About Variana
Monte Carlo Simulations
Build and run models that predict variability and outcomes with ease.
Quality Metrics
Track readiness (people, machines, time), Cp/Cpk, scrap, and rework in one clear dashboard.
Simple Data Input
Operators provide answers through short daily prompts; managers tune targets and constraints.
Actionable Insights
Recommendations turn into change projects with clear scope, owners, and due dates.
How It Works
Map Your Process
Define inputs/outputs and key risks using a simple SIPOC-like view.
Capture Readiness
Small, daily inputs update readiness and risk parameters automatically.
Simulate & Compare
Run Monte Carlo scenarios and compare outcomes to current predictions.
Act & Learn
Implement recommended actions; Variana logs RUN/DELTA for continuous learning.
Modules
SIPOC
Capture Suppliers, Inputs, Process, Outputs, and Customers. Keep inputs/outputs aligned to risks and CTQs.
FMEA
Identify failure modes, causes, and effects. Quantify Risk Priority Numbers and link actions directly to owners.
RUN Log
Every implemented action becomes a RUN entry with timestamp, owner, and impact, closing the learning loop.
DELTA
Track the delta between predicted and observed outcomes. Improve models and recommendations over time.
Process Radar
Visualize readiness across people, machines, methods, and time to spot weak signals early.
Benefits
Les mistakes and Rewards
Catch risks earlier, act before defects propagate.
Faster Decisions
Managers compare scenarios with deltas, not opinions.
Engaged Operators
Micro-questions reduce paperwork and increase signal quality.
Repeatable Improvements
Every accepted change becomes a project card with clear ownership.
User Stories
Step 1 — Answer the daily micro-question
At the start of the shift, the system asks one simple context question (e.g., “Any unusual noise or vibration on press #3?”). The operator replies in a few words or by tapping a quick selector.
Step 2 — System updates the process/risk parameter
The response is interpreted automatically and used to adjust the parameter describing the step or risk in the process.
Step 3 — Propagate changes and prepare simulation
The system cascades the updates across SIPOC I/O and prepares a Monte Carlo run.
Step 4 — Get the best preventive action
The system suggests the most effective preventive action to avoid simulated bad outcomes.
Step 5 — Confirm implementation time
The operator confirms when the suggested change was (or will be) implemented.
Step 1 — Review current system recommendations
The manager reviews the newest recommendations and flags produced by the system.
Step 2 — Adjust parameters
Targets, constraints, or process parameters are modified for new clients or goals.
Step 3 — Options reframed in process & risk terms
The system paraphrases proposed options using the language of process and risk.
Step 4 — Run scenarios and compare outcomes
Monte Carlo analyses show deltas vs current forecasts.
Step 5 — Approve or reject; generate project card
On acceptance, a Process Change Project card is generated with scope, owner, and due dates.
Contact
Tell us about your process and quality goals. We’ll propose a short pilot to show measurable impact.