Supply Chain Demand Prioritization via Time-Sequence Priority Values
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Solution Overview
Problem
Traditional manufacture resource planning (MRP) systems prioritize demand based on a first-come-first-served method, leading to customers 'stealing' committed goods, causing the Bullwhip effect and resulting in excess inventory for suppliers, which is wasteful and inefficient.
Innovation Solution
A method that assigns priority values to forecasted demand numbers based on time sequences, determines differences in demand, and reallocates resources accordingly to ensure previously committed customer demands are met, even with changing demand pictures across all customers, using an automated system to allocate resources based on these priority values.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If a first-come-first-serve (FIFO) method is used to prioritize demand, then the system is simple to operate, but customers can steal goods previously committed to other customers, causing the Bullwhip effect and excess inventory
Solution Approach 1:
The system performs preliminary actions by assigning priority values to forecasted demand numbers before resource allocation occurs. This pre-assignment of priorities based on time sequences ensures that committed demands are protected from being stolen by subsequent demands, resolving the reliability issue while maintaining operational simplicity
Solution Approach 2:
The system determines differences between corresponding numbers in forecasted demand sets and uses this feedback to dynamically adjust priority assignments. This feedback mechanism ensures that resource allocation adapts to changing demand conditions while protecting previously committed demands, eliminating the Bullwhip effect without complex operations
2Reliability
If separate item codes are kept for different customers, products, and families of product lines, then customer demands can be tracked separately, but the system becomes wasteful and inefficient
Solution Approach 1:
The system uses a universal priority value assignment mechanism that can handle multiple customers, products, and product families through a single unified process. Instead of maintaining separate item codes, the universal system assigns priorities based on time sequences and demand differences, achieving accurate customer demand tracking while improving supply chain efficiency by eliminating redundant coding structures
Solution Approach 2:
The system changes the parameter used for tracking customer demands from separate item codes to priority values assigned based on time sequences and demand differences. This parameter change allows the system to maintain accurate tracking of customer-specific demands while using a unified resource pool, thereby improving productivity without sacrificing tracking accuracy
3Adaptability or versatility
If resources are reallocated based on changing customer demands, then the system is adaptable to new demands, but previously committed customer demands may not be met
Solution Approach 1:
The system performs preliminary assignment of priority values to forecasted demand numbers before resource allocation occurs. This pre-assignment based on time sequences ensures that previously committed demands are protected from being displaced by new demands, maintaining reliability while allowing adaptability through the priority-based allocation mechanism
Solution Approach 2:
The system dynamically determines differences between corresponding numbers in forecasted demand sets and adjusts priority assignments accordingly. This dynamic approach allows the system to adapt to changing demand conditions while maintaining the integrity of previously committed demands through the priority value mechanism, achieving both adaptability and reliability simultaneously
Data Source
AI summary
Methods of and devices for developing supply chain management are disclosed. Logic and devices implementing the logic for supply chain management avoid resources (e.g., machine component parts, raw materials, machines, machine capacity) being inappropriately re-allocated to customers without the customers' submission of forecasts in an accurate and timely manner.