored control.
Our advisors are certified Black Belts who have led full Six Sigma deployments. Our solution engineers build the analytics, simulation, and AI tooling that accelerates each phase. The result is faster projects, more projects in flight, and improvements that stick because the AI control plane keeps watching after the team moves on.
A working catalogue of the systems, models, and platforms our engineers ship within this practice — selected for industrial reliability, observability, and scale.
Generative-AI assisted SIPOC, project charters, voice-of-customer analysis, and CTQ tree generation from operational data.
IoT, vision, and ML-driven measurement systems analysis (MSA) replace clipboard data collection — accurate, real-time process data.
Causal ML, automated hypothesis testing, multivariate analysis, and graph-based RCA on the entire process — surfacing the vital few.
Digital-twin simulation and AI-driven design-of-experiments to test improvements virtually before real-world pilots.
Continuous multivariate SPC with change-point detection — improvements stay improvements long after the project closes.
Auto-generated value-stream maps from MES and ERP data — quantitative current-state and future-state in days, not weeks.
Representative deployments across our industrial client base. Each grounded in production engineering — not concept slides.
Generative-AI scans operational data and surfaces ranked Six Sigma project candidates with draft charters, problem statements, and SIPOC diagrams.
Replace manual gauge-R&R studies with AI-vision and IoT-based measurement systems analysis — accurate, repeatable, on every part.
Apply causal-discovery and graph-based RCA to thousands of process parameters — find the actual drivers of variation, not just correlated symptoms.
Simulate proposed process improvements in a calibrated digital twin before committing to real-world trials — faster, cheaper, safer DoE.
Replace univariate control charts with AI multivariate monitoring — detects subtle drift across hundreds of parameters before it becomes an excursion.
Pull MES, ERP, and labour data into automatically-generated current-state VSMs with cycle, process, and lead-time data — quantitatively, not anecdotally.
Rank kaizen opportunities across the plant by quantified return potential — focus events on the next 20 highest-return targets.
Generative-AI training assistant that personalizes Lean Six Sigma curriculum to learner role, industry, and project — accelerating practitioner pipeline development.
Tools, frameworks, and platforms our engineers use day-to-day in this practice.
Every Pentaaxis engagement starts with a structured benchmarking conversation — no obligation, a senior engineer in the room, and a calibrated view of where AI moves the needle for your organization.