Dynamic Employee-Machine Assignment for Production Flow Optimization
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Solution Overview
Problem
Existing production planning methods often result in inefficient assignments of employees to machines, leading to impaired production flow and complexity, particularly in large-scale production of products with multiple components.
Innovation Solution
A device and method that optimize production planning by dynamically assigning employees to machines based on competency and availability information, using mixed-integer optimization to minimize job changes and ensure even workload, while adhering to production sequences and machine criteria, with optional simulation and validation modules for refinement.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If fixed assignment of employees to machines is used for production planning, then planning simplicity is maintained, but production flow efficiency deteriorates
Solution Approach 1:
The patent implements dynamic employee-to-machine assignment that adapts to changing production requirements, employee availability, and competency levels. Instead of fixed assignments, the system continuously optimizes allocations based on current conditions, allowing the production plan to respond flexibly to variations in demand, machine status, and workforce availability, thereby improving production flow efficiency while maintaining planning manageability through automated optimization.
2Productivity
If detailed optimization of production planning is implemented, then production flow efficiency is improved, but planning complexity increases
Solution Approach 1:
The patent replaces manual, complex optimization processes with an automated computer-based optimization system. The system uses algorithms to automatically determine optimal employee-to-machine assignments and production sequences, substituting the need for complex manual planning with automated computational methods. This reduces the perceived complexity for human operators while achieving detailed optimization of production flow.
Solution Approach 2:
The optimization system performs self-service by automatically generating optimized production plans based on input data about employee competencies, availability, and machine requirements. The system independently conducts the complex optimization calculations and generates actionable schedules without requiring intensive human intervention, thereby improving production flow efficiency while keeping the planning process manageable through automation.
3Adaptability or versatility
If adaptive recalculation of production planning is enabled, then responsiveness to deviations is improved, but computational requirements increase
Solution Approach 1:
The system implements partial recalculation by focusing optimization efforts on specific affected areas when deviations occur, rather than completely recalculating the entire production plan. When a deviation is detected, the system identifies the impacted production steps and reoptimizes only those portions, leaving unaffected areas unchanged. This approach improves responsiveness to deviations while significantly reducing computational requirements compared to full recalculation.
Data Source
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AI summary
The invention relates to a device for optimizing production planning for production of at least one product, wherein employees are assigned to operate machines for the production of the at least one product, the device comprising: a) an interface, which is designed to read in planning data for the production and competency information with respect to machine operation and availability information regarding the employees, b) a first optimization module, which is designed to determine optimized percentage assignment of the employees to the machines in question for a specified time period according to the planning data, the competency information and the availability information, c) a second optimization module, which is designed to determine optimized production planning data, wherein an optimized temporal sequence of production steps in question is determined according to the planning data, with respect to the employees and machines, in accordance with the percentage assignment and in accordance with the number of employees needed for a production step, and d) an output module, which is designed to output the optimized production planning data for the production of the at least one product according to the optimized production planning data.