UDMTEK: The Behemoth of Automated Manufacturing Process Management

Once a model is established, manufacturers can develop engineering software and services to create a concrete digital twin solution based on their inherent requirements.

The straightforward onboarding approach of DMTEK allows manufacturers to translate multiple control program languages into a Unified Digital Manufacturing Language (UDML). A computer language developed by UDMTEK, UDML can express various control program languages as one common piece of information. It understands the relationship between static and dynamic data flows in control programs by suggesting a relational-explainable AI model similar to the graphic neural network of natural language processing technology. Once the languages are translated to the UDML format, engineers can use the data to build explainable neural graph networks, maintaining a control log and essential domain data pertaining to a piece of machinery. UXIM is also capable of learning the built graph neural network of the schematics to understand the day-to-day functioning. If any changes are found in the control logic that may cause damage to production outflow, engineers can immediately step in to make the necessary alterations and maintain quality production. "We built a domain-specific digital twin platform for reproducing and analyzing control operations and their interpretationusing the explainable AI model," comments Wang Gi Nam.

Fortified by UDMTEK's automated manufacturing solution, engineers are armed with the necessary tools to improve production efficiency and reduce time and effort without compromising on results. While keeping a check on discrepancies such as a silent stop, hidden delay factors in the control process, and an unusual trend change, engineers can use the digital twin application to reproduce the corresponding control operations by examining and comprehending the control log, actual controlled image, and keydata flow concerning all related automated processes. A service technician can detect an anomaly's root cause and improve delay factors by investigating relational data flows and control models through this process. Machine language processing allows the responsible personnel to create reproducible digital schemas of machine control operations and enable them to interpret, analyze, and predict machine control characteristics at any stage of a production line.

A Class Apart

Currently, many companies try to improve the manufacturing process through digital transformation with data-driven software rather than hardware development. This approach could very well impede the definitive goals of an organization; UDMTEK, on the other hand, takes a different route. "Our machine language processing is based on the tangible goal-oriented digital transformation of control processes and the related data in building explainable AI models for many practical applications," comments Wang Gi Nam.

Likewise, UDMTEK's PLC eXpert software for control program design stage analytics can be used to search for static data of the program that controls a machine and detect errors in production design before a manufacturer commences a product output procedure.

"We Build a Domain-Specific Digital Twin Platform For Reproducing And Analyzing Control Operations And Their Meaning Using The Explainable AI Model And Related Information"

Besides, control and maintenance engineers can use the Black-Box product to observe and reproduce precise control logic programs that are pre-recorded. The added feature allows them to improve productivity, detect process and quality change, and predict machine health conditions by analyzing dynamic information of the operational process.

"With our highly innovative machine language processing, we have developed the gold-standard digital twin technology for industry-leading companies such as Hyundai/Kia Motors, LG Display, MOBIS, LG Energy, Samsung Electronics, and more," comments Wang Gi Nam. UDMTEK's impressive solutions allow manufacturers to alleviate their automated production and optimize operations through precise control analysis. Customers can analyze, comprehend, and predict future control characteristics of automated complex process conditions.

"Our Machine Language Processing Creates New Understanding And Relational Knowledge Connections Through Understanding Control Behaviors And Explainable Building Data And AI Models"

Tales Of Equipment Control Automation Supremacy

With many successful projects completed across various industries such as automotive, secondary battery cell, display, semiconductor, and electronics, to name a few, UDMTEK is leading from the forefront in implementing systems for operation analysis, abnormality detection, and maintenance of automation systems. These advantages have allowed clients to study control logic and reproduce past abnormal situations while operating in a digital environment. Through high-speed PLC log collection and transformation with control data and detailed model analysis, customers can improve facility performance and reduce the loss irrationality factor. Customers understand, analyze, learn, and predict automated-controlled complex behavior by reproducing and interpreting past critical events with explainable unified transformed data and AI models.

UDMTEK plans to acquire more knowledge from systematic information connections on a quest to scale automated manufacturing processes meticulously. "Our machine language processing creates new understanding and relational knowledge connections through accurate interpretation of control logic behaviors, deriving explainable data and digital twin AI models of automated machinery and processes," expresses Wang Gi Nam. To offer a fully customizable digital platform for production automation, UDMTEK is also focusing on designing and developing solutions that can further comprehend manufacturing, building, plant, and complicated equipment control, to name a few.

Heading into the future, UDMTEK believes that its proprietary machine language processing will enable the company to build manufacturing automation platforms with explainable and understandable data, models, and knowledge for engineers.