Semiconductor Back-End Factory Scheduling via Bottleneck Loading Plans

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Solution Overview

Problem

Current scheduling systems in semiconductor back-end factories are inadequate for managing complex reentrant flows and meeting stringent supply chain requirements, leading to inefficiencies and inability to optimize factory performance effectively.

Innovation Solution

A planning and scheduling system that employs mathematical programming models, specifically linear and mixed integer programming, to create a bottleneck loading plan, conversion schedule, and lot schedule, optimizing on-time delivery and minimizing conversions, which is then simulated and published to the dispatching system.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Ease of operation

If simple Excel spreadsheets and manual scheduling are used, then ease of operation is maintained, but productivity and ability to meet supply chain requirements deteriorate

Engineering Contradiction:

Improveease of scheduling operationVSAvoidfactory throughput

Core Design Contradiction:

Ease of operationVSProductivity

Solution Approach 1:

The patent replaces manual mechanical scheduling operations with an automated computer-based system that uses mathematical programming models and simulations to generate optimized schedules, thereby dramatically improving productivity while maintaining ease of operation through automated processes

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Solution Approach 2:

The system changes the parameters of the scheduling process by introducing mathematical programming models with multiple objectives (minimizing makespan, minimizing conversions, maximizing on-time delivery) that automatically optimize factory throughput without requiring manual intervention

Inventive Principle:

Principle #35Parameter changes

2Device complexity

If manual scheduling methods are used, then device complexity is low, but manufacturing precision and ability to optimize factory performance worsen

Engineering Contradiction:

Improvescheduling system complexityVSAvoidschedule optimization precision

Core Design Contradiction:

Device complexityVSManufacturing precision

Solution Approach 1:

The patent substitutes manual scheduling with an automated computer-based system that performs complex mathematical programming and simulations, achieving high manufacturing precision in schedule optimization while managing system complexity through automated algorithms

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Solution Approach 2:

The system introduces mathematical programming models and simulation software as intermediaries between the scheduling requirements and the actual factory operations, enabling precise optimization without requiring the end user to understand the complex underlying algorithms

Inventive Principle:

Principle #24Intermediary (Mediator)

3Ease of manufacture

If simple scheduling processes are used, then ease of manufacture is maintained, but ability to meet stringent supply chain requirements deteriorates

Engineering Contradiction:

Improvescheduling process simplicityVSAvoidon-time delivery reliability

Core Design Contradiction:

Ease of manufactureVSReliability

Solution Approach 1:

The system incorporates multiple objective functions in the mathematical programming models that simultaneously optimize makespan, conversions, and on-time delivery, achieving high reliability for meeting supply chain requirements while maintaining ease of manufacture through automated processes

Inventive Principle:

Principle #35Parameter changes

Solution Approach 2:

The system uses simulation feedback to validate and refine schedules before implementation, ensuring that on-time delivery requirements are met while maintaining the simplicity of the overall manufacturing process

Inventive Principle:

Principle #23Feedback

4Productivity

If automated mathematical programming models are implemented, then productivity and optimization capability improve, but device complexity increases

Engineering Contradiction:

Improvefactory throughputVSAvoidscheduling system complexity

Core Design Contradiction:

ProductivityVSDevice complexity

Solution Approach 1:

The patent implements automated mathematical programming models that use computer algorithms to perform complex optimization calculations, dramatically improving productivity while managing device complexity through software-based solutions

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Solution Approach 2:

The system employs universal mathematical programming models that can handle multiple objectives (makespan minimization, conversion minimization, on-time delivery maximization) and various factory scenarios, improving productivity across different situations while using a unified approach that manages complexity

Inventive Principle:

Principle #6Universality (Multi-functionality)

Data Source

PatentUS11100437B2Method for improving semiconductor back-end factories

Publication Date: 2021.08.24 APPLIED MATERIALS INC

AI summary

Embodiments presented herein provide techniques for planning and scheduling a semiconductor back end factory. The technique begins by running a first mathematical programing model applied to factory data and production targets that produces a solution and processing the solution to produce a bottleneck loading plan for at least one machine of the factory's bottleneck machine families. The technique further includes running a second mathematical programing model applied to the bottleneck loading plan that produces a solution and processing the solution to produce a conversion schedule for the at least one machine of the bottleneck machine families. The technique further includes creating a lot schedule for the factory by running a simulation that follows the conversion schedule. The technique further includes publishing the lot schedule.