JP3796101B2

JP3796101B2 - Foreign object inspection apparatus and method

Info

Publication number: JP3796101B2
Application number: JP2000199446A
Authority: JP
Inventors: 茂阿部; 裕之山下
Original assignee: Hitachi High Technologies Corp
Current assignee: Hitachi High Tech Corp
Priority date: 2000-06-30
Filing date: 2000-06-30
Publication date: 2006-07-12
Anticipated expiration: 2020-06-30
Also published as: JP2002014055A

Description

【０００１】
【発明の属する技術分野】
この発明は、異物検査装置および方法、特に、被検査面上の微小異物や凹凸傷やスクラッチなどの欠陥を高感度で検出する異物検査装置および方法に関し、例えば、半導体ウェハ（以下、ウェハという）、マスク、レチクル、ガラス基板などの表面に付着した異物や凹凸傷やスクラッチなどの欠陥を検出して、その異物や欠陥のサイズ（粒径）、形状などを検査する異物検査装置および方法に関するものである。
【０００２】
【従来の技術】
半導体集積回路（例えば、ＩＣ）などの製造過程において、ウェハの表面、あるいは半導体領域、絶縁領域、電極、配線などを形成する各種パターンに異物が付着すると、ＩＣの性能が劣化するため、パターン形成後に異物検査装置によってウェハ表面の異物有無の検査がなされる。
【０００３】
ところで、ＩＣを高歩留りで製造するためには、ウェハ表面に付着した異物を検出して、その異物のサイズ（粒径）、形状などを検査し、各種半導体製造装置や工程の清浄度を定量的に把握し、製造プロセスを的確に管理する必要がある。従来、異物のサイズ、形状などを検査する異物検査装置として、例えば、特開平１１−５１６２２号公報に示された装置がある。
【０００４】
上記の従来知られた異物検査装置は、ウェハ表面にレーザ光を斜方照射し、該ウェハ表面の付着異物の凹凸による散乱光を検出し、該散乱光の検出データに基づきウェハ上のパターンの同一性を判定して、該パターン以外を異物として検出する。次に、異物を検出した部分を撮像装置により撮像し、該撮像装置による画像データから異物画像を抽出し、該抽出異物画像に基づき異物のサイズ、形状を測定する。しかしながら、上記の異物検査装置においては、異物検査後に、異物部分を撮像装置により撮像し、該撮像装置の画像データから抽出した抽出異物画像に基づいて異物のサイズ、形状を測定するため、撮像装置の動作時間分、ウェハの異物有無の検査を行うことができなくなることから、スループットが低下してしまう。
【０００５】
【発明が解決しようとする課題】
本発明は、上記の点に鑑みて為されたものであり、被検査物表面の異物検査にあたって異物のサイズ（粒径）を判定もしくは推定できる異物検査装置および方法を提供することを目的とする。また、被検査物表面の異物検査にあたって異物の形状を判定もしくは推定できる異物検査装置および方法を提供することを目的とする。
【０００６】
【課題を解決するための手段】
本発明に係る異物検査装置は、被検査物表面の状態を光学的に検出し、複数画素からなる検出データを出力する検出手段と、前記検出データに基づき前記被検査物表面の異物を判定し、異物抽出データを出力する異物判定手段と、前記異物抽出データを所定画素数からなる単位領域毎にグループ分けし、各グループ毎に該グループ内の異物とみなされる画素数を計数する演算手段と、前記演算手段で求めた各グループ毎の異物画素数に基づき、当該グループに対応する単位領域における異物のサイズを推定する判定処理を行う判定手段とを具えることを特徴とする。これによれば、１つの単位領域内に存在する異物を１つの異物とみなしてそのサイズを推定することができるので、パターン認識などの複雑な処理を行うことなく、極めて簡単な構成で異物のサイズ（粒径）を判定もしくは推定できる。
【０００７】
本発明は、上記のような装置の発明として構成することができるのみならず、方法の発明として構成することができる。すなわち、本発明に係る異物検査方法は、被検査物表面の状態を光学的に検出し、複数画素からなる検出データを出力する工程と、前記検出データに基づき前記被検査物表面の異物を判定し、異物抽出データを出力する工程と、前記異物抽出データを所定画素数からなる単位領域毎にグループ分けし、各グループ毎に該グループ内の異物とみなされる画素数を計数する工程と、前記各グループ毎の異物画素数に基づき、当該グループに対応する単位領域における異物のサイズを推定する判定処理を行う工程とを含むことを特徴とする。このような構成の異物検査方法においても、１つの単位領域内に存在する異物を１つの異物とみなしてそのサイズを推定することができるので、パターン認識などの複雑な処理を行うことなく、異物のサイズ（粒径）を判定もしくは推定できる。
【０００８】
また、本発明に係る異物検査装置は、被検査物表面の状態を光学的に検出し、複数画素からなる検出データを出力する検出手段と、前記検出データに基づき前記被検査物表面の異物を判定し、異物抽出データを出力する異物判定手段と、前記異物抽出データを所定画素数からなる単位領域毎にグループ分けし、各グループ毎に該グループ内の異物とみなされる画素数を計数する演算手段と、前記各グループ毎の前記異物抽出データの前記各単位領域における各画素毎の異物検出レベルの和を算出する手段と、前記異物検出レベルデータの和と前記異物画素数の相関性に基づき、当該グループに対応する単位領域における異物の形状を推定する判定手段とを具えることを特徴とする。これによれば、１つの単位領域内に存在する異物を１つの異物とみなしてその形状を推定することができるので、パターン認識などの複雑な処理を行うことなく、極めて簡単な構成で異物の形状を判定もしくは推定できる。
【０００９】
本発明は、上記のような装置の発明として構成することができるのみならず、方法の発明として構成することができる。すなわち、本発明に係る異物検査方法は、被検査物表面の状態を光学的に検出し、複数画素からなる検出データを出力する工程と、前記検出データに基づき前記被検査物表面の異物を判定し、異物抽出データを出力する工程と、前記異物抽出データを所定画素数からなる単位領域毎にグループ分けし、各グループ毎に該グループ内の異物とみなされる画素数を計数する工程と、前記各グループ毎の前記異物抽出データの前記各単位領域における各画素毎の異物検出レベルの和を算出する工程と、前記異物検出レベルデータの和と前記異物画素数の相関性に基づき、当該グループに対応する単位領域における異物の形状を推定する工程とを含むことを特徴とする。このような構成の異物検査方法においても、１つの単位領域内に存在する異物を１つの異物とみなしてその形状を推定することができるので、パターン認識などの複雑な処理を行うことなく、異物の形状を判定もしくは推定できる。
【００１０】
【発明の実施の形態】
以下、添付図面に従って本発明に係る異物検査装置および方法を説明する。
図１において、異物検査装置Ａは、ウェハ１を載置するＸＹ移動機構２と、光ビーム照射手段３と、駆動制御手段４と、受光光学系５と、散乱光検出センサ６と、異物判定部７と、グルーピング処理部８と、メモリ９と、ＣＰＵ１０とを有する。ウェハ１は、図１（ａ）に示すように、回路パターンを形成したＩＣチップ１ａを表面に多数有するパターン付ウェハであり、ＸＹ移動機構２のＸＹテーブル２ａ上に固定されている。ウェハ１の表面には所定の低角度で光ビーム照射手段３（例えばレーザ光照射手段）からスポット状のレーザ光Ｌが斜方照射される。ＸＹ移動機構２は、ＸＹテーブル２ａが駆動制御手段４によりＸ方向およびＹ方向に移動されることによって、レーザ光Ｌに対しＩＣチップ１ａ領域全域を走査させる。ウェハ１の表面にレーザ光Ｌが斜方照射されると、該ウェハ１表面の図示しない付着異物および回路パターンから暗視野下の散乱光が発生する。詳しくは、ウェハ１表面の平滑面に付着異物や回路パターンがあると、その付着異物や回路パターンの凹凸によってレーザ光Ｌが乱反射して散乱する。付着異物や回路パターンで乱反射した散乱光は受光光学系５の図示しない集光レンズによって散乱光検出センサ６に集光される。
【００１１】
散乱光検出センサ６は、レーザ光Ｌの走査方向（図示の例ではＹ方向）にライン状に配列した多数の各画素（固体撮像光電変換素子）を有し、該各画素が受光光学系５を介して散乱光を受光し、所定の複数画素（例えば８画素）からなるデジタルの検出データＤ１を異物判定部７に出力する。異物判定部７では、散乱光検出センサ６からの検出データＤ１に基づいてウェハ１上の異物を判定し、異物抽出データＤ２をグルーピング処理部８に画素毎に出力する。すなわち、散乱光検出センサ６の各画素からの検出データＤ１と、先に取り込んだ隣のＩＣチップ１ａの同一位置でのチップデータとを照合し、不一致の場合に該検出データを異物抽出データＤ２としてグルーピング処理部８に画素毎に出力する。すなわち、回路パターンは隣合うチップで同一のため、検出データＤ１の不一致部分が異物に相当し、回路パターンを排除した異物のみを示す異物抽出データＤ２を得る。例えば、異物抽出データにおいて、異物とみなされない画素のレベルは“０”であり、異物とみなされる画素はその散乱光の検出レベルに応じたレベルを得る。グルーピング処理部８では、検出画素計数部８ｂによって異物判定部７からの異物抽出データＤ２を所定画素数（例えば８×８画素）からなる単位領域毎にグループ分けし（図１（ｃ）参照）、各グループ毎に該グループ内の検出画素数Ｎ（図示の例では黒塗り部分の都合６画素）を１個の異物Ｐの面積とみなして計数する。レベル最大値検出部８ａでは、各グループ毎の異物抽出データＤ２の各画素毎の異物検出レベル（輝度レベル）を比較し、異物検出レベルの最大値Ｍを検出することで、その最大値Ｍを１個の異物Ｐの輝度情報としてみなす。図１（ｃ）の例では、異物Ｐとみなされる６個の各画素のレベルが３，１，５，８，４，２であり、座標（４，４）のレベル“８”が最大値Ｍである。グルーピング処理部８は、上記の最大値検出処理および検出画素計数処理を実行するために構成された所要のハードウェア回路からなっており、これらの処理をリアルタイムに実行し、その最大値Ｍ（図１（ｃ）の例では“８”）と検出画素数Ｎ（図１（ｃ）の例では“６”）をメモリ９に格納する。ＣＰＵ１０は、グルーピング処理部８で求めた各グループ毎の検出画素数Ｎに基づき、当該グループに対応する単位領域における異物Ｐのサイズを推定する判定処理を行う。すなわち、ＣＰＵ１０では、メモリ９から検出画素数Ｎを取り込み、下記の（１）式で異物Ｐの面積Ｓを求め、（２）式に示すように異物Ｐを１つの円とみなして、その半径ｒを求める。なお、ｕは１画素に相当する面積である。
ｕ（１画素の面積）×Ｎ（検出画素数）＝Ｓ…（１）
Ｓ＝ｕ×Ｎ≒πｒ²…（２）
∴ｒ＝√〔（ｕ×Ｎ）／π〕
を算出する。例えば、ｕ＝４平方ミクロンとすると、図１（ｃ）の場合、Ｎ＝６であるから、上記の（２）式よりｒ＝２．８ミクロンを算出する。このようにＣＰＵ１０により推定された判定処理結果は例えば異物マップやヒストグラムなどの表示方法により図示しない表示手段（例えばディスプレイユニットやプリンタなど）に表示することができる。更に、必要に応じて、その算出結果と検査条件（レーザ光Ｌのパワー、ＮＤ（Neutral Density ）フィルタ、偏光板）および予め粒径がわかっている不図示のＰＬＳ標準粒子（校正用標準粒子）の結果とを用いて、ウェハ１上に存在する異物Ｐの実際の粒径を求める。詳しくは、粒径を異にする多種類のＰＬＳ標準粒子について、レーザ光Ｌのパワー、ＮＤフィルタおよび偏光板などの条件を変えて反射強度を測定したデータを記憶させておき、実際の異物検査で得られた算出結果と比較して、異物Ｐの実際の粒径を求める。なお、ＮＤフィルタおよび偏光板は、例えば受光光学系５に設けられる。ＮＤフィルタは、散乱光の透過率を適宜調整して散乱光検出センサ６で受光する散乱光を適度に減衰させることにより該散乱光検出センサ６の飽和を防止する。偏光板は、散乱光に含まれる所定の偏向成分（例えばＳ偏向成分）をカットし、他の偏向成分（例えばＰ偏向成分）を散乱光検出センサ６で受光できるようにするために使用される。
【００１２】
図２に本発明に係る異物検査装置および方法の他の実施例を示す。なお、前述した異物検査装置と共通する部分には同じ符号を付して、その説明を省略する。本実施例の異物検査装置Ａは、図２（ａ）に示すように、グルーピング処理部８において、レベル最大値検出部８ａに代えて、異物レベル算出部８ｃが設けてある。異物レベル算出部８ｃでは、各グループ毎の異物抽出データＤ２の各画素毎の異物検出レベルの総和ΣＱを求める。図１（ｃ）の例では、異物Ｐとみなされる６個の各画素の異物検出レベルが３，１，５，８，４，２であり、それらの異物検出レベルの和“２３”が総和ΣＱである。グルーピング処理部８は、上記の異物レベル算出処理および検出画素計数処理を実行するために構成された所要のハードウェア回路からなっており、これらの処理をリアルタイムに実行し、その総和ΣＱ（図１（ｃ）例では“２３”）と検出画素数Ｎ（図１（ｃ）の例では“６”）をメモリ９に格納する。ＣＰＵ１０では、グルーピング処理部８で求めた各グループ毎の異物検出レベルの総和ΣＱと検出画素数Ｎの相関性に基づき、当該グループに対応する単位領域における異物Ｐの形状を推定する判定処理を行う。散乱光測定方式の場合、画素単位の異物の凹凸が大きいほど検出レベルが大きく、異物が平坦なものほど検出レベルが小さい。このような画素単位の異物検出レベルの大小傾向から全体的な異物の形状（塊状であるか、又は平坦状であるか）をある程度類推することができる。また、複数画素からなる単位領域内における画素単位の異物の集まり具合や分散具合もしくは隣接した画素単位の異物同士の凹凸関係もしくは平坦さなどに応じて、該単位領域内の異物検出レベルの合計レベルがその異物画素数に対して相関性をもってくる。ＣＰＵ１０は、上記の散乱光測定方式における異物検出レベルの合計レベルと異物画素数の相関性に基づいて異物の形状を設定した異物形状判定テーブル１０ａ（図２（ｂ）参照）を用いて異物Ｐの形状を判定する。すなわち、ＣＰＵ１０は、メモリ９から異物検出レベルデータの総和ΣＱと検出画素数Ｎを取り込み、異物形状判定テーブル１０ａの所定の検出画素数Ｎに対応する異物検出レベルの総和ΣＱが所定のしきい値Ｒよりも小さい場合に平坦状異物と判定し、その異物検出レベルの総和ΣＱが該しきい値Ｒよりも大きい場合には塊状異物と判定する。このようにＣＰＵ１０により推定された判定処理結果は例えば異物マップやヒストグラムなどの表示方法により図示しない表示手段（例えばディスプレイユニットやプリンタなど）に表示することができる。なお、異物形状判定テーブル１０ａの特性はこれに限らない。また、異物レベル算出部８ｃでは、異物検出レベルの総和を求めたが、これに限らず、異物検出レベルの平均値を求めてもよい。その場合、異物形状判定テーブルを設けることなく、異物検出レベルの平均値とメモリから得る異物検出レベルとを単に比較するだけで異物の形状を推定もしくは判定することが可能となる。
【００１３】
上述の各実施例に示した異物検査装置Ａは、異物判定部７において、散乱光検出センサ６の検出データＤ１と比較されるチップデータに代えて、ＩＣチップの設計パターンデータや標準パターンデータを用いてもよい。また、散乱光検出センサ６としては、ラインセンサに代えて、エリアセンサまたは撮像管などを用いてもよい。また、上述の実施例ではパターン付ウェハについて記述したが、パターンなしであってもよい。
【００１４】
【発明の効果】
以上のとおり、本発明によれば、１つの単位領域内に存在する異物を１つの異物とみなしてそのサイズを推定することができるので、パターン認識などの複雑な処理を行うことなく、極めて簡単な構成で異物のサイズ（粒径）を判定もしくは推定できるという優れた効果を奏する。また、１つの単位領域内に存在する異物を１つの異物とみなしてその形状を推定することができるので、パターン認識などの複雑な処理を行うことなく、極めて簡単な構成で異物の形状を判定もしくは推定できるという優れた効果を奏する。
【図面の簡単な説明】
【図１】本発明に係る異物検査装置の一実施例を示し、（ａ）は本例の異物検査装置の概要構成を示す概略図、（ｂ）は同装置のデータ処理部のブロック図、（ｃ）はデータ処理部での異物判定データの一例を示す図。
【図２】本発明に係る異物検査装置の他の実施例を示し、（ａ）は本例の異物検査装置のデータ処理部のブロック図、（ｂ）は異物形状判定テーブルの一例を示す図。
【符号の説明】
Ａ異物検査装置
１ウェハ
３光ビーム照射手段
６散乱光検出センサ
７異物判定部
８グルーピング処理部
８ａレベル最大値検出部
８ｂ検出画素計数部
８ｃ異物レベル算出部
９メモリ
１０ＣＰＵ
１０ａ異物形状判定テーブル[0001]
BACKGROUND OF THE INVENTION
BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a foreign substance inspection apparatus and method, and more particularly to a foreign substance inspection apparatus and method for detecting a minute foreign substance on a surface to be inspected and defects such as uneven scratches and scratches with high sensitivity, for example, a semiconductor wafer (hereinafter referred to as a wafer). Concerning foreign substance inspection apparatus and method for detecting foreign matter adhering to the surface of masks, reticles, glass substrates, etc., defects such as uneven scratches and scratches, and inspecting the size (particle size), shape, etc. of the foreign matter and defects It is.
[0002]
[Prior art]
In the manufacturing process of semiconductor integrated circuits (for example, ICs), if foreign matter adheres to the wafer surface or various patterns that form semiconductor regions, insulating regions, electrodes, wiring, etc., IC performance deteriorates, so pattern formation Later, the foreign matter inspection apparatus inspects the presence or absence of foreign matter on the wafer surface.
[0003]
By the way, in order to manufacture ICs with a high yield, foreign matter adhering to the wafer surface is detected, the size (particle size) and shape of the foreign matter are inspected, and the cleanliness of various semiconductor manufacturing equipment and processes is quantified. It is necessary to grasp the situation and manage the manufacturing process properly. Conventionally, as a foreign substance inspection apparatus for inspecting the size and shape of a foreign substance, for example, there is an apparatus disclosed in Japanese Patent Laid-Open No. 11-51622.
[0004]
The conventionally known foreign matter inspection apparatus irradiates laser light obliquely on the wafer surface, detects scattered light due to unevenness of the attached foreign matter on the wafer surface, and detects the pattern on the wafer based on the detection data of the scattered light. The identity is determined, and other than the pattern is detected as a foreign object. Next, a part where a foreign object is detected is imaged by an imaging device, a foreign object image is extracted from image data obtained by the imaging device, and the size and shape of the foreign object are measured based on the extracted foreign object image. However, in the foreign matter inspection apparatus, the foreign matter portion is imaged by the imaging device after the foreign matter inspection, and the size and shape of the foreign matter are measured based on the extracted foreign matter image extracted from the image data of the imaging device. Since the inspection for the presence or absence of foreign matters on the wafer cannot be performed for the operation time, the throughput is lowered.
[0005]
[Problems to be solved by the invention]
The present invention has been made in view of the above points, and an object of the present invention is to provide a foreign substance inspection apparatus and method that can determine or estimate the size (particle size) of a foreign substance in the foreign substance inspection on the surface of an object to be inspected. . It is another object of the present invention to provide a foreign object inspection apparatus and method that can determine or estimate the shape of a foreign object when inspecting the surface of an object to be inspected.
[0006]
[Means for Solving the Problems]
The foreign matter inspection apparatus according to the present invention optically detects the state of the surface of the inspection object and outputs detection data consisting of a plurality of pixels, and determines the foreign matter on the surface of the inspection object based on the detection data. A foreign substance determination means for outputting foreign substance extraction data; a calculation means for grouping the foreign substance extraction data into unit areas each having a predetermined number of pixels and counting the number of pixels regarded as foreign substances in the group for each group; And determining means for performing determination processing for estimating the size of a foreign substance in a unit region corresponding to the group based on the number of foreign substance pixels for each group obtained by the computing means. According to this, since it is possible to estimate the size of a foreign substance existing in one unit area as one foreign substance, it is possible to estimate the size of the foreign substance with a very simple configuration without performing complicated processing such as pattern recognition. The size (particle size) can be determined or estimated.
[0007]
The present invention can be configured not only as a device invention as described above, but also as a method invention. That is, the foreign matter inspection method according to the present invention includes a step of optically detecting the state of the surface of the inspection object and outputting detection data composed of a plurality of pixels, and determining the foreign matter on the surface of the inspection object based on the detection data. A step of outputting foreign matter extraction data; a step of grouping the foreign matter extraction data into unit regions each having a predetermined number of pixels; and a step of counting the number of pixels regarded as foreign matters in the group for each group; And a step of performing a determination process for estimating the size of a foreign substance in a unit region corresponding to the group based on the number of foreign substance pixels for each group. Even in the foreign substance inspection method having such a configuration, since the size of a foreign substance existing in one unit area can be estimated as one foreign substance, and the size of the foreign substance can be estimated without performing complicated processing such as pattern recognition. Can be determined or estimated.
[0008]
The foreign matter inspection apparatus according to the present invention optically detects the state of the surface of the inspection object and outputs detection data consisting of a plurality of pixels, and the foreign matter on the surface of the inspection object based on the detection data. Foreign matter determination means for determining and outputting foreign matter extraction data, and calculation for grouping the foreign matter extraction data into unit areas each having a predetermined number of pixels, and counting the number of pixels regarded as foreign matters in the group for each group A means for calculating a sum of the foreign substance detection levels for each pixel in each unit region of the foreign substance extraction data for each group, and a correlation between the sum of the foreign substance detection level data and the number of foreign substance pixels. And determining means for estimating the shape of the foreign matter in the unit area corresponding to the group. According to this, since it is possible to estimate the shape of a foreign substance existing in one unit area as one foreign substance, it is possible to estimate the foreign substance with a very simple configuration without performing complicated processing such as pattern recognition. The shape can be determined or estimated.
[0009]
The present invention can be configured not only as a device invention as described above, but also as a method invention. That is, the foreign matter inspection method according to the present invention includes a step of optically detecting the state of the surface of the inspection object and outputting detection data composed of a plurality of pixels, and determining the foreign matter on the surface of the inspection object based on the detection data. A step of outputting foreign matter extraction data; a step of grouping the foreign matter extraction data into unit regions each having a predetermined number of pixels; and a step of counting the number of pixels regarded as foreign matters in the group for each group; Based on the step of calculating the sum of the foreign object detection levels for each pixel in each unit region of the foreign object extraction data for each group, and the correlation between the sum of the foreign object detection level data and the number of foreign object pixels, And a step of estimating the shape of the foreign matter in the corresponding unit region. Even in the foreign substance inspection method having such a configuration, since the foreign substance existing in one unit area can be regarded as one foreign substance and the shape thereof can be estimated, the foreign substance can be obtained without performing complicated processing such as pattern recognition. Can be determined or estimated.
[0010]
DETAILED DESCRIPTION OF THE INVENTION
Hereinafter, a foreign substance inspection apparatus and method according to the present invention will be described with reference to the accompanying drawings.
In FIG. 1, a foreign matter inspection apparatus A includes an XY moving mechanism 2 on which a wafer 1 is placed, a light beam irradiation means 3, a drive control means 4, a light receiving optical system 5, a scattered light detection sensor 6, and a foreign matter determination. Unit 7, grouping processing unit 8, memory 9, and CPU 10. As shown in FIG. 1A, the wafer 1 is a patterned wafer having a large number of IC chips 1 a on which a circuit pattern is formed on the surface, and is fixed on an XY table 2 a of an XY moving mechanism 2. The surface of the wafer 1 is obliquely irradiated with a spot-shaped laser beam L from a light beam irradiation unit 3 (for example, a laser beam irradiation unit) at a predetermined low angle. The XY moving mechanism 2 scans the entire region of the IC chip 1a with respect to the laser light L when the XY table 2a is moved in the X direction and the Y direction by the drive control means 4. When the laser beam L is obliquely irradiated on the surface of the wafer 1, scattered light in the dark field is generated from adhering foreign matter and a circuit pattern (not shown) on the surface of the wafer 1. Specifically, if there is an attached foreign matter or circuit pattern on the smooth surface of the wafer 1, the laser beam L is irregularly reflected and scattered by the unevenness of the attached foreign matter or circuit pattern. The scattered light irregularly reflected by the adhering foreign matter or the circuit pattern is condensed on the scattered light detection sensor 6 by a condensing lens (not shown) of the light receiving optical system 5.
[0011]
The scattered light detection sensor 6 has a large number of pixels (solid-state imaging photoelectric conversion elements) arranged in a line in the scanning direction of the laser light L (the Y direction in the illustrated example). The scattered light is received via, and digital detection data D1 composed of a predetermined plurality of pixels (for example, 8 pixels) is output to the foreign matter determination unit 7. The foreign matter determination unit 7 determines foreign matter on the wafer 1 based on the detection data D1 from the scattered light detection sensor 6, and outputs the foreign matter extraction data D2 to the grouping processing unit 8 for each pixel. That is, the detection data D1 from each pixel of the scattered light detection sensor 6 is collated with the chip data at the same position of the adjacent IC chip 1a previously captured, and when there is a mismatch, the detection data is converted into the foreign matter extraction data D2. To the grouping processing unit 8 for each pixel. That is, since the circuit pattern is the same between adjacent chips, the non-matching portion of the detection data D1 corresponds to the foreign matter, and foreign matter extraction data D2 indicating only the foreign matter from which the circuit pattern is excluded is obtained. For example, in the foreign matter extraction data, the level of a pixel that is not regarded as a foreign matter is “0”, and the pixel that is regarded as a foreign matter obtains a level corresponding to the detection level of the scattered light. In the grouping processing unit 8, the detection pixel counting unit 8b groups the foreign matter extraction data D2 from the foreign matter determination unit 7 into unit areas each having a predetermined number of pixels (for example, 8 × 8 pixels) (see FIG. 1C). For each group, the number of detected pixels N in the group (in the illustrated example, six pixels in black) is counted as the area of one foreign matter P. In the level maximum value detection unit 8a, the foreign matter detection level (luminance level) of each pixel of the foreign matter extraction data D2 for each group is compared, and the maximum value M is detected by detecting the maximum value M of the foreign matter detection level. It is regarded as luminance information of one foreign matter P. In the example of FIG. 1C, the level of each of the six pixels regarded as the foreign matter P is 3, 1, 5, 8, 4, 2, and the level “8” of the coordinates (4, 4) is the maximum value. M. The grouping processing unit 8 includes a required hardware circuit configured to execute the above-described maximum value detection process and detection pixel counting process, and executes these processes in real time, and the maximum value M (see FIG. In the example of 1 (c), “8”) and the number of detected pixels N (“6” in the example of FIG. 1C) are stored in the memory 9. The CPU 10 performs a determination process for estimating the size of the foreign matter P in the unit area corresponding to the group based on the number of detected pixels N for each group obtained by the grouping processing unit 8. That is, the CPU 10 fetches the number of detected pixels N from the memory 9, obtains the area S of the foreign matter P by the following equation (1), regards the foreign matter P as one circle as shown in the following equation (2), and calculates its radius. Find r. Note that u is an area corresponding to one pixel.
u (area of one pixel) × N (number of detected pixels) = S (1)
S = u × N≈πr ² (2)
∴r = √ [(u × N) / π]
Is calculated. For example, if u = 4 square microns, in the case of FIG. 1 (c), N = 6, so r = 2.8 microns is calculated from the above equation (2). Thus, the determination processing result estimated by the CPU 10 can be displayed on a display unit (not shown) (for example, a display unit or a printer) by a display method such as a foreign matter map or a histogram. Further, if necessary, the calculation results and inspection conditions (power of laser light L, ND (Neutral Density) filter, polarizing plate) and PLS standard particles (not shown) with known particle diameters (calibration standard particles) And the actual particle size of the foreign matter P existing on the wafer 1 is obtained. Specifically, for various types of PLS standard particles with different particle sizes, the data of the reflection intensity measured by changing the power of the laser beam L, the ND filter, the polarizing plate, etc. are stored, and the actual foreign matter inspection is performed. The actual particle size of the foreign matter P is obtained by comparison with the calculation result obtained in step (1). The ND filter and the polarizing plate are provided in the light receiving optical system 5, for example. The ND filter prevents saturation of the scattered light detection sensor 6 by appropriately adjusting the transmittance of the scattered light and appropriately attenuating the scattered light received by the scattered light detection sensor 6. The polarizing plate is used for cutting a predetermined deflection component (for example, S deflection component) included in the scattered light and allowing the scattered light detection sensor 6 to receive another deflection component (for example, P deflection component). .
[0012]
FIG. 2 shows another embodiment of the foreign matter inspection apparatus and method according to the present invention. In addition, the same code | symbol is attached | subjected to the part which is common in the foreign material inspection apparatus mentioned above, and the description is abbreviate | omitted. As shown in FIG. 2A, the foreign matter inspection apparatus A according to the present embodiment includes a foreign matter level calculation unit 8c in the grouping processing unit 8 instead of the level maximum value detection unit 8a. The foreign substance level calculation unit 8c calculates the total ΣQ of the foreign substance detection levels for each pixel of the foreign substance extraction data D2 for each group. In the example of FIG. 1C, the foreign matter detection levels of the six pixels regarded as the foreign matter P are 3, 1, 5, 8, 4 and 2, and the sum “23” of these foreign matter detection levels is the total sum. ΣQ. The grouping processing unit 8 is composed of required hardware circuits configured to execute the above-described foreign matter level calculation processing and detection pixel counting processing, and executes these processing in real time, and the total ΣQ (FIG. 1). (C) “23” in the example) and the number of detected pixels N (“6” in the example of FIG. 1C) are stored in the memory 9. The CPU 10 performs determination processing for estimating the shape of the foreign matter P in the unit region corresponding to the group based on the correlation between the total foreign matter detection level ΣQ for each group obtained by the grouping processing unit 8 and the number N of detected pixels. . In the case of the scattered light measurement method, the detection level increases as the unevenness of the foreign matter in pixel units increases, and the detection level decreases as the foreign matter is flatter. From such a tendency of the level of detection of foreign matter in units of pixels, the overall shape of foreign matter (whether it is a block shape or a flat shape) can be estimated to some extent. Also, the total level of foreign matter detection level in the unit area according to the degree of gathering or dispersion of the foreign matter in pixel units in the unit area consisting of a plurality of pixels or the unevenness or flatness of the foreign matter in adjacent pixel units Has a correlation with the number of foreign pixels. The CPU 10 uses the foreign object shape determination table 10a (see FIG. 2B) in which the shape of the foreign object is set based on the correlation between the total level of the foreign object detection level and the number of foreign object pixels in the scattered light measurement method. Determine the shape. That is, the CPU 10 fetches the total ΣQ of foreign substance detection level data and the number of detected pixels N from the memory 9, and the total ΣQ of foreign substance detection levels corresponding to the predetermined number of detected pixels N of the foreign object shape determination table 10a is a predetermined threshold value. When it is smaller than R, it is determined as a flat foreign material, and when the total ΣQ of the foreign material detection levels is larger than the threshold value R, it is determined as a massive foreign material. Thus, the determination processing result estimated by the CPU 10 can be displayed on a display unit (not shown) (for example, a display unit or a printer) by a display method such as a foreign matter map or a histogram. The characteristics of the foreign object shape determination table 10a are not limited to this. In addition, the foreign substance level calculation unit 8c calculates the total of the foreign substance detection levels. However, the present invention is not limited to this, and an average value of the foreign substance detection levels may be obtained. In this case, it is possible to estimate or determine the shape of the foreign object by simply comparing the average value of the foreign object detection level and the foreign object detection level obtained from the memory without providing a foreign object shape determination table.
[0013]
In the foreign matter inspection apparatus A shown in each of the above-described embodiments, the foreign matter determination unit 7 uses IC chip design pattern data and standard pattern data instead of the chip data to be compared with the detection data D1 of the scattered light detection sensor 6. It may be used. As the scattered light detection sensor 6, an area sensor or an imaging tube may be used instead of the line sensor. In the above-described embodiments, the patterned wafer has been described.
[0014]
【The invention's effect】
As described above, according to the present invention, it is possible to estimate the size of a foreign object existing in one unit area as a single foreign object, and thus it is extremely simple without performing complicated processing such as pattern recognition. With such a configuration, it is possible to determine or estimate the size (particle size) of the foreign matter. In addition, since the shape of a foreign object existing in one unit area can be estimated as a single foreign object, the shape of the foreign object can be estimated without complicated processing such as pattern recognition. Alternatively, it has an excellent effect that it can be estimated.
[Brief description of the drawings]
FIG. 1 shows an embodiment of a foreign substance inspection apparatus according to the present invention, (a) is a schematic diagram showing a schematic configuration of the foreign substance inspection apparatus of this example, (b) is a block diagram of a data processing unit of the apparatus, (C) is a figure which shows an example of the foreign material determination data in a data processing part.
2A and 2B show another embodiment of the foreign matter inspection apparatus according to the present invention, wherein FIG. 2A is a block diagram of a data processing unit of the foreign matter inspection apparatus of the present embodiment, and FIG. 2B is a view showing an example of a foreign matter shape determination table; .
[Explanation of symbols]
A Foreign substance inspection apparatus 1 Wafer 3 Light beam irradiation means 6 Scattered light detection sensor 7 Foreign substance determination part 8 Grouping processing part 8a Level maximum value detection part 8b Detection pixel counting part 8c Foreign substance level calculation part 9 Memory 10 CPU
10a Foreign object shape determination table

Claims

Detecting means for optically detecting the state of the surface of the object to be detected and outputting detection data comprising a plurality of pixels;
Foreign matter determination means for determining foreign matter on the surface of the inspection object based on the detection data and outputting foreign matter extraction data;
Grouping the foreign substance extracted data for each unit region composed of a predetermined number of pixels, for each group, which are the grouping, when a foreign object is present within the group, to count the number of foreign matters of pixels that are considered the foreign body Computing means;
A foreign matter inspection apparatus comprising: determination means for performing determination processing for estimating the size of foreign matter in the unit region for each group based on the number of foreign matter pixels for each group obtained by the calculation means.

Foreign substance inspection apparatus according to claim 1 comprising before further means for generating a representative foreign object detection level data in each of the unit area based on the foreign object detection level for each pixel which is regarded as the foreign matter Kigu each loop.

Detecting means for optically detecting the state of the surface of the object to be detected and outputting detection data comprising a plurality of pixels;
Foreign matter determination means for determining foreign matter on the surface of the inspection object based on the detection data and outputting foreign matter extraction data;
The foreign matter extracted data grouped into a unit for each region composed of a predetermined number of pixels, for each group, which are the grouping, when a foreign object is present within the group, counted the number of foreign matters of pixels that are considered the foreign body And a calculation means for calculating the sum of the foreign matter detection level data for each pixel regarded as the foreign matter,
A foreign matter inspection apparatus comprising: a determination unit that estimates a shape of a foreign matter in the unit region for each group based on a correlation between the sum of the foreign matter detection level data and the number of foreign matter pixels.

A step of optically detecting the state of the surface of the inspected object and outputting detection data comprising a plurality of pixels;
Determining foreign matter on the surface of the object to be inspected based on the detection data, and outputting foreign matter extraction data;
Grouping the foreign substance extracted data for each unit region composed of a predetermined number of pixels, for each group, which are the grouping, when a foreign object is present within the group, to count the number of foreign matters of pixels that are considered the foreign body Process,
Before based on the number of foreign matters of pixels per Kigu loop, particle inspection method comprising the step of performing determination processing for estimating the size of the foreign matter in the unit area for each the group.

The foreign matter inspection method according to claim 4, further comprising generating representative foreign matter detection level data in each unit region based on a foreign matter detection level for each pixel regarded as the foreign matter for each group.

A step of optically detecting the state of the surface of the inspected object and outputting detection data comprising a plurality of pixels;
Determining foreign matter on the surface of the object to be inspected based on the detection data, and outputting foreign matter extraction data;
The foreign matter extracted data grouped into a unit for each region composed of a predetermined number of pixels, for each group, which are the grouping, when a foreign object is present within the group, counted the number of foreign matters of pixels that are considered the foreign body A step of calculating a sum of foreign matter detection level data for each pixel further regarded as the foreign matter;
Wherein the sum of the foreign object detection level data based on the correlation of the number of foreign matters of pixels, particle inspection method comprising the step of estimating the shape of the foreign substance in the unit area for each the group.