Q-Zone Kanban Capacity Control Under Semiconductor Q-Time Constraints

Solution Overview

Problem

Semiconductor manufacturing plants face challenges in maximizing production capacity while adhering to time constraints (Q-times) for Q-zones, as higher kanban capacity values lead to increased waiting times and potential Q-time violations, while lower values result in reduced machine utilization and throughput.

Innovation Solution

A method using a processing device to compute optimal kanban capacity values for Q-zones, considering overlapping zones and shared machine usage, by executing an assignment program that allocates Q-time allowances through linear programming to balance machine utilization and minimize Q-time violations, ensuring that machines operate at full capacity without exceeding Q-time requirements.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Productivity

If higher kanban capacity values are used, then machine utilization and throughput are improved, but waiting times increase and Q-time violations occur

Engineering Contradiction:

ImprovethroughputVSAvoidQ-time violation

Core Design Contradiction:

ProductivityVSLoss of time

Solution Approach 1:

The system dynamically adjusts kanban capacity values based on real-time conditions. The controller continuously monitors machine status, queue lengths, and time constraints, then adapts the kanban capacity to balance throughput maximization with Q-time compliance. This dynamic adjustment allows the system to respond to changing conditions rather than using fixed capacity values.

Inventive Principle:

Principle #15Dynamics

Solution Approach 2:

The system changes the kanban capacity parameter based on simulated performance metrics. By running simulations with different kanban capacity values and evaluating their impact on throughput and Q-time violations, the system identifies optimal parameter settings that resolve the contradiction between productivity and time compliance.

Inventive Principle:

Principle #35Parameter changes

2Reliability

If lower kanban capacity values are used, then Q-time violations are reduced, but machine utilization and throughput decrease

Engineering Contradiction:

ImproveQ-time complianceVSAvoidmachine utilization

Core Design Contradiction:

ReliabilityVSProductivity

Solution Approach 1:

The system dynamically adjusts kanban capacity values based on real-time conditions. The controller continuously monitors machine status, queue lengths, and time constraints, then adapts the kanban capacity to balance throughput maximization with Q-time compliance. This dynamic adjustment allows the system to respond to changing conditions rather than using fixed capacity values.

Inventive Principle:

Principle #15Dynamics

Solution Approach 2:

The system changes the kanban capacity parameter based on simulated performance metrics. By running simulations with different kanban capacity values and evaluating their impact on throughput and Q-time violations, the system identifies optimal parameter settings that resolve the contradiction between productivity and time compliance.

Inventive Principle:

Principle #35Parameter changes

3Ease of operation

If fixed kanban capacity values are used, then system operation is simplified, but optimal balance between throughput and Q-time compliance cannot be achieved

Engineering Contradiction:

Improvesystem operationVSAvoidproduction efficiency

Core Design Contradiction:

Ease of operationVSProductivity

Solution Approach 1:

The system performs self-optimization by automatically simulating different kanban capacity scenarios and selecting the optimal values without requiring manual intervention. The controller autonomously evaluates performance metrics and adjusts capacity values to maximize throughput while maintaining Q-time compliance, eliminating the need for complex manual tuning while achieving optimal productivity.

Inventive Principle:

Principle #25Self-service

Data Source

PatentUS11372396B2Control product flow of semiconductor manufacture process under time constraints

Publication Date: 2022.06.28 SHI WEIPING

AI summary

A method and system relate to executing, by a processing device, a first simulation of operations of a semiconductor manufacture plant without imposing a Q-time constraint on a Q-zone, determining a kanban capacity value associated with the Q-zone based on results from the first simulation, executing a second simulation of operations of the semiconductor manufacture plant using the kanban capacity value under the Q-time constraint, determining whether results of the second simulation meet performance indices, and responsive to determining that the results of the second plant simulation meet the performance indices, providing the kanban capacity value to a manufacture execution system to operate the semiconductor manufacture plant using the kanban capacity value.