Why doesn't traditional PID control advance energy savings in factories?

Because in environments with significant disturbances and load variations, it is difficult to simultaneously optimize multiple objectives and constraints such as quality maintenance, stable operation, and energy reduction, leading to inefficiencies in control.

What is 'Smart MPC' technology?

It is a next-generation predictive control technology that automatically derives optimal operations while predicting future behavior. By combining machine learning and optimization techniques, it achieves high-precision control without relying on specialized tuning.

What are the features of 'E-Smart MPC'?

It is an embedded AI control controller that can be directly installed in control panels. It features GUI operation and automatic adjustment functions, making it easier to introduce advanced control in the field.

Who is the main target for the webinar?

The target audience includes those responsible for energy cost reduction and GX compliance in factories, those considering control improvements without equipment updates, and those who want to achieve both energy reduction and quality stability.

Who are the organizers and collaborators of the webinar?

The webinar is organized by Proxima Technology Co., Ltd. and supported by Majise Co., Ltd.

AI News NQ Analysis

[Rebroadcast] [High Energy Consumption in Factories] How much can you save just by 'improving control'? Webinar Announcement

NQ Score 80/100

N1 Content Completeness 9

Key facts

[Rebroadcast] [High Energy Consumption in Factories] How much can you save just by 'improving control'? Webinar Announcement
Proxima Technology is hosting a webinar to introduce 'Smart MPC,' an advanced control technology that eliminates control inefficiencies in energy-intensive factory equipment to simultaneously achieve energy savings and quality stability.
Source: PR TIMES
Date: Fri May 29 2026 18:00:01 GMT+0900 (Japan Standard Time)

Direct answer

Proxima Technology is hosting a webinar to introduce 'Smart MPC,' an advanced control technology that eliminates control inefficiencies in energy-intensive factory equipment to simultaneously achieve energy savings and quality stability.

Citation: [Rebroadcast] [High Energy Consumption in Factories] How much can you save just by 'improving control'? Webinar Announcement (Fri May 29 2026 18:00:01 GMT+0900 (Japan Standard Time)), PR TIMES
Source: PR TIMES
Date: Fri May 29 2026 18:00:01 GMT+0900 (Japan Standard Time)

AI Summary (NQ-processed)

Proxima Technology is hosting a webinar to introduce 'Smart MPC,' an advanced control technology that eliminates control inefficiencies in energy-intensive factory equipment to simultaneously achieve energy savings and quality stability.

AI Analysis

Frequently Asked Questions

Q: Why doesn't traditional PID control advance energy savings in factories?: A: Because in environments with significant disturbances and load variations, it is difficult to simultaneously optimize multiple objectives and constraints such as quality maintenance, stable operation, and energy reduction, leading to inefficiencies in control.
Q: What is 'Smart MPC' technology?: A: It is a next-generation predictive control technology that automatically derives optimal operations while predicting future behavior. By combining machine learning and optimization techniques, it achieves high-precision control without relying on specialized tuning.
Q: What are the features of 'E-Smart MPC'?: A: It is an embedded AI control controller that can be directly installed in control panels. It features GUI operation and automatic adjustment functions, making it easier to introduce advanced control in the field.
Q: Who is the main target for the webinar?: A: The target audience includes those responsible for energy cost reduction and GX compliance in factories, those considering control improvements without equipment updates, and those who want to achieve both energy reduction and quality stability.
Q: Who are the organizers and collaborators of the webinar?: A: The webinar is organized by Proxima Technology Co., Ltd. and supported by Majise Co., Ltd.