JP4109495B2

JP4109495B2 - Material data identification method, formability prediction evaluation system, program, and recording medium

Info

Publication number: JP4109495B2
Application number: JP2002140725A
Authority: JP
Inventors: 俊二樋渡; 浩作潮田; 康治佐久間; 繁米村
Original assignee: Nippon Steel Corp
Current assignee: Nippon Steel Corp
Priority date: 2001-05-16
Filing date: 2002-05-15
Publication date: 2008-07-02
Anticipated expiration: 2022-05-15
Also published as: JP2003048021A

Description

【０００１】
【発明の属する技術分野】
本発明は、プレス成形に供される材料が所定の工業規格に従って指定されている場合に、材料の成形の可否を予測評価する方法、材料データの提供方法、材料データの同定方法、成形性予測評価システム、記録媒体、及びプログラムに関する。
【０００２】
【従来の技術】
従来より、自動車用鋼板などの加工用金属板の多くは、工業規格に基づいた商取引がなされている。工業規格は材料種類ごとに降伏強さ、引張強さ、伸び、更に場合によってはｒ値、穴広げ率、板厚の許容範囲を規定している。プレス成形などの塑性加工を施して用いる場合、これらの特性値を参考に適切な材料種類を選択するが、目的とする製品への加工の成否は降伏強さ、引張強さ、伸び、ｒ値、穴広げ率、板厚から、直接且つ定量的に推定できるものではない。製品形状、工程、金型、加工条件などにも影響されるため、これらを総合的に検討し最適条件を見極める必要がある。
【０００３】
そのため、有限要素法（ＦＥＭ）を用いたプレス成形性の予測評価を行い、実際のプレス加工時に安定して生産が行えるように材料が選定され、加工条件などが最適化される。
【０００４】
降伏強さ、引張強さ、伸び、ｒ値、穴広げ率は比較的簡単な機械試験により得られる割には、材料の成形性の優劣を判断する上で参考となる指標であるため、各材料種類の許容範囲はこれらで規定されることが多い。しかしながら、これらの特性値は成形シミュレーション用の材料条件として直接入力されるものではない。材料の変形挙動は降伏強さ、引張強さ、伸び、穴広げ率とは異なる別の材料パラメータを用いて表している。
【０００５】
具体的には、材料の塑性異方性は異方性降伏関数で、加工硬化特性は加工硬化曲線でそれぞれ表現される。これらにはフィッティングにより決定される材料パラメータが含まれており、材料による変形挙動の違いはこの材料パラメータの値として表される。例えば、加工硬化特性は引張試験により得られた応力−歪み曲線で知ることができるが、成形シミュレーションにおいては、これをいわゆるSwiftの式、
σ＝ｃ（ε₀＋ε_p）ⁿ
を用いて近似し、表現することが多い。この場合、材料による加工効果挙動の違いは材料パラメータｃ，ε₀，ｎの値として表現される。
【０００６】
従来では、この材料パラメータをその材料種類のなかの代表的な特性値をもつ材料から得ており、当該材料種類の成形性はこの代表的な特性値に対応する材料パラメータを用いた成形シミュレーションで予測評価していた。「代表的な特性値」とは確率的には平均値に近いものになりがちである。即ち、ある材料種類の成形可否はその許容範囲内の（平均値近傍の）ある代表値に基づき判定されているのが現状である。
【０００７】
【発明が解決しようとする課題】
大量生産による低価格化を成り立たせるため、現状の工業規格に基づく商取引では特性値が許容範囲内にあればそれを出荷しても問題ないことが前提とされている。従って、成形性を予測評価しておく段階で材料パラメータとして平均値近傍の材料に基づく値を利用すると、実際に加工に供される材料が予測評価時の材料と同等以上の成形性を示すとは限らないため、事前評価段階で予測していなかった不具合が実際の加工時に発生する危険性を伴う。
【０００８】
これを防ぐためには、その規格許容範囲内で最も成形性に劣る特性を有する材料で事前評価しておけばよい。ところが、最も成形性に劣る特性の材料を狙って製造するのは容易ではない。最も成形性に劣る材料とは伸び、ｒ値、穴広げ率が下限で、降伏強さや引張強さが上限となる材料であると考えられるが、これらの特性値の１つ以上が狙った限界値の通りになるように製造条件を制御するのは現実的には不可能に近いという問題がある。
【０００９】
そこで本発明は、プレス成形に供される材料が所定の工業規格に従って指定されている場合に、規格許容範囲内での材料のばらつきに対して安定して成形が可能であるか否かを正確に予測評価でき、事前に必要な対策を講じることで、実際の生産が開始された後の成形不具合を回避し、信頼性の高いプレス成形を容易且つ確実に実行することを可能とする成形性予測評価方法、材料データの提供方法、材料データの同定方法、成形性予測評価システム、記録媒体、及びプログラムを提供することを目的とする。
【００１０】
【課題を解決するための手段】
本発明者らは、鋭意検討の結果、以下に示す発明の諸態様に想到した。
【００１１】
本発明の材料データの同定方法は、プレス成形に供される材料が所定の工業規格に従って指定されており、前記材料の引張試験により得られた第１の応力−歪み曲線を用いて、前記材料の成形の可否を決定するための要素である複数の指標である降伏強さ、引張り強さ及び伸びのうち、少なくとも１つが前記工業規格の許容範囲内の限界値と一致するように、前記第１の応力−歪み曲線を圧縮及び拡大して第２の応力−歪み曲線に変換し、当該第２の応力−歪み曲線の曲線に基づいて材料パラメータを同定する。
本発明の材料データの同定方法は、プレス成形に供される材料の材料パラメータを同定するに際して、前記材料の引張試験により得られた第１の応力−歪み曲線を用いて、前記材料の成形の可否を決定するための要素である複数の指標である降伏強さ、引張り強さ及び伸びのうち、少なくとも１つが前記材料の品質ばらつきの分布から算出した限界値と一致するように、前記第１の応力−歪み曲線を圧縮及び拡大して第２の応力−歪み曲線に変換し、当該第２の応力−歪み曲線の曲線に基づいて材料パラメータを同定する。
本発明の材料データの同定方法の一態様では、前記分布が正規分布であり、前記品質ばらつきの平均値をμ、標準偏差をσ、ｋを０以上の実数として、前記限界値をμ±ｋσとする。
本発明の材料データの同定方法は、プレス成形に供される材料の材料パラメータを同定するに際して、前記材料の引張試験により得られた第１の応力−歪み曲線を用いて、前記材料の成形の可否を決定するための要素である複数の指標である降伏強さ、引張り強さ及び伸びのうち、少なくとも１つが、工業規格の許容範囲内の第１の限界値又は前記材料の品質ばらつきの分布から算出した第２の限界値のいずれか厳格な値と一致するように、前記第１の応力−歪み曲線を圧縮及び拡大して第２の応力−歪み曲線に変換し、当該第２の応力−歪み曲線の曲線に基づいて材料パラメータを同定する。
本発明の材料データの同定方法の一態様では、前記分布が正規分布であり、前記品質ばらつきの平均値をμ、標準偏差をσ、ｋを０以上の実数として、前記第２の限界値をμ±ｋσとする。
本発明の材料データの同定方法の一態様では、前記指標値が前記材料の伸びであり、当該伸びが前記限界値として下限値に一致するように、前記第１の応力−歪み曲線を前記第２の応力−歪み曲線に変換する。
本発明の材料データの同定方法の一態様では、前記指標値が、前記伸びに加えて前記材料の降伏強さ又は引張り強さであり、当該伸びが前記限界値として下限値に一致するとともに、前記降伏強さ又は引張り強さが前記限界値として上限値に一致するように、前記第１の応力−歪み曲線を前記第２の応力−歪み曲線に変換する。
本発明の材料データの同定方法の一態様では、前記材料の引張試験に供された前記材料のうちから代表材を選定するに際して、複数の前記指標をそれぞれ所定の基準値を用いて規格化してこれらをベクトル化し、規格化された前記指標の値が異なる複数の材料の平均ベクトルを算出し、複数の規格化された前記指標が張るベクトル空間において前記平均ベクトルとの距離が最も近いベクトルで表される材料を前記代表材とする。
本発明の材料データの同定方法は、プレス成形に供される材料が所定の工業規格に従って指定されており、前記材料の引張試験により得られた公称応力−公称歪み曲線を、公称歪み値から弾性歪み値を減算することにより、公称応力−公称塑性歪み曲線に変換する第１のステップと、前記公称応力−公称塑性歪み曲線を公称塑性歪み方向にａ倍（但し、前記材料の伸びをｅ_bとし、前記工業規格の許容範囲内の伸びの下限値をｅ_b ¹とすると、ａ＝ｅ_b ¹／ｅ_bである。）する第２のステップと、得られた曲線の一様伸び以下の範囲のデータを真応力−真塑性歪み曲線に変換し、必要な材料パラメータを所定のフィッティングにより算出する第３のステップとを含む。
本発明の材料データの同定方法の一態様では、前記第１のステップの後、前記第２のステップの前に、前記公称応力−公称塑性歪み曲線を公称応力方向にｋ倍（但し、前記材料の降伏強さをｓ_y、前記工業規格の許容範囲内の降伏強さの上限値をｓ_y ^uとすると、ｋ＝ｓ_y ^u／ｓ_yである。）する第４のステップを更に含む。
本発明の材料データの同定方法の一態様では、前記第２のステップの後、前記第３のステップの前に、前記公称応力−公称塑性歪み曲線を公称応力方向にｋ倍（但し、前記材料の降伏強さをｓ_y、前記工業規格の許容範囲内の降伏強さの上限値をｓ_y ^uとすると、ｋ＝ｓ_y ^u／ｓ_yである。）する第４のステップを更に含む。
本発明の材料データの同定方法は、プレス成形に供される材料の材料パラメータを同定するに際して、前記材料の引張試験により得られた公称応力−公称歪み曲線を、公称歪み値から弾性歪み値を減算することにより、公称応力−公称塑性歪み曲線に変換する第１のステップと、前記公称応力−公称塑性歪み曲線を公称塑性歪み方向にａ倍（但し、前記材料の伸びをｅ_bとし、前記材料の品質ばらつきの分布から算出した伸びの下限値をｅ_b ¹とすると、ａ＝ｅ_b ¹／ｅ_bである。）する第２のステップと、得られた曲線の一様伸び以下の範囲のデータを真応力−真塑性歪み曲線に変換し、必要な材料パラメータを所定のフィッティングにより算出する第３のステップとを含む。
本発明の材料データの同定方法の一態様では、前記第１のステップの後、前記第２のステップの前に、前記公称応力−公称塑性歪み曲線を公称応力方向にｋ倍（但し、前記材料の降伏強さをｓ_y、前記材料の品質ばらつきの分布から算出した降伏強さの上限値をｓ_y ^uとすると、ｋ＝ｓ_y ^u／ｓ_yである。）する第４のステップを更に含む。
本発明の材料データの同定方法の一態様では、前記第２のステップの後、前記第３のステップの前に、前記公称応力−公称塑性歪み曲線を公称応力方向にｋ倍（但し、前記材料の降伏強さをｓ_y、前記材料の品質ばらつきの分布から算出した降伏強さの上限値をｓ_y ^uとすると、ｋ＝ｓ_y ^u／ｓ_yである。）する第４のステップを更に含む。
本発明の材料データの同定方法の一態様では、前記分布が正規分布であり、前記品質ばらつきの平均値をμ、標準偏差をσ、ｋを０以上の実数として、前記下限値をμ−ｋσ、前記上限値をμ＋ｋσとする。
本発明の材料データの同定方法は、プレス成形に供される材料の材料パラメータを同定するに際して、前記材料の引張試験により得られた公称応力−公称歪み曲線を、公称歪み値から弾性歪み値を減算することにより、公称応力−公称塑性歪み曲線に変換する第１のステップと、前記公称応力−公称塑性歪み曲線を公称塑性歪み方向にａ倍（但し、前記材料の伸びをｅ_bとし、工業規格の許容範囲内の伸びの下限値又は前記材料の品質ばらつきの分布から算出した伸びの下限値のうち、いずれか大きい値をｅ_b ¹とすると、ａ＝ｅ_b ¹／ｅ_bである。）する第２のステップと、得られた曲線の一様伸び以下の範囲のデータを真応力−真塑性歪み曲線に変換し、必要な材料パラメータを所定のフィッティングにより算出する第３のステップとを含む。
本発明の材料データの同定方法の一態様では、前記第１のステップの後、前記第２のステップの前に、前記公称応力−公称塑性歪み曲線を公称応力方向にｋ倍（但し、前記材料の降伏強さをｓ_y、前記工業規格の許容範囲内の降伏強さの第１の上限値又は前記材料の品質ばらつきの分布から算出した降伏強さの第２の上限値のうち、いずれか小さい値をｓ_y ^uとすると、ｋ＝ｓ_y ^u／ｓ_yである。）する第４のステップを更に含む。
本発明の材料データの同定方法の一態様では、前記第２のステップの後、前記第３のステップの前に、前記公称応力−公称塑性歪み曲線を公称応力方向にｋ倍（但し、前記材料の降伏強さをｓ_y、前記工業規格の許容範囲内の降伏強さの第１の上限値又は前記材料の品質ばらつきの分布から算出した降伏強さの第２の上限値のうち、いずれか小さい値をｓ_y ^uとすると、ｋ＝ｓ_y ^u／ｓ_yである。）する第４のステップを更に含む。
本発明の材料データの同定方法の一態様では、前記分布が正規分布であり、前記品質ばらつきの平均値をμ、標準偏差をσ、ｋを０以上の実数として、前記第２の下限値をμ−ｋσ、前記第２の上限値をμ＋ｋσとする。
本発明の材料データの同定方法の一態様では、前記材料の引張試験に供された前記材料のうちから代表材を選定するに際して、複数の前記指標をそれぞれ所定の基準値を用いて規格化してこれらをベクトル化し、規格化された前記指標の値が異なる複数の材料の平均ベクトルを算出し、複数の規格化された前記指標が張るベクトル空間において前記平均ベクトルとの距離が最も近いベクトルで表される材料を前記代表材とする。
本発明の成形性予測評価システムは、プレス成形に供される材料が所定の工業規格に従って指定されており、前記材料の成形の可否を予測評価するシステムであって、前記材料の引張試験により得られた第１の応力−歪み曲線を用いて、前記材料の成形の可否を決定するための要素である複数の指標値である降伏強さ、引張り強さ及び伸びのうち、少なくとも１つが前記工業規格の許容範囲内の限界値と一致するように、前記第１の応力−歪み曲線を圧縮及び拡大して第２の応力−歪み曲線に変換する手段と、前記第２の応力−歪み曲線の曲線に基づいて材料パラメータを同定し、当該材料パラメータを用いて前記材料の成形の可否を予測評価する手段とを含む。
本発明の成形性予測評価システムは、プレス成形に供される材料の成形の可否を予測評価するシステムであって、前記材料の引張試験により得られた第１の応力−歪み曲線を用いて、前記材料の成形の可否を決定するための要素である複数の指標値である降伏強さ、引張り強さ及び伸びのうち、少なくとも１つが前記材料の品質ばらつきの分布から算出した限界値と一致するように、前記第１の応力−歪み曲線を圧縮及び拡大して第２の応力−歪み曲線に変換する手段と、前記第２の応力−歪み曲線の曲線に基づいて材料パラメータを同定し、当該材料パラメータを用いて前記材料の成形の可否を予測評価する手段とを含む。
本発明の成形性予測評価システムの一態様では、前記分布が正規分布であり、前記品質ばらつきの平均値をμ、標準偏差をσ、ｋを０以上の実数として、前記限界値をμ±ｋσとする。
本発明の成形性予測評価システムは、プレス成形に供される材料が所定の工業規格に従って指定されており、前記材料の成形の可否を予測評価するシステムであって、前記材料の引張試験により得られた第１の応力−歪み曲線を用いて、前記材料の成形の可否を決定するための要素である複数の指標値のうち、少なくとも１つが前記工業規格の許容範囲内の第１の限界値又は前記材料の品質ばらつきの分布から算出した第２の限界値のうち、いずれか厳格な値と一致するように、前記第１の応力−歪み曲線を圧縮及び拡大して第２の応力−歪み曲線に変換する手段と、前記第２の応力−歪み曲線の曲線に基づいて材料パラメータを同定し、当該材料パラメータを用いて前記材料の成形の可否を予測評価する手段とを含む。
本発明の成形性予測評価システムの一態様では、前記分布が正規分布であり、前記品質ばらつきの平均値をμ、標準偏差をσ、ｋを０以上の実数として、前記第２の限界値をμ±ｋσとする。
本発明の成形性予測評価システムの一態様では、前記複数の指標値が、前記材料の伸びであり、前記限界値として下限値となる。
本発明の成形性予測評価システムの一態様では、前記複数の指標値が、前記材料の伸びに加え、前記材料の降伏強さ及び引張り強さであり、前記降伏強さ及び引張り強さのうちの少なくとも１つが前記限界値として上限値となる。
本発明の成形性予測評価システムの一態様では、前記材料の成形可否の予測評価を行い、その結果を製品設計に反映させる。
本発明の成形性予測評価システムの一態様では、前記材料の引張試験に供された前記材料のうちから代表材を選定するに際して、前記複数の指標を有する代表材を選定する手段を含み、前記代表材を選定する手段は、複数の前記指標をそれぞれ所定の基準値を用いて規格化してこれらをベクトル化し、規格化された前記指標の値が異なる複数の材料の平均ベクトルを算出し、複数の規格化された前記指標が張るベクトル空間において前記平均ベクトルとの距離が最も近いベクトルで表される材料を前記代表材とする。
本発明の成形性予測評価システムは、プレス成形に供される材料が所定の工業規格に従って指定されており、前記材料の成形の可否を予測評価するシステムであって、前記材料の引張試験により得られた公称応力−公称歪み曲線を、公称歪み値から弾性歪み値を減算することにより、公称応力−公称塑性歪み曲線に変換する手段と、前記公称応力−公称塑性歪み曲線を公称塑性歪み方向にａ倍（但し、前記材料の伸びをｅ_bとし、前記工業規格の許容範囲内の伸びの下限値をｅ_b ¹とすると、ａ＝ｅ_b ¹／ｅ_bである。）する手段と、得られた曲線の一様伸び以下の範囲のデータを真応力−真塑性歪み曲線に変換し、必要な材料パラメータを所定のフィッティングにより算出する手段とを含む。
本発明の成形性予測評価システムの一態様では、前記公称応力−公称塑性歪み曲線を公称応力方向にｋ倍（但し、前記材料の降伏強さをｓ_y、前記工業規格の許容範囲内の降伏強さの上限値をｓ_y ^uとすると、ｋ＝ｓ_y ^u／ｓ_yである。）する手段を更に含む。
本発明の成形性予測評価システムの一態様では、前記材料の成形可否の予測評価を行い、その結果を製品設計に反映させる。
本発明の成形性予測評価システムは、プレス成形に供される材料の成形の可否を予測評価するシステムであって、前記材料の引張試験により得られた公称応力−公称歪み曲線を、公称歪み値から弾性歪み値を減算することにより、公称応力−公称塑性歪み曲線に変換する手段と、前記公称応力−公称塑性歪み曲線を公称塑性歪み方向にａ倍（但し、前記材料の伸びをｅ_bとし、前記材料の品質ばらつきの分布から算出した伸びの下限値をｅ_b ¹とすると、ａ＝ｅ_b ¹／ｅ_bである。）する手段と、得られた曲線の一様伸び以下の範囲のデータを真応力−真塑性歪み曲線に変換し、必要な材料パラメータを所定のフィッティングにより算出する手段とを含む。
本発明の成形性予測評価システムの一態様では、前記公称応力−公称塑性歪み曲線を公称応力方向にｋ倍（但し、前記材料の降伏強さをｓ_y、前記材料の品質ばらつきの分布から算出した降伏強さの上限値をｓ_y ^uとすると、ｋ＝ｓ_y ^u／ｓ_yである。）する手段を更に含む。
本発明の成形性予測評価システムの一態様では、前記材料の成形可否の予測評価を行い、その結果を製品設計に反映させる。
本発明の成形性予測評価システムの一態様では、前記分布が正規分布であり、前記品質ばらつきの平均値をμ、標準偏差をσ、ｋを０以上の実数として、前記下限値をμ−ｋσ、前記上限値をμ＋ｋσとする。
本発明の成形性予測評価システムは、プレス成形に供される材料が所定の工業規格に従って指定されており、前記材料の成形の可否を予測評価するシステムであって、前記材料の引張試験により得られた公称応力−公称歪み曲線を、公称歪み値から弾性歪み値を減算することにより、公称応力−公称塑性歪み曲線に変換する手段と、前記公称応力−公称塑性歪み曲線を公称塑性歪み方向にａ倍（但し、前記材料の伸びをｅ_bとし、前記工業規格の許容範囲内の伸びの第１の下限値又は前記材料の品質ばらつきの分布から算出した伸びの第２の下限値のうち、いずれか大きい値をｅ_b ¹とすると、ａ＝ｅ_b ¹／ｅ_bである。）する手段と、得られた曲線の一様伸び以下の範囲のデータを真応力−真塑性歪み曲線に変換し、必要な材料パラメータを所定のフィッティングにより算出する手段とを含む。
本発明の成形性予測評価システムの一態様では、前記公称応力−公称塑性歪み曲線を公称応力方向にｋ倍（但し、前記材料の降伏強さをｓ_y、前記材料の品質ばらつきの分布から算出した降伏強さの第１の上限値又は前記材料の品質ばらつきの分布から算出した伸びの第２の上限値のうち、いずれか小さい値をｓ_y ^uとすると、ｋ＝ｓ_y ^u／ｓ_yである。）する手段を更に含む。
本発明の成形性予測評価システムの一態様では、前記材料の成形可否の予測評価を行い、その結果を製品設計に反映させる。
本発明の成形性予測評価システムの一態様では、前記分布が正規分布であり、前記品質ばらつきの平均値をμ、標準偏差をσ、ｋを０以上の実数として、前記第２の下限値をμ−ｋσ、前記第２の上限値をμ＋ｋσとする。
本発明の成形性予測評価システムの一態様では、前記材料の引張試験に供された前記材料のうちから代表材を選定するに際して、複数の前記指標をそれぞれ所定の基準値を用いて規格化してこれらをベクトル化し、規格化された前記指標の値が異なる複数の材料の平均ベクトルを算出し、複数の規格化された前記指標が張るベクトル空間において前記平均ベクトルとの距離が最も近いベクトルで表される材料を前記代表材とする。
本発明のプログラムは、プレス成形に供される材料が所定の工業規格に従って指定されており、前記材料の引張試験により得られた公称応力−公称歪み曲線を、公称歪み値から弾性歪み値を減算することにより、公称応力−公称塑性歪み曲線に変換する第１のステップと、前記公称応力−公称塑性歪み曲線を公称塑性歪み方向にａ倍（但し、前記材料の伸びをｅ_bとし、前記工業規格の許容範囲内の伸びの下限値をｅ_b ¹とすると、ａ＝ｅ_b ¹／ｅ_bである。）する第２のステップと、得られた曲線の一様伸び以下の範囲のデータを真応力−真塑性歪み曲線に変換し、必要な材料パラメータを所定のフィッティングにより算出する第３のステップとをコンピュータに実行させるためのものである。
本発明のプログラムは、プレス成形に供される材料の材料パラメータを同定するに際して、前記材料の引張試験により得られた公称応力−公称歪み曲線を、公称歪み値から弾性歪み値を減算することにより、公称応力−公称塑性歪み曲線に変換する第１のステップと、前記公称応力−公称塑性歪み曲線を公称塑性歪み方向にａ倍（但し、前記材料の伸びをｅ_bとし、前記材料の品質ばらつきの分布から算出した伸びの下限値をｅ_b ¹とすると、ａ＝ｅ_b ¹／ｅ_bである。）する第２のステップと、得られた曲線の一様伸び以下の範囲のデータを真応力−真塑性歪み曲線に変換し、必要な材料パラメータを所定のフィッティングにより算出する第３のステップとをコンピュータに実行させるためのものである。
本発明のプログラムは、プレス成形に供される材料の材料パラメータを同定するに際して、前記材料の引張試験により得られた公称応力−公称歪み曲線を、公称歪み値から弾性歪み値を減算することにより、公称応力−公称塑性歪み曲線に変換する第１のステップと、前記公称応力−公称塑性歪み曲線を公称塑性歪み方向にａ倍（但し、前記材料の伸びをｅ_bとし、工業規格の許容範囲内の伸びの下限値又は前記材料の品質ばらつきの分布から算出した伸びの下限値のうち、いずれか大きい値をｅ_b ¹とすると、ａ＝ｅ_b ¹／ｅ_bである。）する第２のステップと、得られた曲線の一様伸び以下の範囲のデータを真応力−真塑性歪み曲線に変換し、必要な材料パラメータを所定のフィッティングにより算出する第３のステップとをコンピュータに実行させるためのものである。
本発明の記録媒体は、前記プログラムを記録したコンピュータ読み取り可能なものである。
【００８２】
【発明の実施の形態】
以下、本発明を鋼板の成形に適用した具体的な実施形態について説明する。なお、本発明の対象は鋼板の成形に限定されるものではなく、例えばアルミニウム合金やマグネシウム合金などの金属板や、材料の種類や厚みの異なる金属板を溶接などの方法で接続して得られる金属板（テーラードブランク）の成形等に適用しても好適である。
【００８３】
−本発明の原理的説明−
初めに、本発明の主要原理について説明する。
【００８４】
プレス成形に供される材料が所定の工業規格に従って指定されている場合に、材料の伸び、穴広げ率は、一般に延性を表現する特性と考えられ、これが小さいほど、加工中の破断が生じ易い。ｒ値は深絞り性を表す特性であり、これが小さいほど、破断、若しくは、しわが生じ易い。また、板厚が小さいほど、破断、若しくは、しわやスプリングバックによる形状不良が発生し易い。従って、前記工業規格にてこれらの許容範囲が定められているときは、当該許容範囲内の限界値として下限値を用いることで、安全性の評価を行うことができる。
【００８５】
他方、材料の降伏強さや引張強さが高いと、しわやスプリングバックによる形状不良が発生し易いことが知られている。従って、前記工業規格にてこれらの許容範囲が定められているときは、当該許容範囲内の限界値として上限値を用いることで、安全性の評価を行うことができる。
【００８６】
以上のことから、伸び、ｒ値、穴広げ率、板厚は前記許容範囲の下限値、降伏強さ、引張り強さは前記許容範囲の上限値となるような総合特性を有した材料パラメータが最も安全側の評価を与える。
【００８７】
現在、一般に用いられている成形シミュレーション用ソフトではｒ値、板厚は、直接、その値を入力する。穴広げ率は有限要素計算に直接必要ではなく、シミュレーション結果をもとに破断判定を行うときに用いる。他方、伸び、降伏強さ、引張り強さは一般には材料パラメータとして直接入力するわけではない。これらの替わりに、材料の真応力−真塑性歪みの関係を表す材料パラメータを入力する。
【００８８】
具体的には、前述のSwiftの式の材料パラメータｃ，ε₀，ｎを用いられることが多い。
σ＝ｃ（ε₀＋ε_p）ⁿ
ここで、σとε_pはそれぞれ真応力と真塑性歪みに対応するものである。あるいは、有限要素法ソフトウェアによっては真応力−真塑性歪み曲線を近似する折れ線を入力するものもある。この場合、加工硬化率が高い領域ほど短い折れ線を用いたほうが近似の精度が高い。いずれにせよ、真応力−真塑性歪み曲線にフィッティングして求めるので、成形性が下限となる材料の真応力−真塑性歪み曲線を知る必要がある。
【００８９】
上述の場合、工業規格を利用する替わりに、材料の品質ばらつきの分布から伸び、ｒ値、穴広げ率、板厚としては下限値、降伏強さ、引張り強さとしては上限値を算出するようにしても良い。具体的には、前記分布として正規分布を用い、品質ばらつきの平均値をμ、標準偏差をσ、ｋを０以上の実数として、下限値をμ−ｋσ、上限値をμ＋ｋσすることが好適である。このようにして、実際に起こり得る状況に限定した安全予測を行うようにする。
【００９０】
また、工業規格と材料の品質ばらつきの分布とを併用しても良い。この場合、先ず工業規格の許容範囲内における伸び、ｒ値、穴広げ率、板厚を第１の下限値とし、降伏強さ、引張り強さを第１の上限値とする。他方、材料の品質ばらつきの分布から算出した伸び、ｒ値、穴広げ率、板厚を第２の下限値とし、降伏強さ、引張り強さを第２の上限値とする。そして、限界値として厳格な値、即ち下限値としては第１の下限値と第２の下限値のうち大きい方の値を、上限値としては第１の上限値と第２の上限値のうち小さい方の値を採用する。これにより、より正確で安全な成形の可否の基準を得ることが可能となる。
【００９１】
−具体的な諸実施例−
以下、本発明の具体的な諸実施例として、成形性予測評価システムを用いた評価方法を示す。
【００９２】
（実施例１）
上述のような真応力−真塑性歪み曲線を有する材料を確保し、実験を行うのは困難であるため、シミュレーションで推定することが必要である。この推定方法の具体的なアルゴリズムを図１に示す。この場合、▲１▼公称応力−公称塑性歪みの状態で変換するため、降伏強さ、引張り強さ、伸びが所定の条件を満足しているか否かの確認が容易であり、▲２▼塑性歪みと応力とを独立に取り扱えるため変換則の決定が簡単である、という利点がある。
【００９３】
図２は、表１に示す工業規格の各種鋼板のうち、ＪＳＣ２７０Ｅという種類の材料として取引された鋼板を引張り試験に供して得られた公称応力−公称歪み曲線を示す特性図である。この材料の特性は表２に示す通りである。
【００９４】
【表１】

【００９５】
【表２】

【００９６】
ここで、本例のように指標が多変数である場合には、前記引張り試験に供された鋼板のうちから最適な代表材を選定するため、以下のような手法を用いることが好適である。
【００９７】
図３に示すように、例えば本例のように指標が、降伏強さ、引張り強さ、伸び、ｒ値（ｒ０，ｒ４５，ｒ９０）などである場合、先ず当該システムの手段１１により、鋼材ごとにこれら指標の生データを取得する（ステップ１１）。続いて、図４に示すように、手段１２により、各指標をそれぞれ所定の基準値、例えば各指標のそれぞれの平均値を用いて規格化した後、鋼材（の材質）ごとに規格化したこれら指標をベクトル化し（図４では図示の都合上、指標として降伏強さと引張り強さのみを示す。ここでは便宜上、規格化していない指標値を示している。）、鋼材ごとの平均値μ、標準偏差σを算出する（ステップ１２）。そして、手段１３により、規格化したこれら指標が張るベクトル空間において、平均値との距離が最も近いベクトルで表される鋼材を代表材として選定する（ステップ１３）。この選定法により、簡易且つ正確に所望の代表材の指標を得ることができる。
【００９８】
鋼材の前記工業規格によると、ＪＳＣ２７０Ｅのｒ値の下限は１．４であり、板厚の下限値は０．７１ｍｍである。これらは直接、成形シミュレーションに入力する材料パラメータである。一方、伸びの下限値は４３％であり、降伏強さの上限値は１９５ＭＰａであるが、これらは、加工硬化曲線を示す材料パラメータとして入力される。
【００９９】
そこで、本発明に従って以下のようにして成形性下限材の材料パラメータを推定する。
なお、以下の例では、指標として伸び及び降伏強さを例示するが、上記のように指標には伸び及び降伏強さ以外に引張り強さ等があり、この引張り強さは、降伏強さに代えて、変換の際に合わせこむ値として用いることができる。図２には、ｓ_uを与える公称伸び値である均一伸び（一様伸び）を指標として規定する工業規格が示されている。なお公知のように、伸びには均一伸びと全伸びとがある。
先ず、図１のステップ１において、当該システムの手段１により、公称応力−公称歪み曲線を公称応力−公称塑性歪み曲線（第１の応力−歪み曲線）に変換する。具体的には、図５に示すように、公称歪みから弾性歪みを除去した残りが公称塑性歪みである。
【０１００】
次に、ステップ２において、手段２により、鋼材の伸びが下限値に一致するように、公称応力−公称塑性歪み曲線を水平方向に圧縮（ａ倍（但し、前記材料の伸びをｅ_bとし、前記工業規格の許容範囲内の伸びの下限値をｅ_b ¹とすると、ａ＝ｅ_b ¹／ｅ_bである。））する。具体的には、図５に示すように、４３／５２．５倍する。
【０１０１】
次に、ステップ３において、手段３により、鋼材の降伏強さが上限に一致するよう、上述のように水平方向に圧縮した公称応力−公称塑性歪み曲線を垂直方向に拡大（ｋ倍（但し、前記材料の降伏強さをｓ_y、前記工業規格の許容範囲内の降伏強さの上限値をｓ_y ^uとすると、ｋ＝ｓ_y ^u／ｓ_yである。））する。具体的には、図５に示すように、１９５／１３５倍する。
【０１０２】
そして、ステップ４において、手段４により、このようにして得られた公称応力−公称塑性歪み曲線（第２の応力−歪み曲線）を真応力−真塑性歪み曲線に変換する。
【０１０３】
更に、図６に示すように、ステップ５において、手段５により、成形シミュレーションで用いる関数にフィッティングして材料パラメータを決定する。その結果として得られた材料パラメータの値を、もととなるデータから求めた材料パラメータの値と共に表２で比較する。表２では、指標である降伏強さ、引張り強さ、伸び、ｒ値及び板厚（ｔ）と、材料パラメータであるｃ，ε ₀ ，ｎとを併記しており、これらが材料データとなる。
【０１０４】
ここで、もとの材料試験データから求めた材料パラメータ（代表材）と、推定された下限値を満たす材料パラメータ（下限材）とを用いて、成形シミュレーションを行った実験について述べる。
【０１０５】
代表材の結果を図７に、下限材の結果を図８にそれぞれ示す。代表材の材料パラメータでは、プレス成形時の破断の危険性が高いFailure領域は見られない。他方、下限材の材料パラメータでは、２箇所にFailure領域が現れた。このことから、規格の許容範囲内であっても下限データに近ければ破断の危険性が高いことがわかる。この種類の材料で安定して生産するには、上記の破断の危険性を回避するような製品形状に修正することが望ましい。あるいは、材料の種類を変更し、下限材が来ても破断が生じない材料を用いる必要がある。
【０１０６】
以上のように、実施例１によれば、規格許容範囲内での材料のばらつきに対して安定して成形が可能であるか否かを予測評価でき、事前に必要な対策を講じることで、実際の生産が開始された後の成形不具合を回避することが容易となる。
【０１０７】
（実施例２）
実施例２では、工業規格を用いる替わりに、品質ばらつきの分布から各指標の下限値や上限値を算出する。
具体的には、先ず実施例１と同様に、図３のステップ１１〜１３により、前記引張り試験に供された鋼板のうちから最適な代表材を選定する。そして、鋼材の品質ばらつきについて図９のような正規分布を仮定し、伸び、ｒ値、穴広げ率、板厚については下限値としてμ−３σを、降伏強さ、引張り強さについては上限値としてμ＋３σをそれぞれ採用する。例えば、図９の例（ＪＳＣ２７０Ｆ）のように指標が降伏強さであれば上限値をμ＋３σ＝１５７．３ＭＰａとする。
【０１０８】
しかる後、図１のステップ１〜５により、鋼材の成形の可否を判断する。
【０１０９】
以上のように、実施例２によれば、品質ばらつきに正規分布を仮定することにより、安定して成形が可能であるか否かを予測評価でき、事前に必要な対策を講じることで、実際の生産が開始された後の成形不具合を回避することが容易となる。
【０１１０】
（実施例３）
実施例３では、工業規格に加えて、品質ばらつきの分布を併せて考慮し、各指標の下限値や上限値を算出する。
具体的には、先ず実施例１と同様に、図３のステップ１１〜１３により、前記引張り試験に供された鋼板のうちから最適な代表材を選定する。続いて、表１に示すような工業規格を利用して伸び、ｒ値、穴広げ率、板厚については下限値（第１の下限値）を、降伏強さ、引張り強さについては上限値（第１の上限値）を用いる。これに加えて、鋼材の品質ばらつきについて図１０のような正規分布を仮定し、伸び、ｒ値、穴広げ率、板厚については下限値（第２の下限値）としてμ−３σを、降伏強さ、引張り強さについては上限値（第２の上限値）としてμ＋３σをそれぞれ採用する。
【０１１１】
そして、限界値として厳格な方の値、即ち下限値については第１の下限値とと第２の下限値とで大きい値、上限値については第１の上限値と第２の上限値とで小さい値を採用する。図１０の例（ＪＳＣ２７０Ｆ）のように指標が降伏強さであれば、第１の上限値が１７５ＭＰａ、第２の上限値が１５７．３ＭＰａであることから、より小さい第２の上限値を採用する。
【０１１２】
しかる後、図１のステップ１〜５により、鋼材の成形の可否を判断する。
【０１１３】
以上のように、実施例３によれば、工業規格と品質ばらつきの正規分布とを併用し、より安定して成形が可能であるか否かを予測評価でき、事前に必要な対策を講じることで、実際の生産が開始された後の成形不具合を回避することが容易となる。
【０１１４】
なお、本発明による評価システムを構成する各機構、及び図１や図３に示した本発明による評価方法を構成する各ステップは、コンピュータのＲＡＭやＲＯＭなどに記憶されたプログラムが動作することによって実現できる。このプログラム及び当該プログラムを記録したコンピュータ読み取り可能な記録媒体は本発明の実施形態に含まれる。
【０１１５】
具体的に、前記プログラムは、例えばＣＤ−ＲＯＭのような記録媒体に記録し、或いは各種伝送媒体を介し、コンピュータに提供される。前記プログラムを記録する記録媒体としては、ＣＤ−ＲＯＭ以外に、フレキシブルディスク、ハードディスク、磁気テープ、光磁気ディスク、不揮発性メモリカード等を用いることができる。他方、上記プログラムの伝送媒体としては、プログラム情報を搬送波として伝搬させて供給するためのコンピュータネットワーク（ＬＡＮ、インターネットの等のＷＡＮ、無線通信ネットワーク等）システムにおける通信媒体（光ファイバ等の有線回線や無線回線等）を用いることができる。
【０１１６】
また、コンピュータが供給されたプログラムを実行することにより上述の実施形態の機能が実現されるだけでなく、そのプログラムがコンピュータにおいて稼働しているＯＳ（オペレーティングシステム）あるいは他のアプリケーションソフト等と共同して上述の実施形態の機能が実現される場合や、供給されたプログラムの処理の全てあるいは一部がコンピュータの機能拡張ボードや機能拡張ユニットにより行われて上述の実施形態の機能が実現される場合も、かかるプログラムは本発明の実施形態に含まれる。
【０１１７】
例えば、図１１は、一般的なパーソナルユーザ端末装置の内部構成を示す模式図である。この図１１において、１２００はコンピュータＰＣである。ＰＣ１２００は、ＣＰＵ１２０１を備え、ＲＯＭ１２０２またはハードディスク（ＨＤ）１２１１に記憶された、あるいはフレキシブルディスクドライブ（ＦＤ）１２１２より供給されるデバイス制御ソフトウェアを実行し、システムバス１２０４に接続される各デバイスを総括的に制御する。
【０１１８】
上記ＰＣ１２００のＣＰＵ１２０１、ＲＯＭ１２０２またはハードディスク（ＨＤ）１２１１に記憶されたプログラムにより、本実施形態の手段１〜５等の各手段の機能や、ステップ１〜５等の手順が実現される。
【０１１９】
１２０３はＲＡＭで、ＣＰＵ１２０１の主メモリ、ワークエリア等として機能する。１２０５はキーボードコントローラ（ＫＢＣ）で、キーボード（ＫＢ）１２０９や不図示のデバイス等からの指示入力を制御する。
【０１２０】
１２０６はＣＲＴコントローラ（ＣＲＴＣ）で、ＣＲＴディスプレイ（ＣＲＴ）１２１０の表示を制御する。１２０７はディスクコントローラ（ＤＫＣ）で、ブートプログラム（起動プログラム：パソコンのハードやソフトの実行（動作）を開始するプログラム）、複数のアプリケーション、編集ファイル、ユーザファイルそしてネットワーク管理プログラム等を記憶するハードディスク（ＨＤ）１２１１、及びフレキシブルディスク（ＦＤ）１２１２とのアクセスを制御する。
【０１２１】
１２０８はネットワークインタフエースカード（ＮＩＣ）で、ＬＡＮ１２２０を介して、ネットワークプリンタ、他のネットワーク機器、あるいは他のＰＣと双方向のデータのやり取りを行う。
【０１２２】
【発明の効果】
本発明によれば、材料のプレス成形における可否を判断するに際して、最も加工性に劣る限界値となる材料パラメータを推定し、これを用いて成形性の予測評価を行うことにより、規格許容範囲内での材料のばらつきに対して安定して成形が可能であるか否かを正確に予測評価でき、事前に必要な対策を講じることで、実際の生産が開始された後の成形不具合を回避し、信頼性の高いプレス成形を容易且つ確実に実行することが可能となる。
【０１２３】
具体的には、主にプレス成形に供される材料が所定の工業規格に従って指定されている場合を想定しているが、当該工業規格を参酌しない場合でも、充分に信頼性の高い成形可否の判断が可能となる。
【図面の簡単な説明】
【図１】成形性予測評価方法の具体的なアルゴリズムを示すフロー図である。
【図２】鋼板を引張り試験に供して得られた公称応力−公称歪み曲線を示す特性図である。
【図３】引張り試験に供された鋼板のうちから最適な代表材を選定する方法を示すフロー図である。
【図４】降伏強さと引張り強さを例として、各指標をベクトル化した様子を示すベクトル空間図である。
【図５】公称応力−公称塑性歪み曲線を示す特性図である。
【図６】成形シミュレーションに供される鋼板の真応力−真塑性歪み曲線を示す特性図である。
【図７】成形シミュレーションの実験において、代表材の材料パラメータについての結果を示す特性図である。
【図８】成形シミュレーションの実験において、下限材の材料パラメータについての結果を示す特性図である。
【図９】実施例２において、品質ばらつきの正規分布を示す特性図である。
【図１０】実施例３において、品質ばらつきの正規分布を示す特性図である。
【図１１】一般的なパーソナルユーザ端末装置の内部構成を示す模式図である。[0001]
BACKGROUND OF THE INVENTION
The present invention relates to a method for predicting and evaluating whether or not a material can be formed, a method for providing material data, a method for identifying material data, and a formability prediction when a material to be subjected to press forming is specified in accordance with a predetermined industrial standard. The present invention relates to an evaluation system, a recording medium, and a program.
[0002]
[Prior art]
Conventionally, most of processing metal plates such as automotive steel plates have been subjected to commercial transactions based on industrial standards. The industry standard prescribes yield strength, tensile strength, elongation, and, in some cases, acceptable ranges of r value, hole expansion rate, and plate thickness for each material type. When plastic processing such as press forming is used, an appropriate material type is selected with reference to these characteristic values. Yield strength, tensile strength, elongation, r value are the success or failure of processing the target product. It cannot be directly and quantitatively estimated from the hole expansion rate and the plate thickness. Since it is also affected by product shape, process, mold, processing conditions, etc., it is necessary to comprehensively consider these and determine the optimum conditions.
[0003]
Therefore, predictive evaluation of press formability using a finite element method (FEM) is performed, and materials are selected so that stable production can be performed at the time of actual pressing, and processing conditions and the like are optimized.
[0004]
  Yield strength, tensile strength, elongation, r value, and hole expansion ratio are indices that can be used as reference for judging the superiority or inferiority of the formability of materials, although they are obtained by relatively simple mechanical tests. In many cases, the allowable range of the material type is defined by these. However, these characteristic values are not directly input as material conditions for molding simulation. The deformation behavior of the material is different from the yield strength, tensile strength, elongation, and hole expansion rate.materialThis is expressed using parameters.
[0005]
  Specifically, the plastic anisotropy of the material is expressed by an anisotropic yield function, and the work hardening characteristic is expressed by a work hardening curve. These are fittingsMaterial determined byParameters are included, and the difference in deformation behavior depending on the materialmaterialExpressed as a parameter value. For example, the work hardening characteristics can be known from the stress-strain curve obtained by the tensile test, but in the molding simulation, this is expressed by the so-called Swift equation,
  σ = c (ε₀+ Ε_p)ⁿ
Is often approximated and expressed using. In this case, the difference in processing effect behavior depending on the material ismaterialParameters c and ε₀, N.
[0006]
  Conventionally, thismaterialThe parameter is obtained from a material having a representative characteristic value of the material type, and the formability of the material type corresponds to the representative characteristic value.materialPredictive evaluation was performed by forming simulation using parameters. The “typical characteristic value” tends to be close to the average value stochastically. That is, at present, whether or not a certain material type can be molded is determined based on a certain representative value (near the average value) within the allowable range.
[0007]
[Problems to be solved by the invention]
In order to realize a low price by mass production, it is assumed that there is no problem even if the characteristic value is within the allowable range in the commercial transaction based on the current industrial standard. Therefore, if a value based on a material in the vicinity of the average value is used as a material parameter at the stage of predictive evaluation of formability, the material actually used for processing exhibits a formability equal to or higher than the material at the time of predictive evaluation. However, there is a risk that defects that were not predicted in the preliminary evaluation stage may occur during actual machining.
[0008]
In order to prevent this, it is sufficient to pre-evaluate with a material having characteristics that are the most inferior in formability within the standard allowable range. However, it is not easy to manufacture with a material having the most inferior formability. The most inferior formable material is considered to be the material whose elongation, r value, and hole expansion ratio are the lower limit, and the yield strength and tensile strength are the upper limit. However, one or more of these characteristic values are the limits targeted. There is a problem that it is practically impossible to control the manufacturing conditions so as to be in accordance with the values.
[0009]
Therefore, the present invention accurately determines whether or not molding can be stably performed with respect to variations in materials within a standard allowable range when a material to be subjected to press molding is specified in accordance with a predetermined industrial standard. Formability that makes it possible to perform reliable and reliable press forming easily and reliably by taking necessary measures in advance to avoid forming defects after actual production has started. It is an object of the present invention to provide a prediction evaluation method, a material data providing method, a material data identification method, a formability prediction evaluation system, a recording medium, and a program.
[0010]
[Means for Solving the Problems]
As a result of intensive studies, the inventors have arrived at the following aspects of the invention.
[0011]
  In the material data identification method of the present invention, a material to be subjected to press molding is designated according to a predetermined industrial standard, and the material is used by using a first stress-strain curve obtained by a tensile test of the material. Multiple indicators that are factors for determining whether or not molding is possibleYield strength, tensile strength and elongation areThe first stress-strain curve is compressed and expanded to be converted into a second stress-strain curve so that at least one of the values matches a limit value within an allowable range of the industry standard, and the second stress-strain curve is converted. The material parameters are identified based on the stress-strain curve.
  The material data identification method of the present invention uses a first stress-strain curve obtained by a tensile test of the material when identifying the material parameters of the material to be subjected to press forming, and Multiple indicators that are elements for determining availabilityYield strength, tensile strength and elongation areThe first stress-strain curve is compressed and expanded to be converted into a second stress-strain curve so that at least one of them matches the limit value calculated from the distribution of quality variations of the material, Material parameters are identified based on the curve of the second stress-strain curve.
  In one aspect of the material data identification method of the present invention, the distribution is a normal distribution, the average value of the quality variation is μ, the standard deviation is σ, k is a real number of 0 or more, and the limit value is μ ± kσ. And
  The material data identification method of the present invention uses a first stress-strain curve obtained by a tensile test of the material when identifying the material parameters of the material to be subjected to press forming, and Multiple indicators that are elements for determining availabilityYield strength, tensile strength and elongation areAmong the first limit value and the second limit value calculated from the distribution of the quality variation of the material. The stress-strain curve is compressed and expanded to be converted into a second stress-strain curve, and material parameters are identified based on the curve of the second stress-strain curve.
  In one aspect of the material data identification method of the present invention, the distribution is a normal distribution, the average value of the quality variation is μ, the standard deviation is σ, k is a real number greater than or equal to 0, and the second limit value is set. Let μ ± kσ.
  In one aspect of the material data identification method of the present invention, the first stress-strain curve is the first stress-strain curve so that the index value is elongation of the material and the elongation matches the lower limit value as the limit value. Convert to a stress-strain curve of 2.
  In one aspect of the material data identification method of the present invention, the index value is the yield strength or tensile strength of the material in addition to the elongation, and the elongation matches the lower limit as the limit value, The first stress-strain curve is converted into the second stress-strain curve so that the yield strength or tensile strength matches the upper limit value as the limit value.
  In one aspect of the material data identification method of the present invention, when selecting a representative material from the materials subjected to the tensile test of the material, a plurality of the indicators are normalized using predetermined reference values, respectively. These are vectorized, an average vector of a plurality of materials having different standardized index values is calculated, and represented by a vector having the closest distance to the average vector in a vector space spanned by the plurality of standardized indices. The material to be used is the representative material.
  In the material data identification method of the present invention, a material to be subjected to press forming is designated according to a predetermined industry standard, and a nominal stress-nominal strain curve obtained by a tensile test of the material is elasticized from a nominal strain value. A first step of converting the nominal stress-nominal plastic strain curve by subtracting the strain value; and a.times.the nominal stress-nominal plastic strain curve in the nominal plastic strain direction (where e is the elongation of the material e_bAnd the lower limit of elongation within the allowable range of the industrial standard is e_b ¹Then a = e_b ¹/ E_bIt is. And a third step of converting the data in a range equal to or less than the uniform elongation of the obtained curve into a true stress-true plastic strain curve and calculating necessary material parameters by a predetermined fitting. Including.
  In one aspect of the material data identification method of the present invention, after the first step and before the second step, the nominal stress-nominal plastic strain curve is multiplied by k times in the nominal stress direction (however, the material Yield strength of s_y, The upper limit of yield strength within the allowable range of the industrial standard_y ^uThen k = s_y ^u/ S_yIt is. ).
  In one aspect of the material data identification method of the present invention, after the second step and before the third step, the nominal stress-nominal plastic strain curve is multiplied by k times in the nominal stress direction (however, the material Yield strength of s_y, The upper limit of yield strength within the allowable range of the industrial standard_y ^uThen k = s_y ^u/ S_yIt is. ).
  In the material data identification method of the present invention, when identifying the material parameters of the material to be subjected to press forming, the nominal stress-nominal strain curve obtained by the tensile test of the material is converted from the nominal strain value to the elastic strain value. A first step of subtracting to convert to a nominal stress-nominal plastic strain curve, and the nominal stress-nominal plastic strain curve is multiplied by a in the nominal plastic strain direction (where the elongation of the material is e_bAnd the lower limit of elongation calculated from the distribution of quality variations of the material is e_b ¹Then a = e_b ¹/ E_bIt is. And a third step of converting the data in a range equal to or less than the uniform elongation of the obtained curve into a true stress-true plastic strain curve and calculating necessary material parameters by a predetermined fitting. Including.
  In one aspect of the material data identification method of the present invention, after the first step and before the second step, the nominal stress-nominal plastic strain curve is multiplied by k times in the nominal stress direction (however, the material Yield strength of s_y, The upper limit of yield strength calculated from the distribution of quality variations of the material_y ^uThen k = s_y ^u/ S_yIt is. ).
  In one aspect of the material data identification method of the present invention, after the second step and before the third step, the nominal stress-nominal plastic strain curve is multiplied by k times in the nominal stress direction (however, the material Yield strength of s_y, The upper limit of yield strength calculated from the distribution of quality variations of the material_y ^uThen k = s_y ^u/ S_yIt is. ).
  In one aspect of the material data identification method of the present invention, the distribution is a normal distribution, the average value of the quality variation is μ, the standard deviation is σ, k is a real number greater than or equal to 0, and the lower limit value is μ−kσ. The upper limit value is μ + kσ.
  In the material data identification method of the present invention, when identifying the material parameters of the material to be subjected to press forming, the nominal stress-nominal strain curve obtained by the tensile test of the material is converted from the nominal strain value to the elastic strain value. A first step of subtracting to convert to a nominal stress-nominal plastic strain curve, and the nominal stress-nominal plastic strain curve is multiplied by a in the nominal plastic strain direction (where the elongation of the material is e_bAnd the larger value of the lower limit value of the elongation within the allowable range of the industry standard or the lower limit value of the elongation calculated from the distribution of the quality variation of the material._b ¹Then a = e_b ¹/ E_bIt is. And a third step of converting the data in a range equal to or less than the uniform elongation of the obtained curve into a true stress-true plastic strain curve and calculating necessary material parameters by a predetermined fitting. Including.
  In one aspect of the material data identification method of the present invention, after the first step and before the second step, the nominal stress-nominal plastic strain curve is multiplied by k times in the nominal stress direction (however, the material Yield strength of s_yThe smaller value of the first upper limit value of the yield strength within the allowable range of the industry standard or the second upper limit value of the yield strength calculated from the distribution of the quality variation of the material is s._y ^uThen k = s_y ^u/ S_yIt is. ).
  In one aspect of the material data identification method of the present invention, after the second step and before the third step, the nominal stress-nominal plastic strain curve is multiplied by k times in the nominal stress direction (however, the material Yield strength of s_yThe smaller value of the first upper limit value of the yield strength within the allowable range of the industry standard or the second upper limit value of the yield strength calculated from the distribution of the quality variation of the material is s._y ^uThen k = s_y ^u/ S_yIt is. ).
  In one aspect of the material data identification method of the present invention, the distribution is a normal distribution, the average value of the quality variation is μ, the standard deviation is σ, k is a real number greater than or equal to 0, and the second lower limit value is Let μ−kσ and the second upper limit be μ + kσ.
  In one aspect of the material data identification method of the present invention, when selecting a representative material from the materials subjected to a tensile test of the material, a plurality of the indicators are normalized using predetermined reference values, respectively. These are vectorized, an average vector of a plurality of materials having different standardized index values is calculated, and represented by a vector that is closest to the average vector in a vector space spanned by the plurality of standardized indices. The material to be used is the representative material.
  The formability prediction and evaluation system of the present invention is a system for predicting and evaluating whether or not a material to be subjected to press forming is specified in accordance with a predetermined industrial standard, and whether or not the material can be formed. A plurality of index values that are elements for determining whether or not the material can be molded using the first stress-strain curve obtainedYield strength, tensile strength and elongation areMeans for compressing and expanding the first stress-strain curve to convert it into a second stress-strain curve so that at least one of them matches a limit value within an acceptable range of the industry standard; Means for identifying a material parameter based on the curve of the second stress-strain curve and predicting and evaluating whether or not the material can be molded using the material parameter.
  The formability prediction evaluation system of the present invention is a system that predicts and evaluates whether or not a material to be subjected to press forming can be formed, using a first stress-strain curve obtained by a tensile test of the material, A plurality of index values that are elements for determining whether or not the material can be moldedYield strength, tensile strength and elongation areMeans for compressing and expanding the first stress-strain curve to convert it into a second stress-strain curve so that at least one of them matches a limit value calculated from the distribution of quality variations of the material; Means for identifying a material parameter based on the curve of the second stress-strain curve and predicting and evaluating whether or not the material can be molded using the material parameter.
  In one aspect of the moldability prediction evaluation system of the present invention, the distribution is a normal distribution, the average value of the quality variation is μ, the standard deviation is σ, k is a real number of 0 or more, and the limit value is μ ± kσ. And
  The formability prediction and evaluation system of the present invention is a system for predicting and evaluating whether or not a material to be subjected to press forming is specified in accordance with a predetermined industrial standard, and whether or not the material can be formed. Of the plurality of index values, which are elements for determining whether or not the material can be molded, using the first stress-strain curve obtained, at least one is a first limit value within an allowable range of the industry standard. Alternatively, the first stress-strain curve is compressed and expanded so as to coincide with any one of the second limit values calculated from the distribution of quality variations of the material, so that the second stress-strain Means for converting to a curve; and means for identifying a material parameter based on the curve of the second stress-strain curve and predicting and evaluating whether or not the material can be molded using the material parameter.
  In one aspect of the moldability prediction evaluation system of the present invention, the distribution is a normal distribution, the average value of the quality variation is μ, the standard deviation is σ, k is a real number greater than or equal to 0, and the second limit value is set. Let μ ± kσ.
  In one aspect of the formability prediction evaluation system of the present invention, the plurality of index values areElongation, saidIt becomes the lower limit as the limit value.
  In one aspect of the formability prediction evaluation system of the present invention, the plurality of index values areIn addition to growth, Yield strength and tensile strength of the material, and at least one of the yield strength and tensile strength is the upper limit value as the limit value.
  In one aspect of the formability prediction / evaluation system of the present invention, prediction evaluation of whether or not the material can be formed is performed, and the result is reflected in product design.
  In one aspect of the formability prediction evaluation system of the present invention, when selecting a representative material from the materials subjected to a tensile test of the material, including means for selecting a representative material having the plurality of indices, The means for selecting a representative material normalizes each of the plurality of indices using a predetermined reference value, vectorizes them, calculates an average vector of a plurality of materials having different standardized index values, A material represented by a vector having the closest distance to the average vector in the vector space spanned by the standardized index is defined as the representative material.
  The formability prediction and evaluation system of the present invention is a system for predicting and evaluating whether or not a material to be subjected to press forming is specified in accordance with a predetermined industrial standard, and whether or not the material can be formed. Means for converting the obtained nominal stress-nominal strain curve to a nominal stress-nominal plastic strain curve by subtracting the elastic strain value from the nominal strain value, and the nominal stress-nominal plastic strain curve in the nominal plastic strain direction. a times (however, the elongation of the material is e_bAnd the lower limit of elongation within the allowable range of the industrial standard is e_b ¹Then a = e_b ¹/ E_bIt is. And means for converting data within a range equal to or less than the uniform elongation of the obtained curve into a true stress-true plastic strain curve and calculating necessary material parameters by a predetermined fitting.
  In one aspect of the formability prediction evaluation system of the present invention, the nominal stress-nominal plastic strain curve is multiplied by k times in the nominal stress direction (provided that the yield strength of the material is s_y, The upper limit of yield strength within the allowable range of the industrial standard_y ^uThen k = s_y ^u/ S_yIt is. And further includes means for
  In one aspect of the formability prediction / evaluation system of the present invention, prediction evaluation of whether or not the material can be formed is performed, and the result is reflected in product design.
  The formability prediction and evaluation system of the present invention predicts and evaluates whether or not a material to be subjected to press forming can be formed. A nominal stress-nominal strain curve obtained by a tensile test of the material is expressed as a nominal strain value. Means for converting the nominal stress-nominal plastic strain curve to a nominal stress-nominal plastic strain curve by subtracting the elastic strain value from_bAnd the lower limit of elongation calculated from the distribution of quality variations of the material is e_b ¹Then a = e_b ¹/ E_bIt is. And means for converting data within a range equal to or less than the uniform elongation of the obtained curve into a true stress-true plastic strain curve and calculating necessary material parameters by a predetermined fitting.
  In one aspect of the formability prediction evaluation system of the present invention, the nominal stress-nominal plastic strain curve is multiplied by k times in the nominal stress direction (provided that the yield strength of the material is s_y, The upper limit of yield strength calculated from the distribution of quality variations of the material_y ^uThen k = s_y ^u/ S_yIt is. And further includes means for
  In one aspect of the formability prediction / evaluation system of the present invention, prediction evaluation of whether or not the material can be formed is performed, and the result is reflected in product design.
  In one aspect of the moldability prediction evaluation system of the present invention, the distribution is a normal distribution, the average value of the quality variation is μ, the standard deviation is σ, k is a real number greater than or equal to 0, and the lower limit value is μ−kσ. The upper limit value is μ + kσ.
  The formability prediction and evaluation system of the present invention is a system for predicting and evaluating whether or not a material to be subjected to press forming is specified in accordance with a predetermined industrial standard, and whether or not the material can be formed. Means for converting the obtained nominal stress-nominal strain curve to a nominal stress-nominal plastic strain curve by subtracting the elastic strain value from the nominal strain value, and the nominal stress-nominal plastic strain curve in the nominal plastic strain direction. a times (however, the elongation of the material is e_bAnd the larger one of the first lower limit value of the elongation within the allowable range of the industry standard or the second lower limit value of the elongation calculated from the distribution of the quality variation of the material._b ¹Then a = e_b ¹/ E_bIt is. And means for converting data within a range equal to or less than the uniform elongation of the obtained curve into a true stress-true plastic strain curve and calculating necessary material parameters by a predetermined fitting.
  In one aspect of the formability prediction evaluation system of the present invention, the nominal stress-nominal plastic strain curve is multiplied by k times in the nominal stress direction (provided that the yield strength of the material is s_yThe smaller one of the first upper limit value of yield strength calculated from the distribution of quality variations of the material and the second upper limit value of elongation calculated from the distribution of quality variations of the material is s._y ^uThen k = s_y ^u/ S_yIt is. And further includes means for
  In one aspect of the formability prediction / evaluation system of the present invention, prediction evaluation of whether or not the material can be formed is performed, and the result is reflected in product design.
  In one aspect of the moldability prediction evaluation system of the present invention, the distribution is a normal distribution, the average value of the quality variation is μ, the standard deviation is σ, k is a real number greater than or equal to 0, and the second lower limit value is Let μ−kσ and the second upper limit be μ + kσ.
  In one aspect of the formability prediction evaluation system of the present invention, when selecting a representative material from the materials subjected to a tensile test of the material, a plurality of the indicators are normalized using predetermined reference values, respectively. These are vectorized, an average vector of a plurality of materials having different standardized index values is calculated, and represented by a vector having the closest distance to the average vector in a vector space spanned by the plurality of standardized indices. The material to be used is the representative material.
  According to the program of the present invention, a material to be subjected to press forming is specified according to a predetermined industry standard, and a nominal stress-nominal strain curve obtained by a tensile test of the material is subtracted from an elastic strain value from the nominal strain value. A first step of converting the nominal stress-nominal plastic strain curve into a nominal plastic strain direction by a times (where the elongation of the material is e_bAnd the lower limit of elongation within the allowable range of the industrial standard is e_b ¹Then a = e_b ¹/ E_bIt is. And a third step of converting the data in a range equal to or less than the uniform elongation of the obtained curve into a true stress-true plastic strain curve and calculating necessary material parameters by a predetermined fitting. It is intended to be executed by a computer.
  In identifying the material parameters of the material to be subjected to press forming, the program of the present invention subtracts the elastic strain value from the nominal strain value of the nominal stress-nominal strain curve obtained by the tensile test of the material. A first step of converting into a nominal stress-nominal plastic strain curve; and a step of multiplying the nominal stress-nominal plastic strain curve by a times in the direction of the nominal plastic strain (provided that the elongation of the material is e_bAnd the lower limit of elongation calculated from the distribution of quality variations of the material is e_b ¹Then a = e_b ¹/ E_bIt is. And a third step of converting the data in a range equal to or less than the uniform elongation of the obtained curve into a true stress-true plastic strain curve and calculating necessary material parameters by a predetermined fitting. It is intended to be executed by a computer.
  In identifying the material parameters of the material to be subjected to press forming, the program of the present invention subtracts the elastic strain value from the nominal strain value of the nominal stress-nominal strain curve obtained by the tensile test of the material. A first step of converting into a nominal stress-nominal plastic strain curve; and a step of multiplying the nominal stress-nominal plastic strain curve by a times in the direction of the nominal plastic strain (provided that the elongation of the material is e_bAnd the larger value of the lower limit value of the elongation within the allowable range of the industry standard or the lower limit value of the elongation calculated from the distribution of the quality variation of the material._b ¹Then a = e_b ¹/ E_bIt is. And a third step of converting the data in a range equal to or less than the uniform elongation of the obtained curve into a true stress-true plastic strain curve and calculating necessary material parameters by a predetermined fitting. It is intended to be executed by a computer.
  The recording medium of the present invention is a computer-readable medium on which the program is recorded.
[0082]
DETAILED DESCRIPTION OF THE INVENTION
Hereinafter, specific embodiments in which the present invention is applied to the forming of steel sheets will be described. The subject of the present invention is not limited to the forming of a steel sheet, and can be obtained by, for example, connecting metal plates such as aluminum alloy and magnesium alloy, or metal plates having different types and thicknesses by a method such as welding. The present invention is also suitable for forming a metal plate (tailored blank).
[0083]
-Principle of the present invention-
First, the main principle of the present invention will be described.
[0084]
When the material to be used for press molding is specified in accordance with a predetermined industry standard, the elongation and hole expansion ratio of the material are generally considered to express ductility, and the smaller this is, the easier it is to break during processing. . The r value is a characteristic representing deep drawability. The smaller this value is, the easier it is to break or wrinkle. In addition, the smaller the plate thickness, the easier it is to cause breakage or shape defects due to wrinkles or springback. Therefore, when these allowable ranges are defined in the industrial standard, safety evaluation can be performed by using the lower limit value as the limit value within the allowable range.
[0085]
On the other hand, it is known that when the yield strength and tensile strength of a material are high, shape defects are likely to occur due to wrinkles and springback. Therefore, when these allowable ranges are defined in the industrial standard, safety can be evaluated by using an upper limit value as a limit value within the allowable range.
[0086]
  From the above, the elongation, the r value, the hole expansion ratio, and the plate thickness had the overall characteristics that the lower limit value of the allowable range, the yield strength, and the tensile strength were the upper limit value of the allowable range.Material parametersGives the safest evaluation.
[0087]
  Currently, the r value and the plate thickness are directly input in the molding simulation software generally used. The hole expansion ratio is not directly required for the finite element calculation, and is used when determining the fracture based on the simulation result. On the other hand, elongation, yield strength and tensile strength are generallymaterialThey are not entered directly as parameters. Instead of these, it expresses the relationship between true stress and true plastic strain of the material.materialEnter the parameters.
[0088]
  Specifically, the above Swift equationmaterialParameters c and ε₀, N are often used.
  σ = c (ε₀+ Ε_p)ⁿ
  Where σ and ε_pAre true stress and true plastic strain, respectively.Corresponding. Alternatively, some finite element method software inputs a polygonal line that approximates a true stress-true plastic strain curve. In this case, the approximation accuracy is higher when the shorter broken line is used in the region where the work hardening rate is higher. In any case, since it is obtained by fitting to a true stress-true plastic strain curve, it is necessary to know the true stress-true plastic strain curve of the material whose formability is the lower limit.
[0089]
In the above case, instead of using the industry standard, the lower limit value, the yield strength, and the upper limit value are calculated as the elongation, r value, hole expansion ratio, and plate thickness from the distribution of quality variation of the material. Anyway. Specifically, it is preferable that a normal distribution is used as the distribution, the average value of quality variation is μ, the standard deviation is σ, k is a real number of 0 or more, the lower limit is μ−kσ, and the upper limit is μ + kσ. is there. In this way, safety prediction is limited to situations that can actually occur.
[0090]
Moreover, you may use together an industry standard and distribution of the quality dispersion | variation in material. In this case, first, the elongation, r value, hole expansion rate, and plate thickness within the allowable range of the industry standard are set as the first lower limit value, and the yield strength and tensile strength are set as the first upper limit value. On the other hand, the elongation, the r value, the hole expansion ratio, and the plate thickness calculated from the distribution of quality variations of the material are set as the second lower limit value, and the yield strength and the tensile strength are set as the second upper limit value. And, a strict value as the limit value, that is, the lower limit value is the larger one of the first lower limit value and the second lower limit value, and the upper limit value is the first upper limit value or the second upper limit value. Use the smaller value. As a result, it is possible to obtain a more accurate and safe standard for molding.
[0091]
-Specific examples-
Hereinafter, as specific embodiments of the present invention, an evaluation method using a formability prediction evaluation system will be described.
[0092]
Example 1
Since it is difficult to secure a material having the above-described true stress-true plastic strain curve and perform an experiment, it is necessary to estimate it by simulation. A specific algorithm of this estimation method is shown in FIG. In this case, since it is converted in the state of (1) nominal stress-nominal plastic strain, it is easy to confirm whether the yield strength, tensile strength, and elongation satisfy predetermined conditions, and (2) plasticity Since strain and stress can be handled independently, there is an advantage that determination of a conversion rule is easy.
[0093]
FIG. 2 is a characteristic diagram showing a nominal stress-nominal strain curve obtained by subjecting a steel plate traded as a type of material called JSC270E to a tensile test among various steel plates of the industry standard shown in Table 1. The properties of this material are shown in Table 2.
[0094]
[Table 1]

[0095]
[Table 2]

[0096]
Here, when the index is multivariable as in this example, it is preferable to use the following method in order to select an optimal representative material from among the steel plates subjected to the tensile test. .
[0097]
As shown in FIG. 3, for example, when the indicators are yield strength, tensile strength, elongation, r value (r0, r45, r90), etc. The raw data of these indexes is acquired (step 11). Subsequently, as shown in FIG. 4, each index is standardized by means 12 using a predetermined reference value, for example, an average value of each index, and then standardized for each steel material. The index is vectorized (in FIG. 4, for the sake of illustration, only the yield strength and the tensile strength are shown as the index. Here, for the sake of convenience, the index value is not standardized), the average value μ for each steel material, the standard The deviation σ is calculated (step 12). And the steel material represented by the vector with the shortest distance with an average value is selected as a representative material by the means 13 in the vector space which these standardized indexes extend (step 13). By this selection method, an index of a desired representative material can be obtained easily and accurately.
[0098]
  According to the industrial standard for steel materials, the lower limit of the r value of JSC270E is 1.4, and the lower limit of the plate thickness is 0.71 mm. These are entered directly into the molding simulationmaterialIt is a parameter. On the other hand, the lower limit of elongation is 43% and the upper limit of yield strength is 195 MPa, which shows a work hardening curve.materialInput as a parameter.
[0099]
  Therefore, according to the present invention, the lower limit of the formability material is as follows.materialEstimate the parameters.
  In the following examples, elongation and yield strength are exemplified as indices, but as described above, the indices include other than elongation and yield strength.Tensile strength, etc.This tensile strength can be used as a value to be adjusted in the conversion instead of the yield strength. In FIG._uThe industry standard which prescribes | regulates as a parameter | index the uniform elongation (uniform elongation) which is a nominal elongation value which gives is shown.As is well known, there are uniform elongation and total elongation.
  First, in step 1 of FIG. 1, the nominal stress-nominal strain curve is converted into a nominal stress-nominal plastic strain curve (first stress-strain curve) by means 1 of the system. Specifically, as shown in FIG. 5, the remainder obtained by removing the elastic strain from the nominal strain is the nominal plastic strain.
[0100]
Next, in step 2, the means 2 compresses the nominal stress-nominal plastic strain curve in the horizontal direction so that the elongation of the steel material matches the lower limit (a times (however, the elongation of the material e_bAnd the lower limit of elongation within the allowable range of the industrial standard is e_b ¹Then a = e_b ¹/ E_bIt is. )) Specifically, as shown in FIG.
[0101]
Next, in step 3, the nominal stress-nominal plastic strain curve compressed in the horizontal direction as described above is expanded in the vertical direction by means 3 so that the yield strength of the steel material matches the upper limit (k times (however, The yield strength of the material is s_y, The upper limit of yield strength within the allowable range of the industrial standard_y ^uThen k = s_y ^u/ S_yIt is. )) Specifically, as shown in FIG.
[0102]
  In step 4, the nominal stress-nominal plastic strain curve thus obtained by means 4 is obtained.(Second stress-strain curve)Is converted into a true stress-true plastic strain curve.
[0103]
  Furthermore,As shown in FIG.In step 5, the material parameter is determined by means 5 by fitting to a function used in the molding simulation. The material parameter value obtained as a result of this calculation is taken as the material parameter value obtained from the original data.bothTable 2 compares.In Table 2, the yield strength, tensile strength, elongation, r value, and plate thickness (t) as indexes, and c and ε as material parameters are shown. ₀ , N are written together, and these become material data.
[0104]
Here, an experiment in which a molding simulation was performed using the material parameters (representative material) obtained from the original material test data and the material parameters (lower limit material) satisfying the estimated lower limit value will be described.
[0105]
The result of the representative material is shown in FIG. 7, and the result of the lower limit material is shown in FIG. In the material parameters of the representative material, there is no failure region where there is a high risk of breakage during press molding. On the other hand, in the material parameter of the lower limit material, Failure regions appeared in two places. From this, it can be seen that even within the allowable range of the standard, the risk of breakage is high if it is close to the lower limit data. In order to stably produce this kind of material, it is desirable to modify the product shape so as to avoid the risk of breakage. Or it is necessary to change the kind of material and to use the material which does not fracture even if the lower limit material comes.
[0106]
As described above, according to Example 1, it is possible to predict and evaluate whether or not molding can be stably performed with respect to variations in materials within the allowable range of standards, and by taking necessary measures in advance, It becomes easy to avoid molding defects after actual production is started.
[0107]
(Example 2)
In the second embodiment, instead of using the industry standard, the lower limit value and the upper limit value of each index are calculated from the distribution of quality variations.
Specifically, as in Example 1, first, an optimal representative material is selected from the steel sheets subjected to the tensile test in Steps 11 to 13 in FIG. Assuming a normal distribution as shown in FIG. 9 for the quality variation of the steel material, μ-3σ is set as the lower limit for the elongation, r value, hole expansion rate, and plate thickness, and the upper limit is set for the yield strength and tensile strength. Μ + 3σ is adopted as For example, if the index is yield strength as in the example of FIG. 9 (JSC270F), the upper limit value is μ + 3σ = 157.3 MPa.
[0108]
Thereafter, whether or not the steel material can be formed is determined in steps 1 to 5 in FIG.
[0109]
As described above, according to the second embodiment, it is possible to predict and evaluate whether or not stable molding is possible by assuming a normal distribution for quality variation, and by actually taking necessary measures in advance, It becomes easy to avoid molding defects after the production of is started.
[0110]
(Example 3)
In Example 3, in addition to the industrial standards, the distribution of quality variation is also taken into consideration, and the lower limit value and the upper limit value of each index are calculated.
Specifically, as in Example 1, first, an optimal representative material is selected from the steel sheets subjected to the tensile test in Steps 11 to 13 in FIG. Subsequently, the lower limit value (first lower limit value) is set for elongation, r value, hole expansion rate, and plate thickness, and the upper limit value is obtained for yield strength and tensile strength using industrial standards as shown in Table 1. (First upper limit value) is used. In addition to this, assuming a normal distribution as shown in FIG. 10 for the quality variation of the steel material, the elongation, the r value, the hole expansion rate, and the plate thickness are expressed as μ-3σ as a lower limit (second lower limit), yield. For the strength and tensile strength, μ + 3σ is adopted as the upper limit (second upper limit).
[0111]
Then, the stricter value as the limit value, that is, the lower limit value is a larger value between the first lower limit value and the second lower limit value, and the upper limit value is determined by the first upper limit value and the second upper limit value. Use a smaller value. If the index is the yield strength as in the example of FIG. 10 (JSC270F), the first upper limit value is 175 MPa and the second upper limit value is 157.3 MPa, so a smaller second upper limit value is adopted. To do.
[0112]
Thereafter, whether or not the steel material can be formed is determined in steps 1 to 5 in FIG.
[0113]
As described above, according to Example 3, it is possible to predict and evaluate whether or not molding can be performed more stably by using industrial standards and a normal distribution of quality variations, and take necessary measures in advance. Thus, it becomes easy to avoid molding defects after actual production is started.
[0114]
Each mechanism constituting the evaluation system according to the present invention and each step constituting the evaluation method according to the present invention shown in FIGS. 1 and 3 are performed by operating a program stored in a RAM or ROM of a computer. realizable. This program and a computer-readable recording medium recording the program are included in the embodiment of the present invention.
[0115]
Specifically, the program is recorded on a recording medium such as a CD-ROM or provided to a computer via various transmission media. As a recording medium for recording the program, besides a CD-ROM, a flexible disk, a hard disk, a magnetic tape, a magneto-optical disk, a nonvolatile memory card, or the like can be used. On the other hand, the transmission medium of the program is a communication medium (wired line such as an optical fiber) or the like in a computer network (LAN, WAN such as the Internet, wireless communication network, etc.) system for propagating and supplying program information as a carrier wave. A wireless line or the like.
[0116]
In addition, the functions of the above-described embodiments are realized by executing a program supplied by a computer, and the program is used in cooperation with an OS (operating system) or other application software running on the computer. When the functions of the above-described embodiment are realized, or when all or part of the processing of the supplied program is performed by a function expansion board or a function expansion unit of the computer, the function of the above-described embodiment is realized. Such a program is included in the embodiment of the present invention.
[0117]
For example, FIG. 11 is a schematic diagram illustrating an internal configuration of a general personal user terminal device. In FIG. 11, reference numeral 1200 denotes a computer PC. The PC 1200 includes a CPU 1201, executes device control software stored in the ROM 1202 or the hard disk (HD) 1211, or supplied from the flexible disk drive (FD) 1212. To control.
[0118]
The functions stored in the CPU 1201 of the PC 1200, the ROM 1202, or the hard disk (HD) 1211 realize the functions of the respective means such as the means 1 to 5 in the present embodiment and the procedures such as steps 1 to 5.
[0119]
A RAM 1203 functions as a main memory, work area, and the like for the CPU 1201. A keyboard controller (KBC) 1205 controls instruction input from a keyboard (KB) 1209, a device (not shown), or the like.
[0120]
Reference numeral 1206 denotes a CRT controller (CRTC) which controls display on a CRT display (CRT) 1210. A disk controller (DKC) 1207 is a hard disk (boot program (start program: a program that starts execution (operation) of personal computer hardware and software)), a plurality of applications, editing files, user files, a network management program, and the like. HD) 1211 and flexible disk (FD) 1212 are controlled.
[0121]
Reference numeral 1208 denotes a network interface card (NIC) that exchanges data bidirectionally with a network printer, another network device, or another PC via the LAN 1220.
[0122]
【The invention's effect】
According to the present invention, when determining whether or not a material can be press-molded, the material parameter that is the limit value inferior in workability is estimated, and a predictive evaluation of formability is performed using the estimated material parameter. It is possible to accurately predict whether or not molding can be stably performed against material variations in the process, and by taking necessary measures in advance, molding defects after actual production has been started can be avoided. Thus, it is possible to easily and reliably execute highly reliable press molding.
[0123]
Specifically, it is assumed that the material used for press molding is specified in accordance with a predetermined industry standard, but even if the industrial standard is not taken into account, sufficiently reliable molding is possible. Judgment is possible.
[Brief description of the drawings]
FIG. 1 is a flowchart showing a specific algorithm of a formability prediction evaluation method.
FIG. 2 is a characteristic diagram showing a nominal stress-nominal strain curve obtained by subjecting a steel sheet to a tensile test.
FIG. 3 is a flowchart showing a method for selecting an optimum representative material from steel plates subjected to a tensile test.
FIG. 4 is a vector space diagram showing a state in which each index is vectorized by taking yield strength and tensile strength as examples.
FIG. 5 is a characteristic diagram showing a nominal stress-nominal plastic strain curve.
FIG. 6 is a characteristic diagram showing a true stress-true plastic strain curve of a steel sheet subjected to forming simulation.
FIG. 7 is a characteristic diagram showing results on material parameters of representative materials in a molding simulation experiment.
FIG. 8 is a characteristic diagram showing a result of material parameters of a lower limit material in a molding simulation experiment.
FIG. 9 is a characteristic diagram showing a normal distribution of quality variation in Example 2.
10 is a characteristic diagram showing a normal distribution of quality variations in Example 3. FIG.
FIG. 11 is a schematic diagram showing an internal configuration of a general personal user terminal device.

Claims

The material to be used for press molding is specified according to the specified industry standard,
Using the first stress-strain curve obtained by the tensile test of the material, out of yield strength, tensile strength and elongation , which are elements for determining whether or not the material can be molded , Compressing and expanding the first stress-strain curve into a second stress-strain curve so that at least one coincides with a limit value within an acceptable range of the industry standard, and the second stress A method for identifying material data, characterized in that material parameters are identified based on the curve of the strain curve.

In identifying the material parameters of the material to be subjected to press molding,
Using the first stress-strain curve obtained by the tensile test of the material, out of yield strength, tensile strength and elongation , which are elements for determining whether or not the material can be molded The first stress-strain curve is compressed and expanded to be converted into a second stress-strain curve so that at least one coincides with a limit value calculated from the distribution of quality variations of the material, and the second stress-strain curve is converted. A method for identifying material data, comprising identifying material parameters based on a curve of a stress-strain curve.

3. The distribution according to claim 2, wherein the distribution is a normal distribution, the average value of the quality variation is μ, the standard deviation is σ, k is a real number greater than or equal to 0, and the limit value is μ ± kσ. Material data identification method.

In identifying the material parameters of the material to be subjected to press molding,
Using the first stress-strain curve obtained by the tensile test of the material, out of yield strength, tensile strength and elongation , which are elements for determining whether or not the material can be molded , The first stress so that at least one coincides with a strict value of either a first limit value within an allowable range of an industry standard or a second limit value calculated from the distribution of quality variations of the material. A method for identifying material data, comprising compressing and expanding a strain curve to convert it into a second stress-strain curve, and identifying material parameters based on the curve of the second stress-strain curve.

5. The distribution according to claim 4, wherein the distribution is a normal distribution, the average value of the quality variation is μ, the standard deviation is σ, k is a real number greater than or equal to 0, and the second limit value is μ ± kσ. The material data identification method described in 1.

The index value is elongation of the material;
6. The first stress-strain curve is converted to the second stress-strain curve so that the elongation matches the lower limit value as the limit value. The material data identification method described in 1.

The index value is the yield strength or tensile strength of the material in addition to the elongation;
The first stress-strain curve is the second stress− so that the elongation matches the lower limit value as the limit value and the yield strength or tensile strength matches the upper limit value as the limit value. The material data identification method according to claim 6, wherein the material data is converted into a strain curve.

When selecting a representative material from the materials subjected to the tensile test of the material,
Each of the plurality of indicators is normalized using a predetermined reference value, and these are vectorized, an average vector of a plurality of materials having different normalized index values is calculated, and the plurality of normalized indicators are The material data identification method according to claim 1, wherein the representative material is a material represented by a vector having the closest distance to the average vector in a stretched vector space.

The material to be used for press molding is specified according to the specified industry standard,
Converting a nominal stress-nominal strain curve obtained by tensile testing of the material into a nominal stress-nominal plastic strain curve by subtracting an elastic strain value from a nominal strain value;
The nominal stress-nominal plastic strain curve is multiplied by a in the nominal plastic strain direction (provided that e _b is the elongation of the material and e _b ¹ is the lower limit of the elongation within the allowable range of the industry standard), a = e _b ¹ / e _b .) a second step,
A material data comprising: a third step of converting data within a range equal to or less than the uniform elongation of the obtained curve into a true stress-true plastic strain curve and calculating a necessary material parameter by a predetermined fitting. Identification method.

After the first step and before the second step, the nominal stress-nominal plastic strain curve is multiplied by k in the direction of the nominal stress (provided that the yield strength of the material is s _y , the industry standard tolerance) The material data of claim 9, further comprising a fourth step of k = s _y ^u / s _y where the upper limit value of the yield strength within the range is s _y ^u . Identification method.

After the second step and before the third step, the nominal stress-nominal plastic strain curve is multiplied by k times in the nominal stress direction (provided that the yield strength of the material is s _y , The material data according to claim 10, further comprising a fourth step of k = s _y ^u / s _y, where an upper limit of yield strength within the range is s _y ^u . Identification method.

In identifying the material parameters of the material to be subjected to press molding,
Converting a nominal stress-nominal strain curve obtained by tensile testing of the material into a nominal stress-nominal plastic strain curve by subtracting an elastic strain value from a nominal strain value;
The nominal stress-nominal plastic strain curve is multiplied by a in the nominal plastic strain direction (provided that e _b is the elongation of the material and e _b ¹ is the lower limit value of the elongation calculated from the distribution of quality variations of the material). = E _b ¹ / e _b ))
A material data comprising: a third step of converting data within a range equal to or less than the uniform elongation of the obtained curve into a true stress-true plastic strain curve and calculating a necessary material parameter by a predetermined fitting. Identification method.

After the first step and before the second step, the nominal stress-nominal plastic strain curve is multiplied by k times in the nominal stress direction (provided that the yield strength of the material is s _y , and the quality variation of the material The material according to claim 12, further comprising a fourth step of k = s _y ^u / s _y where the upper limit value of yield strength calculated from the distribution of s _y is s _y ^u . Data identification method.

After the second step and before the third step, the nominal stress-nominal plastic strain curve is multiplied by k times in the nominal stress direction (provided that the yield strength of the material is s _y , and the quality variation of the material The material according to claim 12, further comprising a fourth step of k = s _y ^u / s _y where the upper limit value of yield strength calculated from the distribution of s _y is s _y ^u . Data identification method.

The distribution is a normal distribution, wherein the average value of the quality variation is μ, the standard deviation is σ, k is a real number of 0 or more, the lower limit value is μ−kσ, and the upper limit value is μ + kσ. The method for identifying material data according to any one of claims 12 to 14.

In identifying the material parameters of the material to be subjected to press molding,
Converting a nominal stress-nominal strain curve obtained by tensile testing of the material into a nominal stress-nominal plastic strain curve by subtracting an elastic strain value from a nominal strain value;
The nominal stress - nominal plastic strain curve a times the nominal plastic strain direction (except that the elongation of the material and e _b, is calculated from the distribution of the quality variation of the lower limit or the material elongation in the allowed range of industry standard of the lower limit of elongation, any larger value when the e _b ^1, and a second step of a _{^{_{a = e b 1 / e b}}} .),
A material data comprising: a third step of converting data within a range equal to or less than the uniform elongation of the obtained curve into a true stress-true plastic strain curve and calculating a necessary material parameter by a predetermined fitting. Identification method.

After the first step and before the second step, the nominal stress-nominal plastic strain curve is multiplied by k in the direction of the nominal stress (provided that the yield strength of the material is s _y , the industry standard tolerance) of the upper limit or the second upper limit of the yield strength calculated from the distribution of quality variations in the material first yield strength of the range, if any small value and s _{_y} ^u, k = s _y The material data identification method according to claim 16, further comprising a fourth step of: ^u / s _y .

After the second step and before the third step, the nominal stress-nominal plastic strain curve is multiplied by k times in the nominal stress direction (provided that the yield strength of the material is s _y , of the upper limit or the second upper limit of the yield strength calculated from the distribution of quality variations in the material first yield strength of the range, if any small value and s _{_y} ^u, k = s _y The material data identification method according to claim 16, further comprising a fourth step of: ^u / s _y .

The distribution is a normal distribution, the average value of the quality variation is μ, the standard deviation is σ, k is a real number greater than or equal to 0, the second lower limit value is μ−kσ, and the second upper limit value is μ + kσ. The material data identification method according to claim 16, wherein the material data is identified.

When selecting a representative material from the materials subjected to the tensile test of the material,
Each of the plurality of indicators is normalized using a predetermined reference value, and these are vectorized, an average vector of a plurality of materials having different normalized index values is calculated, and the plurality of normalized indicators are The material data identification method according to any one of claims 9 to 19, wherein a material represented by a vector having the closest distance to the average vector in the extending vector space is used as the representative material.

A material to be subjected to press molding is specified according to a predetermined industrial standard, and is a system for predicting whether or not the material can be molded,
Using the first stress-strain curve obtained by a tensile test of the material,
At least one of yield strength, tensile strength, and elongation , which are a plurality of index values that are factors for determining whether or not the material can be molded, matches a limit value within an allowable range of the industry standard. Means for compressing and expanding the first stress-strain curve to convert it to a second stress-strain curve;
Means for identifying a material parameter based on the curve of the second stress-strain curve and predicting and evaluating whether or not the material can be molded using the material parameter.

A system for predicting and evaluating whether or not a material for press molding can be molded,
Using the first stress-strain curve obtained by a tensile test of the material,
At least one of yield strength, tensile strength, and elongation , which are a plurality of index values that are factors for determining whether or not the material can be molded, matches a limit value calculated from the distribution of quality variations of the material. Means for compressing and expanding the first stress-strain curve to convert it into a second stress-strain curve,
Means for identifying a material parameter based on the curve of the second stress-strain curve and predicting and evaluating whether or not the material can be molded using the material parameter.

23. The distribution according to claim 22, wherein the distribution is a normal distribution, the average value of the quality variation is μ, the standard deviation is σ, k is a real number greater than or equal to 0, and the limit value is μ ± kσ. Formability prediction evaluation system.

A material to be subjected to press molding is specified according to a predetermined industrial standard, and is a system for predicting whether or not the material can be molded,
Using the first stress-strain curve obtained by a tensile test of the material,
Among a plurality of index values that are factors for determining whether or not the material can be molded, at least one of yield strength, tensile strength, and elongation is a first limit value within an allowable range of the industry standard or the above The first stress-strain curve is compressed and expanded so as to coincide with any one of the second limit values calculated from the distribution of the quality variation of the material to obtain a second stress-strain curve. Means to convert,
Means for identifying a material parameter based on the curve of the second stress-strain curve and predicting and evaluating whether or not the material can be molded using the material parameter.

25. The distribution is a normal distribution, wherein the average value of the quality variation is μ, the standard deviation is σ, k is a real number greater than or equal to 0, and the second limit value is μ ± kσ. Formability prediction evaluation system described in 1.

The formability prediction evaluation system according to any one of claims 21 to 25, wherein the plurality of index values are elongation of the material, and become a lower limit value as the limit value.

In addition to the elongation of the material, the plurality of index values are the yield strength and tensile strength of the material,
27. The formability prediction evaluation system according to claim 26, wherein at least one of the yield strength and the tensile strength is an upper limit value as the limit value.

28. The formability prediction / evaluation system according to any one of claims 21 to 27, wherein a prediction evaluation of whether or not the material is moldable is performed and the result is reflected in product design.

Means for selecting a representative material having the plurality of indices when selecting a representative material from the materials subjected to a tensile test of the material;
The means for selecting the representative material normalizes each of the plurality of indices using a predetermined reference value, vectorizes them, calculates an average vector of a plurality of materials having different values of the standardized index, 29. The material represented by a vector having the closest distance to the average vector in a vector space spanned by a plurality of standardized indexes is the representative material. The formability prediction evaluation system described.

A material to be subjected to press molding is specified according to a predetermined industrial standard, and is a system for predicting whether or not the material can be molded,
Means for converting the nominal stress-nominal strain curve obtained by tensile testing of the material into a nominal stress-nominal plastic strain curve by subtracting the elastic strain value from the nominal strain value;
The nominal stress-nominal plastic strain curve is multiplied by a in the nominal plastic strain direction (provided that e _b is the elongation of the material and e _b ¹ is the lower limit of the elongation within the allowable range of the industry standard), a = e _b ¹ / e _b .)
A moldability prediction evaluation system comprising: means for converting data within a range equal to or less than the uniform elongation of the obtained curve into a true stress-true plastic strain curve, and calculating necessary material parameters by predetermined fitting. .

The nominal stress - k times the nominal plastic strain curve nominal stress direction (however, the yield strength of the material s _y, if the upper limit of yield strength within the allowable range of the industry standard and s _y ^u, k The moldability prediction evaluation system according to claim 30, further comprising: means = s _y ^u / s _y .

32. The formability prediction / evaluation system according to claim 30 or 31, wherein prediction evaluation of whether or not the material is moldable is performed, and the result is reflected in product design.

A system for predicting and evaluating whether or not a material for press molding can be molded,
Means for converting the nominal stress-nominal strain curve obtained by tensile testing of the material into a nominal stress-nominal plastic strain curve by subtracting the elastic strain value from the nominal strain value;
The nominal stress-nominal plastic strain curve is multiplied by a in the nominal plastic strain direction (provided that e _b is the elongation of the material and e _b ¹ is the lower limit value of the elongation calculated from the distribution of quality variations of the material). = E _b ¹ / e _b )
A moldability prediction evaluation system comprising: means for converting data within a range equal to or less than the uniform elongation of the obtained curve into a true stress-true plastic strain curve, and calculating necessary material parameters by predetermined fitting. .

The nominal stress - k times the nominal plastic strain curve nominal stress direction (however, yield strength and s _y of the material, when the upper limit of the yield strength calculated from the distribution of quality variations in the material and s _y ^u , k = a s _{_y} ^u / s _y.) forming prediction evaluation system of claim 33, further comprising a means.

35. The formability prediction / evaluation system according to claim 33 or 34, wherein a prediction evaluation of whether or not the material is moldable is performed and the result is reflected in a product design.

The distribution is a normal distribution, wherein the average value of the quality variation is μ, the standard deviation is σ, k is a real number of 0 or more, the lower limit value is μ−kσ, and the upper limit value is μ + kσ. The moldability prediction evaluation system according to any one of claims 33 to 35.

A material to be subjected to press molding is specified according to a predetermined industrial standard, and is a system for predicting whether or not the material can be molded,
Means for converting the nominal stress-nominal strain curve obtained by tensile testing of the material into a nominal stress-nominal plastic strain curve by subtracting the elastic strain value from the nominal strain value;
The nominal stress - a multiplying nominal plastic strain curve nominal plastic strain direction (however, the elongation of the material and e _b, the first quality variation in the lower limit or the material elongation in the allowed range of the industry standard of the second lower limit value of elongation calculated from the distribution, either large value when the e _b ^1, a _{^{_{a = e b 1 / e b}}} .) means for,
A moldability prediction evaluation system comprising: means for converting data within a range equal to or less than the uniform elongation of the obtained curve into a true stress-true plastic strain curve, and calculating necessary material parameters by predetermined fitting. .

The nominal stress-nominal plastic strain curve is multiplied by k times in the nominal stress direction (provided that the yield strength of the material is s _y , the first upper limit value of the yield strength calculated from the distribution of quality variations of the material, or the material among the second maximum value of the elongation calculated from the distribution of the quality variation of the one smaller and s _y ^u, and further comprising a means for a _{^{_{k = s y u / s y}}} .) The moldability prediction evaluation system according to claim 37.

39. The formability prediction / evaluation system according to claim 37 or 38, wherein prediction evaluation of whether or not the material is moldable is performed and the result is reflected in product design.

The distribution is a normal distribution, the average value of the quality variation is μ, the standard deviation is σ, k is a real number greater than or equal to 0, the second lower limit value is μ−kσ, and the second upper limit value is μ + kσ. The moldability prediction evaluation system according to any one of claims 37 to 39, wherein:

When selecting a representative material from the materials subjected to the tensile test of the material,
Each of the plurality of indicators is normalized using a predetermined reference value, and these are vectorized, an average vector of a plurality of materials having different normalized index values is calculated, and the plurality of normalized indicators are The formability prediction evaluation system according to any one of claims 30 to 40, wherein a material represented by a vector that is closest to the average vector in the extending vector space is the representative material.

The material to be used for press molding is specified according to the specified industry standard,
Converting a nominal stress-nominal strain curve obtained by tensile testing of the material into a nominal stress-nominal plastic strain curve by subtracting an elastic strain value from a nominal strain value;
The nominal stress-nominal plastic strain curve is multiplied by a in the nominal plastic strain direction (provided that e _b is the elongation of the material and e _b ¹ is the lower limit of the elongation within the allowable range of the industry standard), a = e _b ¹ / e _b .) a second step,
A program for causing a computer to execute a third step of converting data within a range equal to or less than the uniform elongation of the obtained curve into a true stress-true plastic strain curve and calculating necessary material parameters by a predetermined fitting.

In identifying the material parameters of the material to be subjected to press molding,
Converting a nominal stress-nominal strain curve obtained by tensile testing of the material into a nominal stress-nominal plastic strain curve by subtracting an elastic strain value from a nominal strain value;
The nominal stress-nominal plastic strain curve is multiplied by a in the nominal plastic strain direction (provided that e _b is the elongation of the material and e _b ¹ is the lower limit value of the elongation calculated from the distribution of quality variations of the material). = E _b ¹ / e _b ))
A program for causing a computer to execute a third step of converting data within a range equal to or less than the uniform elongation of the obtained curve into a true stress-true plastic strain curve and calculating necessary material parameters by a predetermined fitting.

In identifying the material parameters of the material to be subjected to press molding,
Converting a nominal stress-nominal strain curve obtained by tensile testing of the material into a nominal stress-nominal plastic strain curve by subtracting an elastic strain value from a nominal strain value;
The nominal stress - nominal plastic strain curve a times the nominal plastic strain direction (except that the elongation of the material and e _b, is calculated from the distribution of the quality variation of the lower limit or the material elongation in the allowed range of industry standard of the lower limit of elongation, any larger value when the e _b ^1, and a second step of a _{^{_{a = e b 1 / e b}}} .),
A program for causing a computer to execute a third step of converting data within a range equal to or less than the uniform elongation of the obtained curve into a true stress-true plastic strain curve and calculating necessary material parameters by a predetermined fitting.

45. A computer-readable recording medium on which the program according to any one of claims 42 to 44 is recorded.