Production Line Data Allocation for Multi-Line Work Management

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Solution Overview

Problem

Existing management systems for production lines require a large amount of data to manage multiple lines, making data management and editing inefficient and time-consuming.

Innovation Solution

A management method and system that provides configuration data, work data, and distribution data, with data registration and management for each production line, allowing for the creation of distribution data using identifiers and displaying maximum work times to optimize production efficiency.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Productivity

If mounting data is divided and allocated to each component mounter in a centralized management system, then each mounter can operate independently, but the amount of data to be managed increases significantly

Engineering Contradiction:
Improveindependent operation capabilityVSAvoiddata amount
Core Design Contradiction:
ProductivityVSQuantity of substance

Solution Approach 1:

The patent segments mounting data into three distinct types: configuration data (stored centrally), work data (distributed to individual mounters), and distribution data (mapping relationships). This segmentation allows each mouter to hold only necessary work data locally while the central manager maintains configuration and distribution data, reducing the data burden on each component while maintaining independent operation capability.

Inventive Principle:
Principle #1Segmentation

Solution Approach 2:

The patent introduces a hierarchical data management structure with three levels: central management computer, line management computers, and individual component mounters. This dimensional organization transforms the flat data distribution model into a multi-level architecture where data is stored and processed at appropriate levels, reducing the data amount at each individual level while maintaining overall system productivity.

Inventive Principle:
Principle #17Another dimension (Dimensionality change)

2Reliability

If a centralized management computer manages multiple production lines with detailed data, then comprehensive control is achieved, but data editing and movement become time-consuming

Engineering Contradiction:
Improvecomprehensive controlVSAvoiddata editing time
Core Design Contradiction:
ReliabilityVSLoss of time

Solution Approach 1:

The patent extracts detailed mounting data processing functions from the centralized management computer and assigns them to individual component mounters. Each mouter independently manages its own work data, eliminating the need for the central computer to edit and move data for each mounter individually. The central computer only manages high-level configuration and distribution data, significantly reducing data editing time while maintaining comprehensive control through the distribution data structure.

Inventive Principle:
Principle #2Taking out (Extraction)

Solution Approach 2:

Component mounters are empowered to independently manage their own work data, including automatic generation of work data from distribution data and autonomous execution of mounting operations. This self-service capability eliminates the need for manual data editing and movement by the centralized system, reducing data editing time while the centralized distribution data structure ensures comprehensive control across all production lines.

Inventive Principle:
Principle #25Self-service

3Stability of the object's composition

If all mounting data is stored centrally for each production line, then data consistency is maintained, but the system becomes complex and difficult to manage

Engineering Contradiction:
Improvedata consistencyVSAvoidsystem complexity
Core Design Contradiction:
Stability of the object's compositionVSDevice complexity

Solution Approach 1:

The patent implements local quality by allowing each component mouter to maintain its own work data locally rather than requiring all data to be stored centrally. Each mouter's data is optimized for its specific function, and the central distribution data provides the necessary coordination. This local data storage maintains data consistency through the distribution data structure while significantly reducing system complexity compared to centralized storage of all data.

Inventive Principle:
Principle #3Local quality

4Productivity

If distribution data is managed for each production line separately, then production efficiency can be optimized per line, but data management becomes more complex

Engineering Contradiction:
Improveproduction efficiencyVSAvoiddata management complexity
Core Design Contradiction:
ProductivityVSDevice complexity

Solution Approach 1:

The patent creates a universal distribution data structure that can be applied across multiple production lines with similar configurations. The distribution data format and management approach are standardized and can be replicated for different lines, allowing production efficiency optimization for each line while using the same data management framework. This universality reduces data management complexity compared to creating separate custom systems for each production line.

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

Data Source

PatentEP2894528B1Production line management method and production line management system
Publication Date: 2021.08.11 FUJI CORP
  • EP2894528B1 patent drawingFigure 1
  • EP2894528B1 patent drawingFigure 2
  • EP2894528B1 patent drawingFigure 3

AI summary

A production line management system 1 registers and manages distribution data for each of production lines 2A, 2B, 2C, 2D, and 2E, and thus, it is possible to manage work data in a unitary manner. Accordingly, it is possible to construct the management system 1 capable of managing production in a plurality of production lines 2A, 2B, 2C, 2D, and 2E with a small amount of data and to simplify a system configuration. In particular, distribution data is created by an identifier added to work data. With this, it is possible to achieve reduction in the amount of data.