Industrial Process Efficiency Optimization eXplainable AI Solution
INFINITE OPTIMAL SERIES™, equipped with an AI engine developed by INEEJI, a company specializing in explainable artificial intelligence, analyzes process time series data to discover insights into degradation factors hidden in the data and provides actionable
Improvement effect
Artificial Intelligence cannot solve all the problems.
According to IDC, 92% of companies that applied artificial intelligence experienced failure, and after implementing DX, 33% of companies cited 'lack of solutions tailored to the process environment and low prediction accuracy' as the main reasons for failure in applying artificial intelligence.
Industrial sites need industry-specialized artificial intelligence that knows the process well.
In order to utilize complex and special industrial processes and a lot of process data collected in the field and derive results, an industrial AI solution with expertise and high prediction accuracy is needed. Artificial intelligence is emerging as an alternative to the challenges that the manufacturing industry must address(unstable supply of raw materials, increasing energy costs, decreasing professional workforce due to aged society) and increasing production efficiency through process optimization and supporting field workers to make better decision.
Complex industrial processes
Unstable supply of raw materials
Increasing energy costs
Decreasing professional workforce due to aged society
The main features of INFINITE OPTIMAL SERIES™ are as follow
INFINITE OPTIMAL SERIES™ learns key variables and the operating patterns of experienced operators to provide real-time insights for process improvement and guides operators on optimal operating conditions. It is a user-centered AI solution that has a proprietary AI engine with excellent application scalability and provides guidance on the desired prediction results at the customer's desired time based on AI technology with high prediction accuracy
Easy, fast and accurate preprocessing
• Unstructured data structured technology
• Data interpolation technology for handling missing data
• Data cleansing technology
• Automatic detection and elimination of defective data
• Normal data recovery technology
Deriving key insights from data
• Extract key data variables
• Extract causal relationships from process data
• Description of independent variables that affect variable variation and forecast objectives
• Proposal of optimal pattern for variable operation
Flexible and Scalable application
• Easy to integrate with existing models and platforms
• Easy to improve and update prediction model errors by having own engin
Provides user-centered AI guidance
• Supports worker’s process operation decision making
: Provides AI prediction basis (explainable AI technology)
• Present statistical properties of bulk data and AI output results
• Reduce process worker’s workload
AI Server SPEC

ubuntu 20.04
SAMSUNG DDR4-3200 16G X 2
M.2 NVMe 1TB
*4 patents registered and 12 applications completed, mainly in the US and Japan
Representative technology
Distilled Gradient Aggregation: Purify Features for Input Attribution in the Deep Neural Network (NeurIPS 2022) | World-class deep learning model operation core technology
Select input contributions that contribute to the prediction process and calculate prediction accuracy, and have improved algorithm with LeRF/MoRF scores of up to 0.436/0.020 compared to Google TensorFlow
Technology to Correct errors Inside Learning (CVPR 2021) | ‘Technology to repair error creation’ surpasses MIT Technology
Advance performance to correct generation model errors, Self-correction when improvements are discovered