Order Allocation Rule Updates in Production Planning
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Solution Overview
Problem
Existing production planning systems require significant time and labor to modify order allocation rules due to the need for manual definition of modification ranges, as seen in PTL 1, which hinders efficiency in adapting to changing manufacturing conditions.
Innovation Solution
A production planning system that includes a performance rule generation unit, a rule modification unit, a modification value reflecting unit, and a rule evaluation unit to automate the process of generating performance rules, comparison tables, and modification rules, allowing users to efficiently update order allocation rules based on allocation performance data and user input.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If manual modification of order allocation rules is performed as described in PTL 1, then the modification process can be supported by defining a modification range, but it still requires significant time and labor for system engineers to repeatedly perform trial and error
Solution Approach 1:
The system performs preliminary actions by automatically generating multiple candidate modification rules and preparing comparison tables before the user makes final decisions. The rule modification support unit pre-processes the modification needs by creating structured comparison data between existing rules and target rules, so that users don't need to perform time-consuming trial and error modifications manually.
Solution Approach 2:
The system creates copies of existing allocation rules and generates multiple candidate modification versions. The rule modification support unit generates comparison tables that are essentially structured copies of the modification information, allowing users to review and select from pre-prepared modification options rather than manually experimenting with each change.
2Adaptability or versatility
If the number of order allocation rules increases to cover various manufacturing facilities, then the system can handle diverse manufacturing conditions, but the complexity of modifying these rules increases significantly
Solution Approach 1:
The system segments the complex rule modification process into distinct components: the rule modification support unit handles comparison and candidate generation, while the user handles final selection. This segmentation divides the overwhelming task of modifying numerous allocation rules into manageable pieces, where the support unit prepares structured modification information that users can systematically review.
Solution Approach 2:
The rule modification support unit acts as an intermediary between the existing allocation rules and the user. It mediates the complexity by automatically generating comparison tables and candidate modification rules, translating the complex state of numerous allocation rules into simplified, structured modification suggestions that users can easily evaluate without directly managing the complexity of all rules.
3Productivity
If automatic generation of modification rules is implemented, then the time required to modify rules can be reduced, but the system complexity increases due to additional processing units
Solution Approach 1:
The rule modification support unit is designed as a multi-functional component that performs multiple tasks: generating comparison tables, creating candidate modification rules, and presenting options to users. By consolidating these functions into a single support unit rather than separate independent systems, the patent achieves automatic rule modification capabilities while minimizing the increase in overall system complexity.
Data Source
AI summary
The time required to modify order allocation rules is shortened in a production planning system. A performance rule is generated, in which a manufacturing condition is set as the input and a manufacturing facility is set as the output, based on allocation performance data representing a performance of allocating the manufacturing facility for the manufacturing condition. A comparison table is generated representing a difference between the performance rule and an existing rule in which the manufacturing condition is set as the input and the manufacturing facility is set as the output. A modification rule is generated in which the existing rule is modified according to a user operation on the comparison table; and an evaluation index is calculated for production plan data corresponding to each of the existing rule and the modification rule. The rule modification unit generates the comparison table including a modification plan for the existing rule.