Workflow Data Resolution for Sensor and Manual Log Mismatches
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Solution Overview
Problem
Conventional approaches to processing sensor data in manufacturing processes often result in erroneous data due to typing errors, mislabeling, or machine errors, which can lead to incorrect workflow data and require re-running the manufacturing process to correct, thus being inefficient and costly.
Innovation Solution
A system that processes sensor data by comparing it with manually logged information using predefined criteria, resolves duplicate entries, and updates the workflow based on corrected data, ensuring accuracy and efficiency without additional manufacturing processes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional approaches process sensor data without automated resolution, then data accuracy deteriorates due to erroneous entries, but system complexity remains low
Solution Approach 1:
The system segments the data processing workflow into distinct modules: sensor data acquisition, manual logging, automated comparison engine, and workflow update. Each module handles specific tasks independently, allowing complex data resolution functionality to be built from simpler, manageable components that can be processed and maintained separately.
Solution Approach 2:
An automated comparison engine is introduced as an intermediary component between sensor data collection and workflow execution. This mediator automatically compares sensor readings with manual logs, identifies discrepancies, and resolves errors without requiring direct human intervention in the data processing chain, thereby improving accuracy while maintaining manageable system complexity.
2Measurement precision
If erroneous sensor data is not resolved, then workflow accuracy deteriorates, but processing time and resources are saved
Solution Approach 1:
The system performs preliminary automated comparison and resolution of sensor data discrepancies before workflow execution. By pre-processing and correcting errors in advance, the system ensures accurate workflow data without requiring time-consuming manual review during production, thus improving workflow accuracy while minimizing processing time delays.
Solution Approach 2:
The comparison engine operates autonomously to self-resolve data discrepancies by automatically comparing sensor readings against manual logs and correcting erroneous entries. This self-service capability eliminates the need for human operators to manually verify and correct data, maintaining high workflow accuracy while minimizing the time and resources required for data processing.
3Measurement precision
If manual verification of sensor data is performed, then data accuracy improves, but labor requirements and operational complexity increase
Solution Approach 1:
The system implements self-service automated verification where the comparison engine independently performs data validation by comparing sensor readings with manual logs and automatically resolving discrepancies. This eliminates the need for human operators to manually verify each data point, maintaining high data accuracy while significantly simplifying operations and reducing labor requirements.
Solution Approach 2:
The system establishes a feedback loop where sensor data is continuously compared with manual logs, and discrepancies trigger automatic resolution processes. This automated feedback mechanism ensures data accuracy is maintained without requiring continuous manual intervention, thereby improving data reliability while keeping the system easy to operate.
4Measurement precision
If duplicate sensor entries are not removed, then data quality deteriorates, but processing complexity remains low
Solution Approach 1:
The duplicate removal functionality is segmented as a distinct processing step within the comparison engine. By isolating the duplicate detection and removal logic as a separate module, the system can efficiently identify and eliminate redundant sensor entries without overwhelming the overall system complexity, thereby maintaining high data quality through structured, manageable processing.
Data Source
AI summary
Systems and methods are provided for updating a workflow by resolving information of the workflow. The systems and methods may be configured to obtain sensor data describing an operation of the workflow, obtain information describing the workflow, determine whether the sensor data is consistent with the information based on predefined criteria, in response to determining that the sensor data is not consistent with the information, determine whether to resolve the sensor data, in response to determining whether to resolve the sensor data, resolve the sensor data to satisfy the predefined criteria or determining that the sensor data is unresolved, and update the workflow based on the resolved sensor data.