UDMTEK was created while the team was working on the virtual commissioning project, an industry-academic collaboration of the Hyundai Motor Company, in the UDM LAB laboratory of Ajou University in Korea. With the help of university academics and industrial engineers, the team began concentrating on R&D, particularly in the development of a virtual commissioning simulator. Hyundai and Kia cars, LG Display, LG Energy Solution, LG Innoteck, and several automation sectors received virtual commissioning simulators and analytic process tools from UDMTEK in 2008.
UDMTECK created MLP (machine language processing) technology throughout a protracted period of research and development that began in 2007 by deciphering the execution of unidentified control logic and data flow features inside a machine. Understanding control programs that are fixed statically and executed dynamically is how UDMTEK defines machine language processing.
Growing And Serving Through Leaps And Bounds
To deliver useful services, digital transformation collects all required data and turns it into knowledge. The MLP similarly gathers production control data and transforms it into knowledge. Automation control system transformation is a challenging endeavor since these systems are closed black boxes that are incomprehensible to users.
UDMTEK is able to automatically capture observable knowledge or comprehend the control operation of an automated controlled system. Each safe, heterogeneous, mysterious, ad-hoc piece of data and information can be converted into transparent digital understanding using MLP.
The COVID-19 epidemic has made working in digital environments more important to UDMTEK. To provide a service in the digital age, digital data and models are necessary. Additionally, it hastens the implementation of digital transformation to support integrated changing services and create a digital twin for productive collaboration. Moreover, MLP makes it simple to provide us with analytics solutions, such as conversational, explainable, and generative AI.
Technology At the Forefront Of Innovation
MLP gives us the ability to comprehend every anonymous data flow in the manufacturing process or machine, turning a once-difficult-to-understand “black box” into a “white box” that is easy to comprehend.
Before commissioning, the team may verify the control logic during the design phase by deciphering machine language. The UDMTEK team can also commission successfully by closely monitoring machine control behavior. By cutting down on delays and spotting anomalies, the operating phase of the process can be optimized. By examining the trend of operating characteristics, the UDMTEK team can forecast the future status of the machine’s health condition during the maintenance phase.
Sorting Themselves from The Crowd
In an automated manufacturing process, the control algorithms manage every specific device and operation while supplying output signals and receiving reaction input data. There are both static and dynamic data flows in those input-output signals. The static and dynamic semantics of machine operation status is provided to UDMTEK by the automatic interpretation of the control program and are crucial for determining a machine’s cycle time, spotting anomalous operations, and identifying trend changes.
Unfortunately, hardware controller users cannot use the software of other players, making it difficult for it to be interoperable, interpreted, and digitally visible. The UDMTEK team may examine the control software for various plays using UDMTEK MLP technology and turn the information into useful information.
UDMTEK Co. has worked with a variety of industries of varying sizes. UDMTEK tackled issues that its clients were encountering and assisted them in overcoming them.
An engineer can only find some issues in the automotive sector, the second battery process or any automated manufacturing process after the production line has been stopped. Even though the production process has been stopped, it can be difficult to pinpoint the exact reason for non-operation.
It can be challenging to pinpoint the specific issues when a processing activity is occasionally interrupted by an anomaly with an unknown cause. It frequently happens that some machines’ cycle times, accuracy, and other functional performances slowly deteriorate over time. With the use of simply comprehensible control-related data like logs, control programs, moving images, and other crucial indicators, MLP technology enables the reproduction of prior non-operation history.
Unnecessary delays can be eliminated, quiet operation stops can be discovered, anomalies that deviate from normal operation can be found, and changes in machine health conditions can be predicted using UDMTEK MLP technology.
Customers of UDMTEK explore, scrutinize, follow, and comprehend the intricate data flow of a manufacturing process in the digital setting. By replicating previous operations, they can find anomalies, shorten delay times, and detect trend changes in a variety of aberrant conditions. These essential signals include moving images, control log patterns, operation time trends, and any key indications trend.
Making Plans For A Good Future
The semantic meaning of a control program’s activity, both statically and dynamically, is captured by MLP, which interprets control programs executing inside of a machine. It may evolve and add new knowledge while building succinct, controllable semantic information. One can systematically preserve the knowledge that has already happened, which enables UDMTEK experts to repeatedly analyze and duplicate previous control operations, spot issues, and create explainable, generative, and conversational AI models. The UDMTEK team also confirms the effectiveness of AI models and foresees a future anomalous trend under the MLP-based digital twin.
NLP (natural language processing) analyses and interprets natural human language, whereas MLP is a key technique for analyzing and understanding machine control language. MLP can be used to collect relevant data, extract information, and create platforms, systems, and software.
MLP is a succinct digital transformation of a computerized controlled system that collects significant control data, creates multiple models, and mines semantics.
All in all, the customers can also create creative digital twins and add fresh research to the digital twin. With the aid of the engineer’s findings, the digital twin gradually becomes wiser, and the engineer also becomes smarter by cooperating with the digital twin.
Further, based on MLP, engineers and digital twins will be continually intelligent, collaborating in a complementary manner to create explainable, generative, and conversational AI.
