At 11 o’clock in the middle of the night, there were only a few people left in the central control room of a petrochemical plant, but the parameters flashing on the big screen were more stable than during the day.
Ten years ago, the reactor needed to be monitored in three shifts. Now the system will automatically warn and adjust parameters when there are abnormal fluctuations. The engineer on duty only needs to confirm the decision.
Many people think that automation means reducing people and laying off workers. In fact, factories are undergoing a qualitative change from “physical liberation” to “mental upgrade”.
Process industry automation in 2026 is evolving along five clear directions. It is not simply replacing manpower, but restructuring the entire production logic.
Trend 1: From “attended” to “autonomous operation”, the factory learns to “think” on its own
In the smart workshop of Zhenhai Refining and Chemical Industry, the temperature of the reactor suddenly deviated from the preset value. The system completed abnormality identification, risk assessment, plan generation and adjustment within 0.3 seconds. The entire process did not require manual intervention.
This “autonomous operation plant (AOP)” is no longer a concept, but has become the core upgrade direction of the process industry.
Different from traditional automation, it can:
- Autonomously sense abnormalities 24/7 and predict the risk of equipment failure
- Dynamicly find real-time optimal solutions and automatically adjust process parameters when raw materials fluctuate
- From “maintaining
Stable” to “chasing the best”, energy consumption reduced by more than 12%
The central control room is changing from an “operation center” to a “decision-making center”, and engineers’ work has changed from “staring at the screen” to “optimizing algorithms”. This is not an unemployment crisis, but an opportunity for skill upgrading.
Trend 2: AI has changed from an “auxiliary tool” to a “core productivity”, solving the industry’s “old problems”
Lao Li, an old technician from a chemical company in Shandong, has been thinking about algorithm models on the computer recently.
His thirty years of operating experience are being transformed into the decision-making logic of the AI controller, which solves the industry problem of lag adjustment of reactor temperature.
In 2026, AI will achieve three major breakthroughs in the process industry:
- Predictive maintenance: Using equipment vibration, temperature and other data, it can predict the failure of key equipment such as pumps and compressors 7 days in advance to avoid unplanned shutdown losses. An ethylene plant saved 30 million yuan in maintenance costs this year
- Intelligent control: AI controllers can predict dynamic changes in production and implement ahead of schedule
Adjustment to suppress fluctuations in key parameters, and the product qualification rate increased to 99.8% - Full process optimization: from raw material proportioning to finished product separation, AI coordinated optimization, a refinery achieved an 8% reduction in unit energy consumption and a 15% reduction in carbon emissions
AI is not meant to replace old technicians, but to amplify the value of their experience a hundredfold and become the factory’s “smart engine”.
Trend 3: Digital twins become “standard”, virtual and real integration reconstructs the production model
In Zhongke Refining and Chemical’s smart ethylene factory, the digital twin is synchronized with the physical factory in real time, and new processes are “rehearsed” in the virtual space before going online to avoid trial and error costs in actual production.
This “verify first and then implement” model allows the process industry to bid farewell to “experience-based” production:
- The process transformation cycle is shortened by 40%, and the investment risk is reduced by 60%
- Employee training is completed in a virtual environment, and the speed of new employees getting started is increased by three times
- Emergency drills are repeated in the digital space, and the incident response time is shortened by 70%
Digital twins are no longer a “luxury” for high-end factories, but a “necessity” for the digital transformation of small and medium-sized process enterprises. The affordability has made the popularity faster than expected.
Trend 4: Open Internet breaks “data silos” and software-defined manufacturing becomes mainstream
In the past, a pharmaceutical factory’s DCS, MES, and ERP systems worked independently, and data required manual secondary entry, with an error rate as high as 5%.
Now through the unified standard of OPC UA, seamless connection between systems is realized, data is automatically transferred, and the efficiency is increased by 30%.
The process industry network in 2026 is undergoing three major changes:
- Industrial Ethernet fully replaces the traditional bus: Ethernet –
APL technology enables simultaneous power supply and high-speed data transmission on a single cable, reducing wiring costs by 50% - Popularization of software-defined manufacturing: decoupling hardware resources from software applications, shortening production line reconstruction time from months to weeks, and significantly improving flexible production capabilities
- Device-edge cloud
Mature collaborative architecture: real-time control is completed at the edge, and complex analysis is performed in the cloud, taking into account both response speed and computing power
This open architecture makes the factory no longer an information island, but an “intelligent node” integrated into the industrial Internet ecosystem, providing the possibility for cross-enterprise collaboration.
Trend 5: Green low-carbon and safety compliance are deeply bound, and automation assumes dual responsibilities
Huayi New Materials monitors energy consumption and emissions in real time through a digital platform, establishes PDCA closed-loop management, and achieves a 22% reduction in energy consumption and a 28% reduction in carbon emissions in three years.
The automation system in 2026 has been upgraded from a simple production tool to a “green guard” and “safety guardian”:
- Real-time monitoring of VOCs emissions and energy consumption, automatic optimization of process parameters, ensuring environmental protection standards
- Automatic interlocking protection for abnormal working conditions, explosion-proof, and
The response time of the leakage system is shortened to milliseconds - The entire operation log is traceable, meeting strict industry regulatory requirements
Safety and environmental protection are no longer “cost items”, but “value growth points” achieved through automation. Factories that meet ESG standards are more favored by the market.
The industry is coming out of three cognitive misunderstandings: First, it believes that automation means “unmanned” and ignores the value of human decision-making; second, it pursues a “large and comprehensive” system, which leads to a waste of resources; third, it separates technology and business, causing the system to be disconnected from actual production.
The real automation upgrade is to let technology serve production and free workers from repetitive labor to focus on more valuable innovative work.
To put it bluntly, the future of process industry automation is an intelligent ecosystem of “human-machine collaboration”.
Machines undertake 24-hour uninterrupted monitoring and execution, while humans are responsible for complex decision-making, process innovation and continuous optimization.
For practitioners, mastering the “driving skills” of automated systems is more competitive than being able to operate a single piece of equipment.
