Production Data Mapping for Root-Cause Process Improvement
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Solution Overview
Problem
Existing production management systems, particularly in complex sectors like chemical and pharmaceuticals, face challenges in ensuring defect-free products due to the difficulty in aligning and merging different production processes, and lack of systematic methods to identify and address out-of-scope issues, leading to inefficiencies and potential quality deficiencies.
Innovation Solution
A data-driven approach utilizing advanced analytics and artificial intelligence to map and analyze data from multiple production sources, identifying key process characteristics and improving production processes through supervised and unsupervised algorithms, such as Gradient Boosted Decision Trees and artificial neural networks, to enhance quality and reliability.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If traditional Six Sigma methods are used to monitor production parameters, then quality control is improved, but the system cannot systematically address out-of-scope issues and lacks adaptability to alternative approaches
Solution Approach 1:
The patent implements a universal data-driven framework that can handle multiple production processes and alternative methodologies (beyond just Six Sigma) through a common architecture. The system integrates various data sources, mapping techniques, and analysis methods into a single platform that adapts to different quality management approaches while maintaining systematic control over both in-scope and out-of-scope issues.
2Loss of information
If data from multiple production sources are integrated, then comprehensive analysis is improved, but data alignment and merging complexity increases
Solution Approach 1:
The patent introduces data mapping as an intermediary layer between diverse production data sources and the analysis engine. This mapping mechanism standardizes and aligns data from multiple sources without requiring direct integration complexity, acting as a mediator that transforms heterogeneous data into a unified format suitable for comprehensive analysis while managing the complexity of data alignment.
3Ease of operation
If expert input is used to define scope items in Six Sigma, then prioritization is improved, but systematic identification of out-of-scope root causes is hindered
Solution Approach 1:
The patent implements feedback mechanisms where the system continuously monitors production data, identifies deviations, and provides information about out-of-scope issues back to the analysis process. This feedback loop enables systematic identification of root causes that may have been initially excluded from scope definitions, allowing the system to iteratively refine understanding and address previously overlooked factors.
4Adaptability or versatility
If manual expert analysis is used for production processes, then flexibility is improved, but automation and efficiency are reduced
Solution Approach 1:
The patent enables the system to perform automated data collection, mapping, and analysis without requiring continuous manual expert intervention. The system serves itself by automatically gathering data from production sources, applying mapping rules, and generating insights through integrated analysis methods, thereby maintaining flexibility while significantly improving productivity and efficiency of process improvement activities.
Data Source
AI summary
A method for developing or improving a process for producing a product from a material comprising steps of acquiring process data from at least two different sources for the production process and its relevant parameters by using a Data Collecting computer; using the acquired process data related to the production process to perform a Process Mapping step by using a Process Mapping computer; assigning the acquired process data related to the relevant parameters of the production process to its corresponding process parts by performing a Data Mapping step by using a Data Mapping computer; analyzing the therefore mapped process data with a specific software performed on an Analyzing computer thereby identifying and validating one or more existing characteristics related to the quality or performance of the production process; and using the identified and validated characteristics to develop the production process or improve its performance.