Why industrial AI success starts with process stability, not prediction

From Control: Why establishing stable operations, dynamic centerlining and a trusted data foundation is the critical first step toward AI-driven quality optimization.

Len Vermillion writes:

Nearly every plant manager has heard a pitch for an artificial intelligence (AI) system that promises to predict quality metrics, catch downtime before it happens or squeeze another point of yield out of a line. However, fewer have seen those systems survive once they hit the plant floor.

The gap between the pitch and the plant is usually the result of a recommendation engine being only as useful as the operator's willingness to act on what it says. But operators don't act on advice they don't trust, and in a process environment, trust is built on stability.

When a line moves from setpoint to setpoint depending on who's running the shift, when centerlines are frozen numbers pulled from a binder nobody has updated in years, and when the data behind a recommendation is stitched together by hand, an AI model's output looks like noise. Confidence stalls, and so does adoption.

That's the case TwinThread is making to manufacturers evaluating industrial AI in 2026: don't reach for the most advanced use case first. Instead, the industrial AI and digital twin software company aims to address process variability with AI first and then bring in more advanced optimization as production stabilizes.

“Improving industrial data and scoping Industrial AI can happen in tandem,” says Brandon Ekberg, TwinThread’s VP of Product Management. “While TwinThread automates much of the data foundation work, teams can identify and validate viable use cases for Industrial AI. Once the data is integrated and the use case is vetted, pre-built solutions help customers move as quickly as they’d like.”

Read the entire article HERE.

Podcast: Reverse osmosis — when it's time to ditch the softener

From Chemical Processing: In the latest episode of the Distilled podcast, SAMCO’s Brad Buecker explains how RO can slash boiler blowdown and corrosion risk — and why water quality, not just equipment, determines whether the switch pays off.

Listen below.

Low-flow, high-head pump selection: Factors that affect operation and equipment reliability

From Plant Services: Low-flow, high-head pump applications can be complicated to specify. Matching a pump to a required flow rate and pressure is only the starting point. The pump also has to operate within its designed range, handle the actual fluid conditions of the application, as well as support the needed flow and pressure for the process.

Jose Gutierrez, executive director of engineered products at ITT Goulds Pumps, has spent more than four decades working with pump applications. He cautions engineers to begin by understanding the operating conditions, rather than simply selecting equipment based on the required duty point. Gutierrez sat down with Anna Townshend, Plant Services chief editor, to discuss pump options and how to select the right pump for a low-flow, high-head application.

Read the Q&A HERE.

The control engineering skills that matter more as AI capabilities expand

From Automation World: As AI takes on more programming work, controls engineers’ process knowledge and judgment become even more critical.

G Brooks-Zak writes:

Most of what I've written recently has been about where the software and logic processing hardware in our industry is headed. Software-defined automation, software engineering concepts like object-oriented programming and DevOps applied to industrial automation, and virtual PLCs running in IT-managed stacks.

More of what used to be determined by hardware will be handled in software, and controls workflows will increasingly resemble the ones software teams have used for years. It's tempting to read that as controls engineers needing to become software engineers, or completely obsolete, but the core controls engineering skill set isn't going anywhere. If anything, it's about to become more valuable.

Modern tools reduce the cost of producing logic, but they don't solve the harder part of the work, which is understanding a complex machine or automated process well enough to decide what that logic should do. They don't lower the cost of being wrong about the physical process, which has real implications for safety, business operations, and maintenance risk. When writing machine logic becomes faster, the bottleneck shifts toward engineering judgment.

Read the entire article HERE.

Recapping the week on Processing

Articles

Labor, food safety and efficiency drive processing equipment investment

Processors are turning to automation, AI and integrated technologies to address workforce constraints, strengthen food safety and sanitation, improve efficiency, and advance sustainability goals.

Practical factors behind better optical sorting

Stable flow, effective product presentation, controlled operating conditions, appropriate downstream handling and disciplined operating practices all help optical sorters deliver accurate, repeatable results.

Pack Expo International 2026 Preview: METTLER TOLEDO Product Inspection Group

The company's sales director highlights important topics and emerging trends ahead of PACK EXPO International 2026 in Chicago.

Application Corner: Starting and finishing

The latest installment in David W. Spitzer's long-running series.

Quiz Corner: Reynolds number

Do you have the right answer? Find out by reading the latest installment in David W. Spitzer's long-running series.

Flow measurement: Driving sustainability with data-driven precision

Accurate, reliable and auditable flow measurement provides the essential data points that help transform sustainability from a high-level concept into a series of intentional, measurable and verifiable actions.

Previewing Pack Expo International 2026 with Rob DeHaan of Hapman

The company's director of strategic sales & marketing highlights important topics and emerging trends ahead of PACK EXPO International 2026 in Chicago.

Podcast 

What PACK EXPO exhibitors are saying about the challenges facing processors in 2026

Processors are increasingly looking for equipment engineered around flexibility, integration and lifecycle value, rather than machines optimized around a single specification. Listen below.