Tank-Based Production Planning for Discrete Batch Lot Sizing
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Solution Overview
Problem
Existing production planning methods for tank-based production in the beverage industry fail to account for interdependence between packaging operations and tank storage, leading to distorted optimization results that affect shelf life, capacity, and cost due to the inability to plan production in discrete batches.
Innovation Solution
A multi-level tank-based production system that utilizes a tank-based production planner with customizable post-heuristic production planning to synchronize and integrate lot sizing, incorporating sensors for real-time data monitoring and flexible-capacity methods to optimize tank utilization and reduce spoilage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If linear programming is used for manufacturing decisions, then production planning can be done with continuous variables, but the ability to plan production in discrete batches is lost leading to distorted optimization results
Solution Approach 1:
The patent segments the production planning process into two distinct levels: (1) continuous variable production planning using linear programming at the aggregate level, and (2) discrete batch lot sizing at the execution level. This segmentation allows each level to operate with appropriate variable types - continuous for strategic planning and discrete for operational execution - thereby resolving the contradiction between continuous planning capability and discrete batch accuracy.
Solution Approach 2:
The patent introduces an intermediary post-processing step that translates the continuous production plan from linear programming into discrete batch lots. This intermediary layer acts as a bridge between the continuous optimization model and discrete manufacturing requirements, converting continuous variable outputs into actionable discrete batch schedules while maintaining optimization benefits.
2Ease of operation
If post-process lot sizing is applied after linear programming, then discrete batch production can be achieved, but optimization results become distorted impacting shelf life, capacity, and cost
Solution Approach 1:
The patent applies preliminary action by incorporating lot sizing considerations directly into the linear programming model through specialized lot-sizing constraints and objectives, rather than applying post-process lot sizing after optimization. This preliminary integration ensures that discrete batch requirements are considered during the optimization process itself, preventing distortion of optimization results while still achieving discrete batch production capability.
Solution Approach 2:
The patent implements dynamic lot-sizing strategies that adapt to changing conditions such as shelf life constraints, capacity availability, and cost parameters. The system dynamically adjusts batch sizes and timing based on real-time data from sensors and market conditions, allowing the optimization to remain reliable while accommodating discrete batch requirements.
3Productivity
If tank storage capacity is not integrated into production planning, then packaging operations can be optimized independently, but tank utilization is suboptimal and spoilage increases
Solution Approach 1:
The patent merges previously separate packaging operation planning and tank storage planning into a unified multi-level production planning system. By combining these functions into a single integrated model that simultaneously optimizes both packaging schedules and tank utilization, the system achieves improved tank utilization and reduced spoilage while maintaining packaging efficiency, directly resolving the contradiction between operational independence and resource optimization.
Data Source
AI summary
A system and method of a multi-level tank-based production system. Embodiments include planning data for one or more finished goods, the one or more finished goods produced from one or more semi-finished goods stored in one or more tanks, identifying, from the planning data, planned production orders for the one or more finished goods in each time bucket of a planning period, modifying the planned production orders to satisfy lot-size requirements of production operations of the one or more finished goods and time and tank capacity constraints of the one or more semi-finished goods, generating a tank-based production plan based, at least in part, on the modified planned production orders, and producing the one or more finished goods according to the tank-based production plan.