Least Cost Formulation System for Process Manufacturing
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Solution Overview
Problem
Process manufacturing companies face challenges in reducing costs while maintaining quality due to seasonal and regional variations in ingredient quality and availability, requiring efficient formulations that consider multiple factors.
Innovation Solution
A system that determines a least cost formulation for products by integrating ingredient properties, costs, inventory levels, and target properties, using a linear algorithm and simplex method to generate optimal ingredient compositions, integrated with enterprise resource planning systems for efficient production planning.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional formulation methods are used to maintain product quality, then product quality consistency is maintained, but manufacturing costs increase
Solution Approach 1:
The formulation is made dynamic by allowing ingredient specifications to vary within defined ranges based on current inventory and cost conditions. The system dynamically adjusts ingredient selections and proportions while maintaining product quality through computational optimization, enabling cost-effective formulations that adapt to changing conditions rather than relying on fixed traditional recipes.
Solution Approach 2:
The system changes multiple formulation parameters simultaneously including ingredient specifications, proportions, and substitutions. By optimizing across these parameters using linear programming and the simplex method, the system identifies cost-effective formulations that maintain quality requirements, transforming the static formulation process into an optimized dynamic system.
2Loss of energy
If ingredient substitutions are made to reduce costs, then manufacturing costs decrease, but product quality may deteriorate
Solution Approach 1:
The system incorporates feedback loops where formulation recommendations are continuously evaluated against quality requirements and inventory conditions. The optimization process uses quality constraints as feedback to ensure substitutions maintain acceptable product standards, and the system can iterate to improve formulations while preserving quality through controlled experimentation and validation.
3Loss of energy
If multiple ingredients are optimized simultaneously, then cost effectiveness improves, but computational complexity increases
Solution Approach 1:
The complex multi-ingredient optimization problem is segmented into manageable components. The system divides the formulation optimization into discrete ingredient decisions, evaluates substitutions individually or in small groups, and combines results through systematic optimization. This segmentation makes the computational problem tractable while still achieving comprehensive cost optimization across all ingredients.
Data Source
AI summary
A system for manufacturing a product receives a formulation specification that includes a plurality of ingredients for the product. The system further receives cost information for the ingredients and inventory information. The system then generates a least cost formulation for the product based on the formulation specification, cost information and inventory information.