Resources
Engineering articles, guides and posts on closed-loop control in refining, chemicals and polymers, cement, and mining and minerals.
This library is written for process and control engineers in refining, chemicals and polymers, cement, and mining and minerals.
Most articles take one unit and the decisions that run it. They cover how the process works, which variables and constraints set the limit, and where margin, energy or quality is lost between the plan and the plant. They then look at what changes when a learning process model and closed-loop control run on top of the existing APC and DCS, inside limits set by plant engineers.
The posts cover the technology behind Deep Learning Process Control® (DLPC®), market updates, opinion pieces, events and a customer case study. Press coverage and awards are on News and awards.
To see where your plant sits today on the path from reactive operation to autonomous control, talk to us.
Featured
Oxbow runs petroleum coke calcining in closed loop
Oxbow runs its rotary kiln operations for petroleum coke calcining in closed loop with Imubit, raising yield and cutting natural gas use within specification.
Process modeling and the gap between planning targets and the plant
Why LP, APC and simulator models drift from the plant, how modeling approaches differ in upkeep, and how continuously learning models narrow the gap.
Answers to common questions about closed-loop AI control
Answers to the questions refining engineers ask most about DLPC®, from architecture and data flow to inferentials, retraining and operator trust.
By role
Lead the plant and the business
Operations manager
Every unit runs for itself. The plant sits a little below plan, and nobody sees it.
Plant manager
Safety, reliability, margin and people all feel the gap between plan and plant, and the people who know the unit best are retiring.
VP operations
Many sites, each optimized one unit at a time, and never enough experts.
Economics and commercial lead
Margin slips between plan and plant every shift, and it never shows up as a line item.
Digital and OT leader
Pilots, point tools, and AI nobody can certify for a running unit.
Plan and improve
Planner and scheduler
You already conduct the plant, with a linear model of a nonlinear plant and a phone call to every unit.
Energy and sustainability lead
Energy and emissions trade off by the hour, and compliance comes after the fact.
Early-career engineer
You inherit a unit, and the strategy lives in binders and senior operators' heads.
Run the plant
Shift supervisor and panel operator
You decide how hard to run from inputs that arrived hours ago.
Process engineer
"What happens if we push?" gets answered with a step test or a guess.
Process control engineer
Your control layer pads every constraint, and you won't sign for a black box.
Reliability and maintenance manager
Duty gets cut to be safe, fouling accelerates anyway, and the outage comes early.
Latest posts
All posts
Process safety management in daily plant operations
Why PSM programs drift between audits, how cross-functional gaps line up in CSB findings, and how a shared operating view helps close them.
Process safety management and the role of industrial AI
How OSHA's 14 PSM elements depend on each other, where programs break down in a changing plant, and where AI helps with hazard detection, alarms and knowledge.
Imubit named a Leader in the ARC MarketMap 2026 for Autonomous Execution Agents
ARC Advisory Group positions Imubit as a Leader in the ARC MarketMap 2026: Autonomous Execution Agents, Continuous Process Edition, its study of AI that executes decisions in the plant rather than only recommending them.
How closed-loop optimization supports chemical process safety
How steadier control, earlier sight of drift and a recorded trail of moves support process safety in chemical plants, alongside the existing safeguards.
How Imubit differs from APC, and works with it
APC holds each unit to its targets within its limits. Imubit learns cause and effect across units and makes the key decisions on top of APC, inside limits set by plant engineers.
Causality and correlation in process control
Correlation is enough to predict. Acting on a running unit needs cause and effect. What the difference means for AI in process control.
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