Production Order Scheduling Under Overlapping Period Constraints
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Solution Overview
Problem
Existing methods struggle to plan a production order that satisfies both specification constraints and period constraints, especially when there is partial overlap in the period constraints of respective products.
Innovation Solution
A computation program is provided that calculates probabilities for each processing specification at each processing timing, determines the sum of probabilities for each timing, and uses cumulative sums to specify the processing timings of objects, thereby planning a production order that balances specification constraints with period constraints.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If a target tracking method is used to level specification frequency, then specification constraints are satisfied, but period constraints cannot be observed
Solution Approach 1:
The patent segments the planning process into two distinct phases: first determining valid processing timings that satisfy period constraints, then applying target tracking within those segmented time slots to satisfy specification constraints. This segmentation allows both constraints to be satisfied independently without conflict.
Solution Approach 2:
The patent performs preliminary determination of valid processing timings based on period constraints before executing the target tracking method. By pre-establishing the feasible time window for each object, the system ensures period constraints are met before optimizing for specification leveling.
2Reliability
If production order planning considers both specification constraints and period constraints, then constraint satisfaction improves, but computational complexity increases
Solution Approach 1:
The computation program is segmented into distinct functional modules: a period constraint verification module that identifies valid processing timings, and a target tracking module that levels specification frequency. This modular segmentation reduces overall computational complexity by breaking down the complex optimization problem into manageable sub-problems.
Solution Approach 2:
The patent introduces an intermediary data structure (valid processing timing information) that mediates between period constraints and specification constraints. This intermediary represents the feasible time window derived from period constraints, which then serves as the input domain for target tracking optimization, simplifying the overall computation.
3Manufacturing precision
If processing timing is optimized for specification leveling, then production quality improves, but processing period flexibility decreases
Solution Approach 1:
The patent dynamically determines the valid processing timing range for each object based on its specific period constraint, rather than using a fixed time slot allocation. This dynamic approach allows the system to adapt the feasible time window to each object's requirements while still applying target tracking for specification leveling within those flexible boundaries.
Data Source
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AI summary
A computation program comprising instructions which, when executed by a computer, cause the computer to execute: on a condition that each of objects is processed at any of a plurality of processing timings for which an order is determined, a processing specification is determined for each of the objects, a processing period in which processing is performed for each of the objects is determined, and the processing period includes one or more of the processing timings, calculating a probability obtained as a reciprocal of a number of the processing timings included in the processing period for each of the processing specifications of the objects, for each processing timing; calculating a sum of probabilities of the processing specifications for each processing timing; and calculating a cumulative sum of sums of the probabilities for the processing timing; and specifying the processing timings of the objects by using the cumulative sum.