Placement Line Allocation to Balance Component Variety and Line Load
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Solution Overview
Problem
Current methods for assigning assemblies to assembly lines in electronics production face challenges in minimizing production time fluctuations and component variance, particularly due to uncertainties in future assembly types and limitations in handling larger instances using standard solvers for mixed integer linear programming.
Innovation Solution
A computer-aided method using integer linear programming to optimize the assignment of assemblies to assembly lines, considering expected production times, cycle times, line utilization, and probability distributions, while limiting deviations from expected production times and minimizing component variance and production time variance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If mixed integer linear programming is used to optimize assembly assignments, then production time fluctuations and component variance are minimized, but computational complexity increases and standard solvers cannot handle larger instances
Solution Approach 1:
The patent segments the complex MIP problem into two separate optimization steps: first optimizing component variance (setup families), then optimizing production time variance. This decomposition allows each sub-problem to be solved more efficiently than the full combined problem, reducing computational complexity while maintaining optimization quality.
Solution Approach 2:
The patent extracts and separates the two optimization objectives (component variance and production time variance) into distinct calculation steps. By taking out the production time optimization as a separate step after component variance optimization, the method avoids the computational burden of solving both simultaneously using standard MIP solvers.
2Measurement precision
If standard solvers are used for mixed integer linear programming, then optimal solutions are found for small instances, but larger instances cannot be solved
Solution Approach 1:
The patent divides the assignment problem into two sequential optimization phases. The first phase optimizes component variance independently, and the second phase optimizes production time variance given the first phase's results. This segmentation enables handling of larger problem instances that would be intractable for standard solvers attempting to optimize both objectives simultaneously.
3Productivity
If assembly lines are assigned based on manual or heuristic methods, then computational resources are saved, but production time fluctuations increase and utilization efficiency decreases
Solution Approach 1:
The patent implements a self-service optimization system where the computer automatically performs the assignment optimization without requiring manual intervention or complex heuristic programming. The system uses the two-step optimization method to autonomously determine optimal assignments, improving line utilization efficiency while keeping the implementation relatively simple and automated.
Data Source
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AI summary
The invention relates to a method for allocating assemblies (LP1 –LP6) to placement lines (BL1 – BL2) for placing components (B1 – B6) on the assemblies (LP1 – LP6), in order to achieve a minimum variation in components with a predefinable maximum capacity utilization in terms of time for each placement line (BL1 – BL2), wherein the component variation is determined as the sum of the number of component types required on the placement lines (BL1 – BL2) and an expected production time is determined for each assembly type of the assemblies (LP1 – LP6) to be provided with components and for each placement line (BL1 – BL2), taking into consideration each cycle time for the assembly type on the placement line (BL1 – BL2), each reset time, the degree of utilization for each line and the expected number of pieces to be produced for each assembly type. The actual number of pieces to be produced arises according to a predeterminable probability distribution, wherein the sum of these expected overall production times for the set of assemblies (LP1 – LP6) allocated to a line (BL1 – BL2) may not exceed the maximum capacity utilization in terms of time of each placement line (BL1 – BL2), and the possible allocations of assemblies (LP1 – LP6) to the placement lines (BL1 – BL2) are restricted by the existing infrastructure or by user-defined specifications. The allocation is carried out such that for the probability distributions for the sum of the expected production times for each placement line, said distributions resulting from the aforementioned probability distributions for the number of pieces, the deviations from each expected value of the resultant probability distributions are limited by a predefinable maximum threshold value, and the allocation of the assemblies (LP1 – LP6) to the placement lines (BL1 – BL2) is calculated using the given specifications by means of integer linear programming.