Data Collection for RSM In general, the data feeding into the model are initially organized in the RSM based on their associated plant, workshops, or production sections. They are classified according to various defect sources: Raw Material-Related Defects, Utilities-Related Defects, Batch-Plant Related Defects, Melting-Related Defects, Forming-Related Defects (Tin Bath), Annealing-Related Defects, Cold End-Related Defects, and […]
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Leantechnique Relational Smart Model (RSM) for Data Collection and Analysis – Part 1
In this article, we explore the diverse range of data essential for our smart model to function effectively, detailing how each type is pivotal in shaping the solutions our technology provides. From real-time operational data to historical performance metrics, we outline how comprehensive data collection forms the backbone of our cause-and-effect modelling, ultimately paving the […]
How Leantechnique Uses AI to Solve Glass Industry Challenges Through Cause-and-Effect Modelling
AI at the Core of Leantechnique Leantechnique integrates advanced AI technologies to streamline operations within the glass industry. At its core, the app utilizes machine learning algorithms and data analysis to predict and solve potential problems in the production pipeline. Data Analysis for Quality Control: In addition to machine learning, Leantechnique employs sophisticated data analysis […]
Time-Honoured Techniques: Navigating Troubleshooting
Preventive Techniques Traditionally, preventive measures in glass manufacturing involve maintaining critical process parameters within established operational limits. Thus, it is essential to inspect, regulate, and standardize all parameters from the grain size and composition of raw materials to the packaging of the final product. Additionally, ensuring the proper design and maintenance of all equipment, from […]
Understanding the Challenges in the Glass Industry – Part 2
Concurrent Processes: A Complex Challenge in Glass Manufacturing These intricate scenarios present significant challenges not only in traditional troubleshooting methods but also pose serious challenges for AI-powered software. These issues require careful consideration and strategic solutions. Primary Processes: Primary processes such as batching, melting, refining, homogenizing, forming, annealing, cutting, stacking, and storing in warehouses are […]
Understanding the Challenges in the Glass Industry – Part 1
For instance, if the primary issue is an increase in silica content in the glass batch, an operator might temporarily increase the furnace temperature to compensate. However, such rapid temperature adjustments are not sustainable and can accelerate the corrosion of refractory materials, leading to visible defects like seeds in the final product and other issues […]