Layered Factory Planning for Faster Capacity Balancing
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Solution Overview
Problem
Existing factory planning systems face challenges in generating high-quality plans efficiently due to numerous variables such as frozen schedules, material constraints, and resource utilization goals, leading to significant time and computing resource consumption, especially when changes occur.
Innovation Solution
A layered approach to factory planning is employed, where demands are grouped into sets and planned in a specified sequence, partitioning the problem into smaller components, using tuning algorithms to refine the solution, and prioritizing subsets based on attributes like due date or customer priority.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If existing planning systems consider all variables (frozen schedules, material constraints, resource utilization goals, etc.) to generate high-quality factory plans, then plan quality is improved, but processing time and computing resource consumption increase significantly
Solution Approach 1:
The patent segments the factory planning problem into multiple hierarchical layers (strategic, tactical, operational) and further divides demands into ordered subsets. Each layer and subset is planned separately in sequence, transforming one monolithic complex optimization problem into multiple smaller, manageable sub-problems that can be solved more efficiently while maintaining overall plan quality.
2Manufacturing precision
If existing planning systems consider all variables to generate highly optimized plans, then solution quality is improved, but computing resource consumption increases
Solution Approach 1:
The planning problem is divided into hierarchical layers and ordered subsets, reducing the computational complexity of each individual optimization problem. This segmentation allows the system to solve multiple smaller problems sequentially rather than one large problem, decreasing peak computing resource consumption while achieving comparable or improved solution quality through iterative refinement.
Solution Approach 2:
The system performs preliminary planning actions at higher hierarchical layers (strategic and tactical) before addressing operational details. By establishing frameworks, priorities, and constraints in advance, the system reduces the complexity of subsequent operational planning, thereby reducing overall computing resource requirements while maintaining solution quality.
3Adaptability or versatility
If existing planning systems handle changes in considered variables, then plan adaptability is improved, but solve time increases
Solution Approach 1:
The hierarchical segmentation allows the system to identify which layers and subsets are affected by changes and re-solve only those specific portions rather than the entire plan. This localized re-optimization maintains plan adaptability while significantly reducing re-solve time compared to complete re-planning.
Solution Approach 2:
By establishing hierarchical frameworks and ordered subsets in advance, the system creates a structured foundation that enables rapid identification and isolation of change impacts. This preliminary structuring allows for faster adaptation when variables change, as the system can quickly determine which segments need re-optimization.
Data Source
AI summary
A system and method are disclosed for layered planning. The method includes partitioning a planning problem into ordered subsets based on a prioritization scheme, applying a planning algorithm to optimize a first subset of the ordered subsets and freeze a corresponding plan, determining whether there are any remaining subsets that have not been optimized, in response to determining that there are remaining subsets that have not been optimized, loading a next subset ordered according to the prioritization scheme, optimizing the loaded subset without disturbing the frozen plan, and in response to determining that there are no remaining subsets to optimize, running a final pass of the planning algorithm to improve the global plan metrics. The method further includes where the prioritization scheme is based on a relative priority of tasks to be performed, a value of finished goods that are to be produced or requirements regarding a use of resources.