Better quality and productivity, from the data you already have
Stored data doesn't improve anything on its own. The goal is better quality and higher productivity: knowing whether the process changed, whether it can hold spec, and where each lost hour went.
Where plants lose time, and what DMI does about it
✕ Investigations take days
Engineers export data from several systems and line it up by hand to explain a single deviation.
✓ Root cause in minutes
DMI correlates signals, alarms, batches, maintenance and quality records automatically and walks the process upstream to find where the change started.
✕ Tampering with stable processes
Operators react to every movement on a trend, which adds variation and creates new problems.
✓ Signal vs. noise
Built-in statistical process control separates special-cause events from common-cause variation, so teams act only when the process has actually changed.
✕ OEE without explanation
One OEE number can't tell the crew whether the loss came from downtime, slow running or off-spec product.
✓ Loss broken down by cause
DMI splits OEE into availability, performance and quality, tied to the process stage and asset, so effort goes to the biggest loss.
✕ Knowledge walks out the door
Troubleshooting expertise sits in experienced staff and in manuals that nobody can find when they need them.
✓ Knowledge on demand
DMI's assistant answers plain-language questions using live process context and cites the relevant SOP or manual passage.
✕ Inconsistent names across sites
The same signal has a different name on every line and at every site, so plants can't be compared.
✓ Unified namespace
DMI builds one reviewed, ISA-95-aligned naming structure (enterprise, site, area, cell, signal) without moving the underlying data.
✕ Cloud isn't an option
IP, regulatory, security or connectivity constraints rule out sending plant data off site.
✓ Sovereign, plant-local AI
Core analysis and the AI model run inside your facility. You decide what, if anything, goes to the cloud.
Four steps from raw data to confident action
Find what's already there
DMI discovers databases, tables, tags and metadata across your plant systems and sites. It reads structure and context only, and the data stays where it is.
One map of your operation
DMI proposes a unified namespace and your team reviews and approves it. From that, DMI identifies your process type and builds an ISA-95 process graph that shows how every stage connects to the next.
Follow the process to the cause
Control charts flag special-cause events. Root-cause analysis then walks the process graph upstream to find which signals moved first, and correlates them with production, maintenance and quality context.
Evidence-backed recommendations
Anyone on the team can ask a question in plain language. DMI answers with the evidence, the relevant documentation and recommended next steps. Alerts watch for the issue coming back, and your people stay in control of every decision.
What changes for your team
Faster investigations
Hours of manual data gathering become a guided, evidence-based analysis.
Less scrap & rework
Real process changes are caught earlier, before they turn into off-spec product.
More uptime
Maintenance and reliability teams see the patterns that lead up to trips and failures.
Knowledge that stays
Expertise from your people and documents is available to every shift.
Bring us your hardest problem
We'll show how DMI would investigate it.