Workpiece Transfer Chain Scheduling for Multi-Machine Production
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Solution Overview
Problem
Existing multi-machine, multi-process production systems face challenges in efficiently scheduling workpiece transfers between machines and robots, leading to suboptimal production workflows and increased downtime.
Innovation Solution
A method and system for generating a schedule for a plurality of machines and robots, which involves receiving production-system and process descriptions, constructing transfer chains based on the production-system state, and selecting an optimal transfer chain using selection criteria.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional scheduling methods are used for workpiece transfers, then the system is simpler to implement, but production efficiency decreases and downtime increases
Solution Approach 1:
The scheduling system dynamically generates and evaluates multiple transfer chains based on real-time production-system states, robot capabilities, and process requirements. Instead of using a fixed static schedule, the system adapts transfer sequences dynamically by recursively generating candidate chains and selecting optimal ones based on current conditions, thereby improving productivity while managing complexity through structured dynamic decision-making
Solution Approach 2:
The system performs preliminary generation of multiple candidate transfer chains before actual workpiece transfers occur. By pre-computing and evaluating possible transfer sequences based on production-system descriptions and process requirements, the system prepares optimized schedules in advance, reducing actual transfer time and improving production efficiency without requiring complex real-time decision-making during execution
2Loss of time
If optimal transfer chain selection is implemented, then downtime is reduced, but the complexity of schedule generation increases
Solution Approach 1:
The scheduling problem is segmented into distinct components: production-system description, process description, transfer chain generation, and transfer chain selection. By dividing the complex optimization problem into manageable segments with clear interfaces, the system can implement sophisticated optimization algorithms while maintaining manageable system complexity through modular architecture
Solution Approach 2:
The system uses feedback from production-system states and process requirements to iteratively improve transfer chain selection. By evaluating candidate chains against actual system conditions and selecting optimal sequences based on this feedback, the system reduces downtime through data-driven decisions while managing complexity through structured feedback loops rather than uncontrolled optimization
Data Source
AI summary
Some devices, systems, and methods receive a production-system description that describes respective operations that can be performed on workpieces by each of a plurality of machines and that describes capabilities of one or more robots to transfer the workpieces to and from each of the plurality of machines; receive a process description that describes at least one sequence of process operations to be performed on a workpiece; construct a plurality of transfer chains by recursively generating transfer chains based on a production-system state, the process description, and on the production-system description; and select a particular transfer chain of the plurality of transfer chains based on one or more selection criteria.