Production Planning Modules for Cross-Domain Coordination
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Solution Overview
Problem
Modern production systems face challenges in efficiently coordinating and optimizing the action sequences of multiple production modules for producing or processing different products or product variants, often requiring manual intervention which is complex and time-consuming, especially when product changes are frequent.
Innovation Solution
A method that breaks down the planning problem into sub-planning problems, using digital structural and processing information to generate detailed action sequences across planning modules, allowing for real-time planning and cross-domain optimization, with control signals generated for the production system based on refined action sequences.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual coordination and optimization of action sequences is performed by experts, then planning accuracy can be maintained, but planning time increases significantly especially when products or product variants change frequently
Solution Approach 1:
The planning problem is segmented into multiple independent sub-planning problems, each handled by a specialized planning module. This allows parallel processing of different action sequences while maintaining planning accuracy through domain-specific expertise in each module, significantly reducing overall planning time when product variants change.
Solution Approach 2:
Planning modules pre-process and generate action sequences based on stored knowledge and previous planning results. When product changes occur, the system can quickly adapt by building upon pre-computed plans rather than performing complete manual re-planning, reducing planning time while maintaining accuracy through iterative refinement.
2Measurement precision
If specialized planning programs are used for specific planning domains, then planning quality can be maintained, but cross-domain coordination capability is lacking and requires manual intervention
Solution Approach 1:
The system employs multiple specialized planning modules that each handle specific planning domains with high quality. These modules are coordinated through a universal framework that enables automatic cross-domain coordination, allowing the system to maintain planning quality in each domain while gaining versatile cross-domain coordination capability without manual intervention.
Solution Approach 2:
A coordination mechanism acts as an intermediary between specialized planning modules, automatically integrating their outputs and resolving conflicts. This mediator enables cross-domain coordination by translating between different planning domains and ensuring consistent action sequences across modules, eliminating the need for manual expert coordination.
3Measurement precision
If complete action sequences are planned for the entire production process, then comprehensive optimization can be achieved, but computational effort becomes prohibitively high
Solution Approach 1:
The comprehensive planning problem is divided into smaller sub-problems handled by individual planning modules. Each module performs optimization within its domain using reduced computational resources. The segmented approach maintains comprehensive optimization by coordinating results across modules while dramatically reducing total computational effort compared to monolithic planning.
Solution Approach 2:
Instead of planning all action sequences simultaneously with full computational resources, the system performs partial planning in each module and iteratively refines the complete sequence. This partial action approach achieves comprehensive optimization through multiple passes with modest computational effort at each stage, rather than requiring excessive computational resources in a single pass.
Data Source
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AI summary
According to the invention, for producing or machining a product (P), differently detailed structural information (SA) about a structure of the product and digital machining information (BA) about a machining process are read in. The structural information (SA) is examined as to whether a respective item of structural information is given further detail by a respective other structure. Furthermore, a plurality of machining sequences (BS1, BS2) for the product are generated from the structural information (SA) and machining information (BA) in such a way that an item of structural information (ZSA1) from a first machining sequence (BS1) is given further detail by an item of structural information (ZSA2) from a second machining sequence (BS2). The first machining sequence (BS1) is then transmitted to a first planning module (PL1) and the second machining sequence (BS2) is transmitted to a second planning module (PL2). By means of the received machining sequence (BS1, BS2), the planning modules (PL1, PL2) in each case generate an action sequence (AS1, AS2) as a planning result, a planning result (AS1) of the first planning (PL1) being taken into consideration by the second planning module (PL2) during generation of the action sequence (AS2) thereof. Control signals (CS) for controlling the production system (PS) are then generated and output by means of the action sequence (AS2) generated by the second planning module (PL2).