Production Planning Using Semantic Task-Capability Matching
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Solution Overview
Problem
Current production planning methods are inflexible and time-consuming, particularly for new product introductions, as they require manual planning for each manufacturing installation, leading to long market introduction times and lack of flexibility, which is inadequate for market trends like manufacture to order or manufacturing services.
Innovation Solution
A computer-implemented method for production planning that compares task descriptions from a work plan with manufacturing capabilities of various devices, allowing for situation-dependent planning by matching tasks with device capabilities, using semantic and multiattributive comparisons to bridge the granularity gap between abstract task descriptions and machine capabilities.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual production planning is performed for each manufacturing installation, then the manufacturing process can be precisely adapted to available equipment, but the market introduction time becomes long and flexibility is reduced
Solution Approach 1:
The patent applies preliminary action by pre-defining manufacturing capabilities of devices in a standardized format before production planning occurs. The capability descriptions are prepared in advance, allowing automated matching with work plan tasks without manual intervention during actual planning, thus reducing market introduction time while maintaining adaptation accuracy.
Solution Approach 2:
The patent introduces an intermediary layer - the standardized capability description format - that bridges between the work plan tasks and the actual manufacturing devices. This intermediary enables automated comparison and matching, eliminating the need for manual planning while ensuring precise adaptation to available equipment capabilities.
2Extent of automation
If central planning logic matches task descriptions with machine capability descriptions, then production planning can be automated, but complex machines cannot have their capabilities expressed completely in declarative form
Solution Approach 1:
The patent applies segmentation by dividing machine capabilities into hierarchical levels: general capabilities that can be described declaratively, and specific capabilities that require demonstration. This segmentation allows automated planning for general tasks while preserving detailed capability information for complex machines through the instruction mechanism.
Solution Approach 2:
The patent applies partial action by using declarative capability descriptions for tasks where they are sufficient, and resorting to demonstration instructions only when necessary. This partial use of automated matching with supplemental demonstration ensures automation where possible while maintaining complete capability expression for complex scenarios.
3Adaptability or versatility
If decentralized approaches with intelligent machines are used, then production planning flexibility is improved, but additional communication complexity and coordination functions are required
Solution Approach 1:
The patent merges central and decentralized approaches by having the production control system perform initial automated matching using standardized capability descriptions, then allowing individual devices to demonstrate specific capabilities if needed. This combination reduces communication complexity compared to fully decentralized approaches while maintaining flexibility through device-level demonstration capability.
Data Source
AI summary
The invention relates to a production planning method using a plurality of manufacturing devices (INTMA) according to which tasks (TD) of a work plan (BOP) are compared (MA) with manufacturing capabilities (SD) of the manufacturing devices (INTMA) and, depending on the one or more results (MAQ) of said comparison (MA), at least one or more manufacturing devices (INTMA) are commissioned to match their manufacturing capabilities (SD) with the task(s) (TD).