Plating Apparatus Machine Learning Resistance Control

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Solution Overview

Problem

Setting optimal resistance values for variable resistors in a plating apparatus to ensure uniform electric current distribution and film thickness across a substrate is challenging due to varying contact resistances and inherent substrate surface distributions.

Innovation Solution

A plating apparatus equipped with a controller using a machine learning model to determine and adjust resistance values based on input parameters such as plated film thickness, electric current, voltage, substrate shape, and plating liquid characteristics, ensuring equal current flow through multiple paths and optimizing film thickness uniformity.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Manufacturing precision

If variable resistors are connected to each electric contact to control current distribution, then film thickness uniformity can be improved, but the complexity of setting and adjusting resistance values increases significantly

Engineering Contradiction:

Improvefilm thickness uniformityVSAvoidresistance value setting complexity

Core Design Contradiction:

Manufacturing precisionVSDevice complexity

Solution Approach 1:

The system automatically determines optimal resistance values through machine learning without requiring manual adjustment. The controller executes a learning algorithm that autonomously calculates and sets resistance values based on substrate characteristics and desired film thickness distribution, eliminating the need for operators to manually tune each variable resistor.

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

The system incorporates feedback mechanisms where the controller monitors plating results and uses machine learning to adjust resistance values iteratively. By comparing actual film thickness measurements with target values, the system learns and refines resistance settings to achieve optimal current distribution and uniform plating.

Inventive Principle:

Principle #23Feedback

2Reliability

If manual adjustment of variable resistors is performed to compensate for contact resistance variations, then current distribution can be improved, but the time and skill required for operation increases

Engineering Contradiction:

Improvecurrent distribution uniformityVSAvoidoperation simplicity

Core Design Contradiction:

ReliabilityVSEase of operation

Solution Approach 1:

The system replaces manual mechanical adjustment of variable resistors with an automated electronic control system. The controller uses machine learning algorithms to calculate and electronically set resistance values, substituting the mechanical tuning process with automated computational methods that are both more accurate and easier to operate.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Solution Approach 2:

The system dynamically changes resistance parameters based on substrate characteristics and plating conditions. Rather than fixed manual settings, the controller adjusts resistance values as variables that can be modified based on measured data, substrate geometry, and desired outcomes, making the system adaptable and easy to operate across different scenarios.

Inventive Principle:

Principle #35Parameter changes

3Manufacturing precision

If multiple variable resistors are used to address contact resistance variations, then plating uniformity can be improved, but the difficulty of determining optimal resistance values increases

Engineering Contradiction:

Improveplating uniformityVSAvoidresistance value determination difficulty

Core Design Contradiction:

Manufacturing precisionVSDifficulty of detecting and measuring

Solution Approach 1:

The machine learning algorithm acts as an intermediary between the variable resistors and the control system. Rather than directly measuring and adjusting each resistor, the algorithm processes substrate data and plating parameters to determine optimal resistance values, serving as an intelligent mediator that simplifies the determination process while maintaining precision.

Inventive Principle:

Principle #24Intermediary (Mediator)

Applied Scientific Principles

This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.

Function Achieved in This Case

The solution enables precise control of resistance values, leading to improved uniformity in film thickness distribution on the substrate by compensating for contact resistance variations and substrate-specific factors, enhancing the overall plating process efficiency.

Implementation Method 1

Methodology Applied

Scientific EffectElectrical Resistance: Electrical Resistance

Implementation Method 2

a plating apparatus and a plating method for plating a substrate by making electric current flow from an anode to the substrate

Methodology Applied

Scientific EffectElectroplating: Electroplating

Data Source

PatentUS20230203701A1Plating apparatus and plating method

Publication Date: 2023.06.29 EBARA CORP

AI summary

Uniformity in plated film thickness in a plating apparatus is improved. A plating apparatus for plating a substrate by making electric current flow from an anode to the substrate is provided. The plating apparatus comprises: plural anode-side electric wires which are electrically connected to the anode via plural electric contacts on the anode; plural substrate-side electric wires which are electrically connected to the substrate via plural electric contacts on the substrate; plural variable resistors positioned, in at least one of the anode side and the substrate side, in middle positions in the plural anode-side electric wires or the plural substrate-side electric wires; and a controller constructed to adjust each of resistance values of the plural variable resistors.