Central Managing Unit for Container Quality Monitoring

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Solution Overview

Problem

Current container processing plants lack effective automated solutions for monitoring and maintaining product quality along the entire production line, relying on sample inspections that do not provide direct insights into quality issues.

Innovation Solution

An automated intelligent system that connects machine control units in container processing plants to a central managing unit via a communication interface, allowing real-time data analysis and predictive modeling to identify performance deviations and generate action plans for maintaining product quality, using KPIs and data analysis to detect anomalies and predict future trends.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If automated intelligent system with central managing unit is implemented, then product quality monitoring capability is improved, but device complexity increases

Engineering Contradiction:
Improveproduct quality monitoring capabilityVSAvoidsystem complexity
Core Design Contradiction:
Measurement precisionVSDevice complexity

Solution Approach 1:

Multiple machine control units from different processing machines are merged into a single central managing unit that consolidates data reception, performance measurement analysis, and action plan generation functions. This reduces overall system complexity while maintaining comprehensive quality monitoring across all machines.

Inventive Principle:
Principle #5Merging (Combining)

Solution Approach 2:

The central managing unit serves multiple functions: receiving data from various machines, analyzing performance measurements, detecting anomalies, generating action plans, and transmitting instructions back to machines. This multi-functional approach eliminates the need for separate specialized systems for each function.

Inventive Principle:
Principle #6Universality (Multi-functionality)

2Productivity

If real-time data analysis is performed by machine control units, then product quality management effectiveness is improved, but use of energy increases

Engineering Contradiction:
Improveproduct quality management effectivenessVSAvoidenergy consumption by machine control units
Core Design Contradiction:
ProductivityVSUse of energy by moving object

Solution Approach 1:

The computationally intensive tasks of data analysis, anomaly detection, and action plan generation are extracted from individual machine control units and relocated to a central managing unit. This allows local control units to operate with minimal processing burden, reducing their energy consumption while maintaining effective quality management through centralized intelligence.

Inventive Principle:
Principle #2Taking out (Extraction)

Data Source

PatentEP3187948B1System and method for managing product quality in container processing plants
Publication Date: 2019.03.06 SIDEL PARTICIPATIONS SAS
  • EP3187948B1 patent drawingFigure 1
  • EP3187948B1 patent drawingFigure 2
  • EP3187948B1 patent drawingFigure 3

AI summary

An automated system (25) for managing product quality in container processing plants (1) having a number of processing machines (2) cooperating in the processing of containers, the automated system (25) having a number of machine control units (22), each operatively coupled to a respective processing machine (2) to control operations thereof, each machine control unit (22) acquiring operating data from monitoring sensors (35) coupled to the processing machine (2), performing a pre-analysis of the acquired operating data, to determine performance parameter measurements indicative of a performance of operations executed in the processing machine (2), monitoring the performance parameter measurements, to determine an anomalous event in which these measurements drift outside a predetermined range indicative of a desired normal operating condition. The automated system (25) also has a central managing unit (32), acquiring from the machine control units (22) a subset of the respective performance parameter measurements, upon determination, by the machine control units (22) of the anomalous events; and processing the acquired performance parameter measurements in order to determine corrective actions to be performed in the processing machines (2) to maintain a desired product quality.