Designシンポジウム2021 講演論文集

እほ᳨ᰝ࡟࠾ࡅࡿே㛫୰ᚰᆺࡢసᴗ࡜⮬ື໬ࡢࢹࢨ࢖ࣥ
Human-Centered Work and Automation Design in Appearance Inspection‫ۑ‬୰ᔱⰋ௓㸦㟁Ẽ㏻ಙ኱Ꮫ㸧  ⶶ᪉ⱥ⣖㸦㟁Ẽ㏻ಙ኱Ꮫ㸧  ୕ୖᙬᑀ㸦㟁Ẽ㏻ಙ኱Ꮫ㸧 *1Ryosuke Nakajima, The University of Electro-Communications, 1-5-1 Chofugaoka, Chofu, Tokyo, 182-8585, nakajima@uec.ac.jp*2 Hidenori Kurakata, The University of Electro-Communications, 1-5-1 Chofugaoka, Chofu, Tokyo, 182-8585, k1510055@uec.ac.jp*3 Ayane Mikami, The University of Electro-Communications, 1-5-1 Chofugaoka, Chofu, Tokyo, 182-8585, m1610606@uec.ac.jp࣮࣮࢟࣡ࢻእほ᳨ᰝ┠ど᳨ᰝసᴗタィ⮬ື໬ᶵᲔᏛ⩦◊✲⫼ᬒ ᕤᴗ 〇ရ ࡢ⏕ ⏘⌧ ሙ࡟ ࠾࠸ ࡚ 㸪 ே㛫 ࡟ࡼ ࡿస ᴗࡣ IE
㸦Industrial Engineering㸧ᡭἲ࡛࠶ࡿ┤᥋ほᐹἲࡸ PTS㸦Predetermined Time Standard㸧ἲ࡞࡝ࢆ⏝࠸࡚㸪ࡑࡢసᴗ࡟㐺ṇ࡛ᚲせ࡞᫬㛫ࢆᶆ‽᫬㛫࡜ࡋ࡚Ỵᐃࡋ㸪ࡑࡢ᫬㛫ࢆࡶ࡜࡟⏕⏘ィ⏬ࡸసᴗᨵၿࡀ⾜ࢃࢀ࡚࠸ࡿ㸬ࡓࡔࡋ㸪ᕤᴗ〇ရࡢእほୖ࡟ᚤᑠ࡞࢟ࢬࡸởࢀ࡞࡝ࡢḞⅬࡀ࡞࠸ࡇ࡜ࢆಖドࡍࡿࡓࡵࡢእほ᳨ᰝ࡟㛵ࡋ࡚ࡣ㸪ࡑࡢ௚ࡢ⤌❧ࡸຍᕤࡢࡼ࠺
࡟〇ရ⮬య࡟┤᥋ⓗ࡟௜ຍ౯್ࡀ୚࠼ࡽࢀࡿࡶࡢ࡛ࡣ࡞ࡃ㸪࠿ࡘูࡢ᳨ᰝ⪅ࡸ⟶⌮⪅ࡀእ㒊࠿ࡽࡑࡢసᴗࡢጇᙜᛶࢆホ౯ࡍࡿࡇ࡜ࡀ㞴ࡋ࠸࡜࠸࠺ၥ㢟ࡀ࠶ࡿ (1)㸬ࡲࡓ㸪㏆ᖺ࡛ࡣ〇㐀ᴗ࡟࠾࠸࡚ࡶᑡᏊ㧗㱋໬࡟ࡼࡿேᮦ୙㊊ࡀ῝้࡛㸪㐣ཤ 20 ᖺ㛫࡛ປാேཱྀࡀ 11.6%ῶᑡࡋ㸪〇㐀ᴗ࡟㛵ࡍࡿ஦ᴗ⪅ᩘࡶ༙ῶࡋ࡚࠾ࡾ㸪ࡉࡽ࡟᪂ᆺࢥࣟࢼ࢘࢖ࣝࢫឤᰁ⑕࡟
ࡼࡿᙳ㡪࡛ᑐ㠃࡛ࡢ OJT㸦On the job training㸧ࡢᶵ఍ࡀῶ
ᑡࡋ㸪ᚑ᮶ࡢே࠿ࡽே࡬ࡢᢏ⬟ఏᢎࡀᅔ㞴࡞≧ἣ࡜࡞ࡗ࡚
࠸ࡿ (2)㸬
ࡇࢀࡽࡢၥ㢟࡟ᑐࡋ࡚㸪ྂࡃ࠿ࡽே㛫࡟ࡼࡿእほ᳨ᰝ࡟㛵ࡍࡿ◊✲ࡀ㐍ࡵࡽࢀ࡚࠸ࡿ㸬౛࠼ࡤ㸪᳨ᰝ⢭ᗘࡸ᳨ᰝຠ⋡ࡢྥୖࡢࡓࡵ࡟᳨ᰝ⪅ࡢ┠ど᪉ἲࢆศᯒࡋࡓ◊✲ (3)-(6)㸪
㌟య㈇ᢸࡢపῶࡢࡓࡵ࡟᳨ᰝ⪅ࡢどぬⓗ࣭㌟యⓗ㈇ᢸࢆศᯒࡋࡓ◊✲ (7)-(9)࡞࡝ࡀከࡃ⾜ࢃࢀ࡚࠸ࡿ㸬ࡓࡔࡋ㸪ࡇࢀࡽࡢ◊✲ࡣ㸪ಶูࡢእほ᳨ᰝᕤ⛬ࡢసᴗᨵၿࢆ┠ⓗ࡜ࡋࡓศᯒⓗ࡞࢔ࣉ࣮ࣟࢳ࡟ࡼࡿ᳨ウ࡟␃ࡲࡗ࡚࠸ࡿ㸬ࡍ࡞ࢃࡕ㸪ከࡃࡢᕤᴗ〇ရࡸḞⅬࡢ≉ᚩ࡟ྜࢃࡏ࡚ᖜᗈࡃ㐺⏝࡛ࡁࡿࡼ࠺࡞సᴗタィࡢ᪉ἲㄽࡀ♧ࡉࢀࡿ࡟ࡣ⮳ࡗ࡚࠾ࡽࡎ㸪⌧ᅾ࡛ࡶᶆ‽᫬㛫ࢆタᐃࡍࡿ᪉ἲࡀ☜❧ࡉࢀ࡚࠸࡞࠸㸬ࡑࡢࡓࡵ㸪ᐇ㝿ࡢ⏕⏘⌧ሙ࡛ࡣ㸪㐣ᗘ࡞᳨ᰝ⢭ᗘࡢ㏣ồ࡟ࡼࡿ㐣๫࡞᳨ᰝ㸦࣒ࢲ࡞సᴗ㸧࡜࡞ࡗ࡚࠸ࡿሙྜࡸ㸪㐣ᗘ࡞᳨ᰝຠ⋡ࡢ㏣ồ࡟ࡼࡿே㛫ࡢどぬᶵ⬟ࡢ㝈⏺ࢆ㉸࠼ࡓ᳨ᰝ㸦࣒ࣜ࡞సᴗ㸧࡜࡞ࡗ࡚࠸ࡿሙྜࡀ࠶ࡿ (10)㸬ࡲࡓ㸪㐺ṇ࡞సᴗタィࡀ࡞ࡉࢀ࡚࠸࡞࠸ࡢ࡛㸪᳨ᰝ⪅࡟ᑐࡋ࡚ࡣࠕ㞟୰ࡋ࡚ࡼࡃぢ࡞ࡉ࠸ࠖ࡜࠸ࡗࡓ㠀⛉Ꮫⓗ࡞ᣦᑟࡀ࡞ࡉࢀ࡚࠸ࡿሙ㠃ࡶぢཷࡅࡽࢀࡿ (11)㸬
ࡑࡢࡓࡵ㸪୍㒊ࡢ⏕⏘⌧ሙ࡛ࡣእほ᳨ᰝࡢ⮬ື໬ࡢᑟධ࡟ྥࡅࡓ᳨ウࡀ⾜ࢃࢀ࡚࠸ࡿ㸬ẚ㍑ⓗྂࡃ࠿ࡽὀ┠ࡉࢀ࡚࠸ࡿᡭἲ࡜ࡋ࡚㸪⏬ീฎ⌮ᢏ⾡ࡸ⤫ィᡭἲࢆ⏝࠸ࡓ⮬ື᳨ᰝࢩࢫࢸ࣒ (12)-(14) 㸪࣮ࣞࢨ࣮ࢆ⏝࠸ࡓ⮬ື᳨ᰝࢩࢫࢸ࣒ (15)ࡀᥦ᱌ࡉࢀ㸪ࡑࡢ᭷ຠᛶࡶሗ࿌ࡉࢀ࡚࠸ࡿ㸬ࡋ࠿ࡋ࡞ࡀࡽ㸪᳨ᰝ⢭ᗘ᳨࣭ᰝຠ⋡ࡀ୙༑ศ࡜࠸ࡗࡓၥ㢟ࡸ㐣᳨ฟ㸦➨୍✀㐣ㄗ㸧࡜ㄗ᳨ฟ㸦➨஧✀㐣ㄗ㸧ࢆࣂࣛࣥࢫࡍࡿࡓࡵࡢ㜈್ࡢㄪᩚࡀ㞴ࡋ࠸࡜࠸ࡗࡓၥ㢟㸪ࡉࡽ࡟ࡣᑟධࢥࢫࢺࡸ㐠⏝ࢥࢫࢺ࡟ᑐࡋ࡚㈝⏝ᑐຠᯝࡀప࠸࡜࠸ࡗࡓၥ㢟ࡶᣦ᦬ࡉࢀ࡚࠾ࡾ (16)-(18)㸪ᢏ⾡ⓗ࣭⤒῭ⓗ࡞୧㠃࠿ࡽᚲࡎࡋࡶᐇ⏝໬ࡀ㐍ࢇ࡛࠸࡞࠸≧ἣࡶ࠶ࡿ㸬ࡓࡔࡋ㸪㏆ᖺ࡛ࡣ㸪Ⰻရ⏬ീ࡜୙Ⰻရ⏬ീࢆᩍᖌࢹ࣮ࢱ࡜ࡍࡿᶵᲔᏛ⩦ࢆ⏝࠸ࡓ⮬ື᳨ᰝࢩࢫࢸ࣒ࡶᥦ᱌ࡉࢀࡣࡌࡵ㸪୍㒊ࡢእほ᳨ᰝᕤ⛬࡟࠾࠸࡚ᢏ⾡ⓗ࣭⤒῭ⓗ࡞ၥ㢟ࢆゎỴࡋ࠺ࡿࡇ࡜ࡀሗ࿌ࡉࢀ࡚࠾ࡾ (19)-(21)㸪ࡑࡢືྥࡀὀ┠ࡉࢀ࡚࠸ࡿ㸬◊✲┠ⓗ ᮏ◊✲࡛ࡣ㸪ᕤᴗ〇ရࡢእほୖࡢရ㉁ࢆಖドࡍࡿࡓࡵࡢእほ᳨ᰝࢆ◊✲ᑐ㇟࡜ࡋ࡚㸪᳨ᰝ⢭ᗘ࡜᳨ᰝຠ⋡ࢆྥୖࡉࡏࡿࡓࡵ㸪ከ✀ከᵝ࡞ᕤᴗ〇ရࡸḞⅬࡢ≉ᚩ࡟ྜࢃࡏ࡚ᖜᗈࡃ㐺⏝࡛ࡁࡿసᴗタィࡢ᪉ἲㄽࢆ☜❧ࡍࡿࡇ࡜ࢆ┠ⓗ࡜ࡍࡿ㸬ࡍ࡞ࢃࡕ㸪సᴗᨵၿࡢࡓࡵࡢศᯒⓗ࢔ࣉ࣮ࣟࢳࡔࡅ࡛࡞ࡃ㸪సᴗタィࢆ┠ⓗ࡜ࡋࡓタィⓗ࡞࢔ࣉ࣮ࣟࢳ࡟ࡼࡿ
᳨ウࢆ┠ᣦࡋ࡚࠸ࡿⅬࡀ௚ࡢ㛵㐃◊✲ (3)-(9)࡜ᮏ㉁ⓗ࡟␗࡞ࡿⅬ࡛࠶ࡿ㸬ࡉࡽ࡟㸪ࡑࢀࡽࡢ▱ぢ࡜⏬ീࢹ࣮ࢱ࡟ࡼࡿᶵᲔᏛ⩦ࢆ⏝࠸ࡓ⮬ື໬ࢆ┠ⓗ࡜ࡋ࡚࠸ࡿ㸬◊✲ࡢ඲యീ࡜◊✲⤒㐣
ୖ㏙ࡋࡓ◊✲┠ⓗࢆ㐩ᡂࡍࡿࡓࡵ㸪ᮏ◊✲࡛ࡣᅗ 1 ࡟♧
ࡍ㏻ࡾ㸪እほ᳨ᰝࡢᵓᡂせ⣲ࡢほⅬ࠿ࡽ᳨ᰝᑐ㇟㸦ᕤᴗ〇ရࡸḞⅬ㸧࡜᳨ᰝ⎔ቃ㸦↷᫂࡜⏝ල㸧㸪᳨ᰝ⪅㸪⮬ື᳨ᰝࢩࢫࢸ࣒ࡢ 4 ࡘ࡟ᩚ⌮ࡋ㸪ࡑࢀࡒࢀ࡟[1]᳨ᰝᑐ㇟ࡢホ౯᪉ἲ࡟㛵ࡍࡿ᳨ウ㸪[2]᳨ᰝ⎔ቃࡢタィ࡟㛵ࡍࡿ᳨ウ㸪[3]᳨ᰝ⪅ࡢ᳨ᰝ᪉ἲࡢタィ࣭カ⦎࣭⟶⌮࡟㛵ࡍࡿ᳨ウ㸪[4]⮬ື᳨ᰝࢩࢫࢸ࣒ࡢ㛤Ⓨ࡟㛵ࡍࡿ᳨ウ࡜ࡋ࡚ㄢ㢟ࢆタᐃࡋ㸪◊✲ࢆᐇ᪋ࡋ࡚࠸ࡿ㸬࡞࠾㸪ࡇࢀࡽࡢ◊✲ㄢ㢟ࢆᐇ᪋ࡍࡿୖ࡛ࡣ㸪◊✲ᐊ࡟࠾ࡅࡿ⿕㦂⪅ᐇ㦂࡜ࢩࢫࢸ࣒㛤Ⓨࡢࡳ࡞ࡽࡎ㸪ᐇ㝿ࡢእほ᳨ᰝᕤ⛬࡟࠾ࡅࡿᐇែㄪᰝ᳨࣭ドࡶ୪⾜ࡋ࡚ᐇ᪋ࡋ࡚࠸ࡿ (22)-(24)㸬ྛ◊✲ࢸ࣮࣐ࡢලయⓗ࡞◊✲⤒㐣࡜ࡋ࡚㸪[1]᳨ᰝᑐ㇟ࡢホ౯᪉ἲ࡟㛵ࡍࡿ᳨ウ࡟㛵ࡋ࡚ࡣ㸪ᮏ◊✲࡛⪃᱌ࡍࡿసᴗタィࡢ᪉ἲㄽࢆ࠶ࡽࡺࡿᕤᴗ〇ရࡸḞⅬ࡟㐺⏝ࡍࡿࡓࡵ㸪ᵝࠎ࡞ᕤᴗ〇ရࡸḞⅬࢆḞⅬ᳨ฟࡢほⅬ࠿ࡽホ౯ࡍࡿᣦᶆ81

Designシンポジウム2021 講演論文集

㻌 Research Questions (RQ)ͳ͞ΗΉͲ͹‫͍͘Ͳڂݜ‬Δ͖Ͷ͵ͮͪ͞ͳ

RQ1 ‫ࠬݗ‬ଲেଡझଡ༹͵޽‫ۂ‬੣඾ʤ‫ࠬݗ‬ଲেͳ఼ܿʥΝʹ͹Γ͑Ͷ඲Ճ͢ɼຌ‫ߡͲڂݜ‬ҌͤΖ๏๑࿨Ͷన༽ͤ΄͖͘ʃ‫ࠬݗ‬ଲেΏ఼ܿ͹ಝ௅ΝรಊགྷҾͳͤΖࣰ‫ݩ‬ΝߡҌ͢ɼͨΗΔ͗‫ࠬݗ‬੠ౕΏ‫ིްࠬݗ‬Ͷ‫ͤ·ٶ‬Ӫ‫ڻ‬Ν‫ݗ‬౾ͪ͢ɽ→>>   @‫ࠬݗ‬ଲেͺ৯ͳ‫ܙ‬য়/ߑଆ͹෵ࡸ੓Ͳ඲ՃՆ೵Ͳ͍Ζ͞ͳ͗Κ͖ͮͪɽ→>>   @఼ܿͺΦρζว͹ௗ͠ͶٍౕαϱφϧηφΝ৒ͣͱಚΔΗΖ఼ܿ͹໚ޭౕͲ඲ՃՆ೵Ͳ͍Ζ͞ͳ͗Κ͖ͮͪɽ

RQ2 ‫ڧ؂ࠬݗ‬‫͏༽Ͳࠬݗ‬Ζ֨୉‫ں‬Ώল໎ͺʹ͹Γ͑Ͷઅ‫͖͘΄ͤܯ‬ʃ֨୉‫ں‬Ώল໎͹࢘༽๏๑ΝรಊགྷҾͳͤΖࣰ‫ݩ‬ΝߡҌ͢ɼͨΗΔ͗‫ࠬݗ‬੠ౕΏ‫ིްࠬݗ‬Ͷ‫ͤ·ٶ‬Ӫ‫ڻ‬Ν‫ݗ‬౾ͪ͢ɽ>   @఼ܿ͹໚ޭౕͶ߻Κͦͱనਜ਼͵֨୉‫ں‬͹֨୉ഔིΝઅ‫ܯ‬Ն೵Ͳ͍Ζ͞ͳ͗Κ͖ͮͪɽ→>→>>@ ఼ܿ͹໚ޭౕͶΓΔͥɼ‫ࠬݗ‬ଲেͶଲ͢ͱল໎͹লֱౕࣻΝรԿͦ͠Ζ‫ࠬݗ‬๏๑༙͗ްͲ͍Ζ͞ͳ͗Κ͖ͮͪɽ‫ͤࠬݗ‬Ζ‫ࠬݗ‬ଲেͶ߻Κͦͪ‫ڧ؂ࠬݗ‬͹અ‫ܯ‬‫ڧ؂ࠬݗ‬[2]‫ڧ؂ࠬݗ‬͹અ‫ܯ‬Ͷ‫ͤؖ‬Ζ‫ݗ‬౾

[2-1]‫͏༽Ͳࠬݗ‬Ζ֨୉‫ں‬͹నਜ਼ԿͶ‫ͤؖ‬Ζ‫ڂݜ‬[2-2]‫͏༽Ͳࠬݗ‬Ζল໎͹నਜ਼ԿͶ‫ͤؖ‬Ζ‫ڂݜ‬‫ࠬݗ‬ଲে
[1]‫ࠬݗ‬ଲে͹඲Ճ๏๑Ͷ‫ͤؖ‬Ζ‫ڂݜ‬[1-1]‫ࠬݗ‬ଲে͹෵ࡸ੓͹඲ՃࢨඬͶ‫ͤؖ‬Ζ‫ڂݜ‬[1-2] ఼ܿ͹ࢻ೟੓͹඲ՃࢨඬͶ‫ͤؖ‬Ζ‫ڂݜ‬‫ࠬݗ‬ϕϫιη‫݃ࠬݗ‬Վʀྒྷ඾/෈ྒྷ඾൓พིʀ‫ؔ࣎ࠬݗ‬͹޴৏నਜ਼͵֐؏‫ۂࡠࠬݗ‬͹ࣰ‫ݳ‬[3]‫ंࠬݗ‬͹‫ࠬݗ‬๏๑͹અ‫ܯ‬ʀ‫܉‬࿇ʀ؇ཀྵͶ‫ͤؖ‬Ζ‫ݗ‬౾‫ͤࠬݗ‬Ζ‫ࠬݗ‬ଲেͶ߻Κͦͪ‫ࠬݗ‬๏๑͹અ‫ܯ‬[3-1]‫ंࠬݗ‬͹‫ࠬݗ‬๏๑͗‫ࠬݗ‬੠ౕʀ‫ིްࠬݗ‬Ͷ‫ͤ·ٶ‬Ӫ‫ڻ‬Ͷ‫ͤؖ‬Ζ‫ڂݜ‬[3-2]ࣰࡏ͹֐؏‫޽ࠬݗ‬ఖͶ͕͜Ζࡠ‫ۂ‬෾ੵͶ‫ͤؖ‬Ζ‫ڂݜ‬[3-3]‫܉‬࿇εητϞʀ؇ཀྵεητϞ͹֋൅Ͷ‫ͤؖ‬Ζ‫ڂݜ‬‫ंࠬݗ‬[4]ࣙಊ‫ࠬݗ‬εητϞ͹֋൅Ͷ‫ͤؖ‬Ζ‫ݗ‬౾
[4-1]‫ؽ‬փָसΝ༽͏ͪࡠ‫ࢩۂ‬ԋεητϞ͹֋൅Ͷ‫ͤؖ‬Ζ‫ڂݜ‬[4-2]‫ؽ‬փָसΝ༽͏ͪࡠ‫ࢩۂ‬ԋεητϞ͹‫༽׈‬๏๑Ͷ‫ͤؖ‬Ζ‫ڂݜ‬ࣙಊ‫ࠬݗ‬εητϞ

RQ3 ‫ंࠬݗ‬‫ंࠬݗ‬͹‫ࠬݗ‬๏๑ͺʹ͹Γ͑Ͷઅ‫Ͳ͘΄ͤܯ‬ɼʹΗΝʹ͹Γ͑Ͷ‫܉‬࿇ʀ؇ཀྵͤ΄͖͘ʃ‫ंࠬݗ‬͹‫ࠬݗ‬๏๑ΝรಊགྷҾͳͤΖࣰ‫ݩ‬ΝߡҌ͢ɼͨΗΔ͗‫ࠬݗ‬੠ౕΏ‫ིްࠬݗ‬Ͷ‫ͤ·ٶ‬Ӫ‫ڻ‬Ν‫ݗ‬౾ͪ͢ɽ→>>   @֐؏‫ࠬݗ‬Ͷ͕͏ͱ෉ଵࡠ‫ۂ‬͹಼༲Ώළౕɼν΢ϝϱήͺ‫ࠬݗ‬੠ౕʀ‫ིްࠬݗ‬ͶӪ‫ڻ‬Ν‫͗ͳ͞͏͵͠·ٶ‬Κ͖ͮͪɽࣰࡏ͹‫ݳ‬৖Νଲেͳ͢ͱɼࢻત‫ܯ‬଎ૹ஖ͳϠʖεϥϱΫϡϕοϡΝ‫ۂࡠͪ͢༽׈‬෾ੵʀࡠ‫܉ۂ‬࿇͹Ն೵੓Ν‫ݗ‬౾ͪ͢ɽ→>>   @ॊཔͺೋ͖ͮͪ͢ࡠ‫ۂ‬ϕϫιη͹෾ੵΝࢻત‫ܯ‬଎ૹ஖Ν༽͏Ζ͞ͳͲՆ೵ͳ͵Ζ͞ͳ͗Κ͖ͮͪɽͪɽ→>>   @ࢻત‫ܯ‬଎ૹ஖ͳϠʖεϥϱΫϡϕοϡΝಋ‫ͦ͠غ‬Ζ͞ͳͲɼࡠ‫܉ۂ‬࿇ʀࡠ‫ۂ‬؇ཀྵͶ‫༽׈‬Ն೵Ͳ͍Ζ͞ͳ͗Κ͖ͮͪɽ

RQ4 ࣙಊ‫ࠬݗ‬εητϞࣰࡏ͹ਫ਼ࢊ‫ݳ‬৖Ͷ͕͏ͱࣙಊ‫ࠬݗ‬εητϞΝʹ͹Γ͑Ͷ಍೘͢ɼӣ༽ͤΖ΄͖͘ʃࣰࡏ͹ਫ਼ࢊ‫ݳ‬৖Ͳࣰ༽ԿͶචགྷ͵གྷ݇Ν௒ࠬͤΖͳͳ΍Ͷɼ‫ؽ‬փָसΝ༽͏ͪࡠ‫ࢩۂ‬ԋεητϞΝ֋൅͢ɼͨ͹༙ް੓Νࣰ‫ݩ‬దͶ‫ݗ‬౾ͪ͢ɽ→>>   @‫ؽ‬փָसΝ༽͏Ζ͞ͳͲɼ‫ंࠬݗ‬ΝࢩԋͤΖࡠ‫ࢩۂ‬ԋεητϞ͗֋൅Ն೵Ͳ͍Ζ͞ͳ͗Κ͖ͮͪɽ→>>   @֋൅ͪ͢ࡠ‫ࢩۂ‬ԋεητϞͶͺɼ‫ࠬݗ‬੠ౕΝ޴৏ͦ͠ΖްՎ͍͗Ζ͞ͳ͗Κ͖ͮͪɽFig.1 Overview of this research and Research Question 㻌ࡢ᳨ウࢆ㐍ࡵ࡚࠸ࡿ㸬[2]᳨ᰝ⎔ቃࡢタィ࡟㛵ࡍࡿ᳨ウ࡟㛵ࡋ࡚ࡣ㸪[1]᳨ᰝᑐ㇟࡛⪃᱌ࡋࡓホ౯ᣦᶆࢆࡶ࡜࡟㸪᳨ᰝ࡛⏝࠸ࡿᣑ኱㙾ࡸ↷᫂ࢆ㐺ṇ໬ࡍࡿࡓࡵࡢ᳨ウࢆ㐍ࡵ࡚࠸ࡿ㸬[3]᳨ᰝ⪅ࡢ᳨ᰝ᪉ἲࡢタィ࣭カ⦎࣭⟶⌮࡟㛵ࡍࡿ᳨ウ࡟㛵ࡋ࡚ࡣ㸪[1]᳨ᰝᑐ㇟࡛⪃᱌ࡋࡓホ౯ᣦᶆࢆࡶ࡜࡟㸪᳨ᰝ⪅ࡢ᳨ᰝ᪉ἲࢆ㐺ṇ໬ࡍࡿࡓࡵࡢ᳨ウ㸪ᐇ㝿ࡢ⏕⏘⌧ሙ࡛ࡢ᭷ຠᛶࡢ᳨ド㸪࠾ࡼࡧカ⦎ࢩࢫࢸ࣒ࡸ⟶⌮ࢩࢫࢸ࣒ࡢࣉࣟࢺࢱ࢖ࣉࡢ㛤Ⓨࢆ㐍ࡵ࡚࠸ࡿ㸬[4]⮬ື᳨ᰝࢩࢫࢸ࣒ࡢ㛤Ⓨ࡟㛵ࡍࡿ᳨ウ࡟㛵ࡋ࡚ࡣ㸪ᐇ㝿ࡢእほ᳨ᰝᕤ⛬࡛ᐇ⏝໬࣭ᑟධ࡟ᚲせ࡞せ௳ࢆᩚ⌮ࡋࡓୖ࡛㸪ᶵᲔᏛ⩦ࢆά⏝ࡋࡓసᴗᨭ᥼ࢩࢫࢸ࣒ࡢ㛤Ⓨ࡜ࡑࡢά⏝᪉ἲࡢ᳨ウࢆ㐍ࡵ࡚࠸ࡿ㸬82◊✲ㄢ㢟>@᳨ᰝᑐ㇟ࡢホ౯ᣦᶆ࡟㛵ࡍࡿ◊✲ ᮏ❶࡛ࡣ㸪ᅗ 1 ࡢ[1]᳨ᰝᑐ㇟ࡢホ౯᪉ἲ࡟㛵ࡍࡿ᳨ウ࡟࠾ࡅࡿ[1-1]᳨ᰝᑐ㇟ࡢホ౯ᣦᶆ࡟㛵ࡍࡿ◊✲࡟ࡘ࠸࡚㏙࡭ࡿ㸬᳨ᰝᑐ㇟ࡢホ౯ࡢ◊✲⫼ᬒ እほ᳨ᰝࡢᑐ㇟࡜࡞ࡿᕤᴗ〇ရ࡟ࡣ㸪⮬ື㌴⏝ࡢ࢞ࣛࢫࡸ࣎ࢹ࢕ࡢࡼ࠺࡞᳨ᰝᑐ㇟㠃ࡀ༢⣧࡞ࡶࡢ࠿ࡽ㸪㟁Ꮚ㒊ရ⏝ࡢࣉࣜࣥࢺᇶᯈࡢࡼ࠺࡞」㞧࡞ࡶࡢࡲ࡛ከ✀ከᵝ࡛࠶ࡿ㸬ࡑࡋ࡚㸪᳨ᰝᑐ㇟㠃ࡀ」㞧࡟࡞ࡿ࡟ࡘࢀ࡚㸪እほ᳨ᰝ⮬యDesignシンポジウム2021 講演論文集㻌ࡀ㞴ࡋࡃ࡞ࡿࡇ࡜ࡀண᝿ࡉࢀࡿ (25)㸬ࡍ࡞ࢃࡕ㸪᳨ᰝᑐ㇟㠃◊✲ㄢ㢟>@ᶵᲔᏛ⩦ࢆ⏝࠸ࡓసᴗᨭ᥼ࢩࢫࢸ࣒ࡢ᭷ຠᛶ࡟㛵ࡍࡿ◊✲ ᮏ❶࡛ࡣ㸪ᅗ  ࡢ>@⮬ື᳨ᰝࢩࢫࢸ࣒ࡢ㛤Ⓨ࡟㛵ࡍࡿ᳨ウ࡟࠾ࡅࡿ>@ᶵᲔᏛ⩦ࢆ⏝࠸ࡓసᴗᨭ᥼ࢩࢫࢸ࣒ࡢ᭷ຠᛶ࡟㛵ࡍࡿ◊✲࡟ࡘ࠸࡚㏙࡭ࡿ㸬సᴗᨭ᥼ࢩࢫࢸ࣒ࡢ◊✲⫼ᬒ ⏘Ꮫ᳨࡛ウࡀ㐍ࡵࡽࢀ࡚࠸ࡿ⮬ື᳨ᰝࢩࢫࢸ࣒ࡢືྥࡸၥ㢟Ⅼࢆㄪᰝ (18)ࡍࡿ࡜࡜ࡶ࡟㸪እほ᳨ᰝᕤ⛬࡛ᐇ㝿࡟ᐇ⏝໬ࡍࡿࡓࡵ࡟ᚲせ࡞せ௳ࢆᩥ⊩ㄪᰝ (28)-(29)㸪࠾ࡼࡧᐇ㝿ࡢእほ᳨ᰝᕤ⛬ࡢᐇົᢸᙜ⪅࡬ࡢࣄ࢔ࣜࣥࢢࢆ㏻ࡌ࡚ᩚ⌮ࡋࡓ㸬ࡑࡢ⤖ᯝ㸪(1)ᮦ㉁ࡸᙧ≧㸪ព໶࡞࡝ࡀከ✀ከᵝ࡞〇ရ࡟࠾࠸࡚ከᵝ࡞≧ែࢆ࿊ࡍ࢟ࢬࡸởࢀ࡞࡝ࡢḞⅬࢆ᥈⣴ࡍࡿࡇ࡜㸦᥈⣴ࣉࣟࢭࢫ㸧࡜ḞⅬࡢ≧ែ࡟ྜࢃࡏ࡚Ⰻရ࣭୙
Ⰻရࡢุูࡍࡿࡇ࡜㸦ุูࣉࣟࢭࢫ㸧ࡀ㞴ࡋࡃ㸪ࡉࡽ࡟␗ᖖ⟠ᡤࡢษ㝖ࡸὙί࡞࡝ࡢᡭ┤ࡋ࡟ࡼࡗ࡚Ⰻရ࡟࡛ࡁࡿࡶࡢࡢุูࡀ㞴ࡋ࠸࡜࠸࠺ᢏ⾡ⓗ࡞ၥ㢟ࡀ࠶ࡿࡇ࡜ࡀࢃ࠿ࡗ
ࡓ㸬ࡲࡓ㸪(2)⮬ື᳨ᰝࢩࢫࢸ࣒ࡣᑟධࢥࢫࢺࡸ㐠⏝ࢥࢫࢺࡀ⭾኱࡛㸪᥇⟬ࡀྜ࠺࠿࡝࠺࠿ࡀ୙☜ᐇ࡞ࡶࡢ࡟ᑐࡋ࡚タഛᢞ㈨࡟㋃ࡳษࢀ࡞࠸࡜࠸࠺⤒῭ⓗ࡞ၥ㢟ࡶ࠶ࡿࡇ࡜ࡀࢃ
࠿ࡗࡓ㸬ࡉࡽ࡟㸪(3)⮬ື᳨ᰝࢩࢫࢸ࣒ࢆᑟධࡍࡿ㝿࡟ࡣ㸪᳨ᰝࡍࡿ〇ရࡸ᳨ฟࡍ࡭ࡁḞⅬ࡟ྜࢃࡏ࡚Ⰻရ࡜୙Ⰻရࢆ
ุูࡍࡿࡓࡵࡢ≉ᚩⅬ࣭≉ᚩ㔞ࢆᐃ⩏ࡋ㸪㐠⏝ࡢ୰࡛ᚲせ࡟ᛂࡌ࡚ࡑࢀࡽࢆ෌ᐃ⩏ࡍࡿ࡜࠸ࡗࡓヨ⾜㘒ㄗࡀᚲせ࡜࡞ࡿࡀ㸪⏕⏘⌧ሙ࡛ᚑ஦ࡉࢀ࡚࠸ࡿ᪉ࠎࡣᚲࡎࡋࡶࢩࢫࢸ࣒㛤Ⓨ࡟⢭㏻ࡋ࡚࠸࡞࠸ሙྜࡀከࡃ㸪ࡇࢀࡀ⮬ື໬᥎㐍ࡢᘢᐖ࡟࡞ࡗ࡚࠾ࡾ㸪ᐇ㐠⏝ୖࡢၥ㢟ࡀ࠶ࡿࡇ࡜ࡶࢃ࠿ࡗࡓ㸬
௨ୖࡢ(1)㹼(3)ࡢၥ㢟Ⅼ࡟ᑐࡋ࡚㸪ḞⅬࡢ᥈⣴ࣉࣟࢭࢫࡢࡳࡢ⮬ື໬㸦ุูࣉࣟࢭࢫ௨㝆ࡣసᴗ⪅ࡀᚑ஦㸧ࢆ᝿ᐃࡋ㸪୍⯡ⓗ࡞ỗ⏝࣓࢝ࣛࡸ PC ࡢࡳࢆ⏝࠸࡚㸪ࢩࢫࢸ࣒㛤Ⓨ࡟㛵ࡋ࡚≉ู࡞▱㆑ࡸᢏ⾡ࢆ᭷ࡉ࡞࠸᪉ࠎ࡛ࡶⰋရ࡜୙Ⰻရࡢ〇ရ⏬ീࢆ‽ഛࡍࡿࡇ࡜࡛ᢅ࠼ࡿࢩࢫࢸ࣒ࡀ㛤Ⓨ࡛ࡁࢀ

Fig.2 State of the subject experiment 㻌఼ܿ‫ݗ‬ड़ིʁ ఼ܿ‫ݗ‬ड़ིʁ ఼ܿ‫ݗ‬ड़ིʁߑଆʀ‫ܙ‬য়͹෵ࡸ੓ࡢ」㞧ᛶ࡟ᛂࡌ࡚㐺ṇ࡞᳨ᰝ⎔ቃࡸ᳨ᰝ᪉ἲࢆタィࡍࡿᚲせࡀ࠶ࡿ࡜⪃࠼ࡽࢀࡿࡀ (26)㸪ࡑࡢࡓࡵ࡟ᚲせ࡞᳨ᰝᑐ㇟㠃ࢆホ౯ࡍࡿᣦᶆࡀᏑᅾࡋ࡚࠾ࡽࡎ㸪ከ✀ከᵝ࡞ᕤᴗ〇ရ࡟㐺⏝ྍ⬟࡞సᴗタィࡢ᪉ἲㄽࡢ☜❧ࡀᅔ㞴࡛࠶ࡗࡓ (27)㸬
᳨ᰝᑐ㇟ࡢ」㞧ᛶࡀḞⅬ᳨ฟ࡟ཬࡰࡍᙳ㡪࡟㛵ࡍࡿ⿕㦂⪅ᐇ㦂 ᳨ᰝᑐ㇟ࡢ」㞧ᛶ࡟ཬࡰࡍせᅉࢆ⥙⨶ⓗ࡟ᩚ⌮ࡋࡓୖ࡛㸪ࡑࢀࡽࢆᐇ㦂せᅉ࡜ࡍࡿ⿕㦂⪅ᐇ㦂ࢆᅗ 2 ࡟♧ࡍࡼ࠺࡟ᐇ
᪋ࡋ㸪ࡑࢀࡽࡀ᳨ᰝ⢭ᗘ࡟ཬࡰࡍᙳ㡪ࢆ᳨ウࡋࡓ㸬᳨ᰝᑐ㇟ࡢ」㞧ᛶࡢホ౯ᣦᶆࡢ⪃᱌ ᐇ㦂ࡢ⤖ᯝ㸪Ⰽࡢ」㞧ᛶ㸦᧜ᙳࡋࡓᕤᴗ〇ရࡢ⏬⣲್ࡢᖹᆒ᝟ሗ㔞ࢆ♧ࡍᣦᶆ࡛࠶ࡿ᝟ሗ࢚ࣥࢺࣟࣆ࣮ࡢ್㸧࡜ᵓ㐀࣭ᙧ≧ࡢ」㞧ᛶ㸦᧜ᙳࡋࡓᕤᴗ〇ရࡢ⏬⣲್ࡢ⃰ῐ㠃ࡢኚ໬ࡸᙧ≧ࡢ⢒ࡉ㸪ࢸࢡࢫࢳࣕࡢ」㞧ᛶࢆ♧ࡍࣇࣛࢡࢱࣝḟඖࡢ್㸧ࡀ᳨ᰝ⢭ᗘ࡟᭷ព㸦5%Ỉ‽㸧࡟ᙳ㡪ࢆཬࡰࡍࡇ࡜ࢆ☜ㄆࡋࡓ㸦ᅗ 3㸧㸬ලయⓗ࡟ࡣ㸪ࡇࢀࡽࡢ 2 ࡘࡢホ౯ᣦᶆ࡛ホ౯ྍ⬟࡛㸪」㞧ᛶࡀ㧗ࡃ࡞ࡿ࡜㸪ḞⅬ᳨ฟ⋡ࡶẁ㝵ⓗ࡟పࡃ࡞ࡿࡇ࡜ࢆ♧ࡋࡓ㸬ࡇࢀࡽࡢᐇ㦂⤖ᯝࡼࡾ㸪ከ✀ከᵝ࡞ᕤᴗ〇ရࢆḞⅬ᳨ฟ
ࡢほⅬ࠿ࡽホ౯ࡍࡿࡇ࡜ࡀྍ⬟࡜࡞ࡾ㸪సᴗタィࡢ᪉ἲㄽࡢ☜❧࡟ྥࡅ࡚㔜せ࡞▱ぢࡀᚓࡽࢀ࡚࠸ࡿ㸬఼ܿ‫ݗ‬ड़ིʁ ఼ܿ‫ݗ‬ड़ིʁ ఼ܿ‫ݗ‬ड़ིʁʀ‫ࠬݗ‬ଲে͹෵ࡸ੓ͺ͞͹2࣢Ͳ඲ՃՆ೵ʀ෵ࡸ੓͗߶͚͵Ζͳɼ఼ܿ‫ݗ‬ड़ི΍ஊ֌దͶఁ͚͵Ζ఼ܿ‫ݗ‬ड़ིʁ ఼ܿ‫ݗ‬ड़ིʁ ఼ܿ‫ݗ‬ड़ིʁ৯͹෵ࡸ੓

Fig.3 Relationship between color complexity,structure / shape complexity and inspection accuracy 㻌ࡤ㸪ከࡃࡢእほ᳨ᰝᕤ⛬࡛⮬ື໬ࡢ᳨ウࡀ᥎㐍࡛ࡁࡿྍ⬟ᛶࡀ࠶ࡿ࡜⪃࠼ࡓ㸬సᴗᨭ᥼ࢩࢫࢸ࣒ࡢ㛤Ⓨ࡜᭷ຠᛶࡢ᳨ドᐇ㦂 ᕤᴗ〇ရࢆࣔࢹࣝ໬ࡋࡓ 6 ✀㢮ࡢḞⅬ⏬ീࢆᑐ㇟࡜ࡋ㸪᥈⣴ࣉࣟࢭࢫ࡟ᑐࡋ࡚㸪ࡑࡢసᴗࢆᨭ᥼ࡍࡿࢩࢫࢸ࣒ࡢ㛤Ⓨࢆ⾜ࡗࡓ㸬ලయⓗ࡟ࡣ㸪సᴗ⪅ࡀ᳨ᰝࡍࡿ๓࡟࣓࡛࢝ࣛ〇ရࡢ⏬ീࢆ᧜ᙳࡋ㸪Ꮫ⩦῭ࡳࢿࢵࢺ࣮࣡ࢡࢆ⤒࡚Ⰻရ࠿୙Ⰻရ࠿ࡢุูࢆ⾜࠺࡜࡜ࡶ࡟㸪సᴗ⪅࡬ุู⤖ᯝ࡜ࡑࡢ᰿ᣐࢆ Grad-CAM ࡢᢏ⾡ (30)ࢆ⏝࠸࡚ྍど໬ࡍࡿసᴗᨭ᥼ࢩࢫࢸ࣒ࢆ㛤Ⓨࡋࡓ㸦ᅗ 4㸧㸬ࡲ ࡓ 㸪 Ⰻ ရ ⏬ ീ 300 ᯛ ࡜ ୙ Ⰻ ရ ⏬ ീ 300 ᯛ ࢆ Deep
Learning ࡢᢏ⾡ࢆ⏝࠸࡚Ꮫ⩦ࡋ㸪Ꮫ⩦῭ࡳࢿࢵࢺ࣮࣡ࢡࢆᵓ⠏ࡋ㸪సᴗᨭ᥼ࢩࢫࢸ࣒ࢆ⏝࠸࡞࠸࡛඲࡚ே㛫ࡀ᳨ᰝࡍࡿሙྜ࡜㸪సᴗᨭ᥼ࢩࢫࢸ࣒ࢆ⏝࠸࡚ Grad-CAM ࡢ⏬ീࡢࡳࢆᥦ♧ࡍࡿሙྜ㸪࠾ࡼࡧ Grad-CAM ࡢ⏬ീ࡜ุᐃ⤖ᯝࡢ୧᪉ࢆᥦ♧ࡍࡿሙྜࡢ 3 ࡘࡢ᮲௳ࢆᐇ㦂せᅉ࡜ࡍࡿ⿕㦂⪅ᐇ㦂ࢆᐇ᪋ࡋ㸪ࡑࢀࡽࡀ᳨ᰝ⢭ᗘࡸ᳨ᰝ᫬㛫࡟ཬࡰࡍᙳ㡪ࢆ᳨ウࡋࡓ㸬
సᴗᨭ᥼ࢩࢫࢸ࣒ࡢ᭷ຠᛶࡢ᳨ド⤖ᯝ ᐇ㦂ࡢ⤖ᯝ㸪᳨ᰝ⢭ᗘࡣసᴗᨭ᥼ࢩࢫࢸ࣒ࢆ⏝࠸࡞࠸ሙྜࡀ 80.80%࡛࠶ࡗࡓࡢ࡟ᑐࡋ࡚㸪సᴗᨭ᥼ࢩࢫࢸ࣒ࢆ⏝࠸࡚ Grad-CAM ࡢ⏬ീࡢࡳࢆᥦ♧ࡍࡿሙྜࡀ 97.33%㸪GradCAM ࡢ⏬ീ࡜ุᐃ⤖ᯝࡢ୧᪉ࢆᥦ♧ࡍࡿሙྜࡀ 96.83%࡜
࡞ࡾ㸪సᴗᨭ᥼ࢩࢫࢸ࣒࡟ࡣ᳨ᰝ⢭ᗘࢆ 16%⛬ᗘྥୖࡉࡏ
ࡿຠᯝࡀ࠶ࡿࡇ࡜ࢆ♧ࡋࡓ㸦ᅗ 5㸧㸬ࡲࡓ㸪᳨ᰝ᫬㛫ࡣ࡝ࡢ᪉ἲ࡛ࡶྠ⛬ᗘ࡛࠶ࡗࡓࡓࡵ㸪సᴗᨭ᥼ࢩࢫࢸ࣒ࢆ⏝࠸ࡿ

83

Designシンポジウム2021 講演論文集㻌੣඾͹ླྀΗ੣඾̥-3֋൅ͪ͢ࡠ‫ࢩۂ‬ԋεητϞ͹ླྀΗ

੣඾̥-2ࡠ‫ंۂ‬͹‫ࠬݗ‬͹ླྀΗ੣඾̥-1੣඾̥֋൅ͪ͢ࡠ‫ࢩۂ‬ԋεητϞ

Step1: ੣඾͹ժ଀ΝࡳӪҡ৙඾͹Ն೵੓͍Εʄʄ֚౲՗ॶͶ஭қʄʄΩϟϧ෾ੵ༽PC

Step2: ੣඾͹ժ଀Ν෾ੵ

Step5: ҡ৙՗ॶ͹ΊΝࡠ‫ࠬݗ͗ंۂ‬৚ๅ఑ࣖ༽υΡηϕϪ΢

Step3: ҡ৙՗ॶΝՆࢻԿࡠ‫ंۂ‬

Step4: ҡ৙՗ॶΝࡠ‫֮͗ंۂ‬೟

Fig.4 Overview of the developed work support system 㻌 ࡇࢀࡲ࡛࡟᥎㐍ࡋࡓ◊✲ࡼࡾ㸪እほ᳨ᰝࡢసᴗタィ࡜⮬ື໬࡟ྥࡅࡓከࡃࡢ▱ぢ࡜௒ᚋࡢㄢ㢟ࡀ᫂ࡽ࠿࡟࡞ࡾࡘࡘ࠶ࡿ㸬௒ᚋࡣᅗ  ࡟♧ࡍ㏻ࡾ㸪ྛ◊✲ࢸ࣮࣐࡟ࡉࡽ࡞ࡿㄢ㢟ࢆタᐃࡋ㸪◊✲┠ⓗࢆ㐩ᡂࡍࡿࡓࡵ࡟ᘬࡁ⥆ࡁ◊✲ࢆ᥎㐍ࡍࡿணᐃ࡛࠶ࡿ㸬ྛ◊✲ࢸ࣮࣐ࡢලయⓗ࡞◊✲ィ⏬࡜ࡋ࡚㸪>@᳨ᰝᑐ㇟ࡢホ౯᪉ἲ࡟㛵ࡍࡿ᳨ウ࡟㛵ࡋ࡚ࡣ㸪ࡇࢀࡲ࡛࡟⪃᱌ࡋࡓᕤᴗ〇ရ࡜ḞⅬࡢホ౯ᣦᶆࢆࡶ࡜࡟㸪ே㛫࡜>@࡛㛤Ⓨࡋࡓ⮬ື᳨ᰝࢩࢫࢸ࣒ࡢ᳨ᰝ⢭ᗘ᳨࣭ᰝຠ⋡ࢆẚ㍑ࡍࡿࡇ࡜࡛㸪ே㛫࣭ᶵᲔࡢศᴗ᪉ἲ࡟㛵ࡍࡿ◊✲ࢆ᥎㐍ࡍࡿ㸬>@᳨ᰝ⎔ቃࡢタィ࡟㛵ࡍࡿ᳨ウ࡟㛵ࡋ࡚ࡣ㸪ࡇࢀࡲ࡛࡟ᚓࡽࢀࡓ◊✲ࢹ࣮ࢱࢆ⤫ྜࡋ㸪⥲ྜⓗ࡞సᴗタィࡢ᪉ἲㄽࡢᵓ⠏࡟㛵ࡍࡿ◊✲ࢆ᥎㐍ࡍࡿ㸬>@᳨ᰝ⪅ࡢ᳨ᰝ᪉ἲࡢタィ࣭カ⦎࣭⟶⌮࡟㛵ࡍࡿ᳨ウ࡟㛵ࡋ࡚ࡣ㸪ࡇࢀࡲ࡛࡟ᚓࡽࢀࡓ◊✲ࢹ࣮ࢱࢆ⤫ྜࡋ㸪⥲ྜⓗ࡞సᴗタィࡢ᪉ἲㄽࡢᵓ⠏࡟㛵ࡍࡿ◊✲㸪࠾ࡼࡧᐇ㝿ࡢእほ᳨ᰝᕤ⛬࡛ࡢカ⦎ࢩࢫࢸ࣒࣭⟶⌮ࢩࢫࢸ࣒ࡢᐇド◊✲ࢆ᥎㐍ࡍࡿ㸬>@⮬ື᳨ᰝࢩࢫࢸ࣒ࡢ㛤Ⓨ࡟㛵ࡍࡿ᳨ウ࡟㛵ࡋ࡚ࡣ㸪ࡇࢀࡲ࡛ࣔࢹࣝ⏬ീࢆ⏝࠸᳨࡚ウࡋࡓ⮬ື᳨ᰝࢩࢫࢸ࣒ࡢ▱ぢࢆࡶ࡜࡟㸪ᐇ〇ရࡢ⏬ീࢆ⏝࠸ࡓᐇド◊✲ࡸᑡ࡞࠸ධຊ⏬ീ᳨࡛ᰝ⢭ᗘࢆྥୖࡉࡏࡿ᪉ἲ࡟㛵ࡍࡿ◊✲㸪ྍどග⥺ࡔࡅ࡛࡞ࡃ㸪⣸እ⥺ࡸ㉥እ⥺࡞࡝ࡢ≉ᛶࡢ␗࡞ࡿ࣓࡛࢝ࣛ᧜ᙳࡋࡓ⏬ീࡢ᭷ຠᛶ࡟㛵ࡍࡿ◊✲ࢆ᥎㐍ࡍࡿ㸬௨ୖࡢࡼ࠺࡟㸪௒ᚋࡶྛ◊✲ࢸ࣮࣐࡟ࡘ࠸࡚◊✲ࢆ᥎㐍

84֋൅ͪ͢ࡠ‫ࢩۂ‬ԋεητϞͶͺ఼ܿ‫ݗ‬ड़ིΝ޴৏ͦ͠ΖްՎ͍͗Ζ఼ܿ‫ݗ‬ड़ི

100
90
80

80.80

97.33

96.83

‫ؔ࣎ࠬݗ‬
1.02

1.2
1.10

10.98

70

0.8

60
500.6

‫[ؔ࣎ࠬݗ‬s]௒ᚋࡢ◊✲ィ⏬఼ܿ‫ݗ‬ड़ི[%]ሙྜࡶ᳨ᰝຠ⋡ࡣపୗࡋ࡞࠸ࡇ࡜ࡀࢃ࠿ࡗࡓ㸬ࡉࡽ࡟㸪ᐇ㝿ࡢ〇ရ࡟㐺⏝ࡍࡿࡓࡵ࡟ࡣ㸪Ꮫ⩦࡟኱㔞ࡢධຊ⏬ീࡀᚲせ࡜࡞ࡿ࡜࠸࠺᪂ࡓ࡞ㄢ㢟ࡶ᫂ࡽ࠿࡟࡞ࡗࡓ㸬ࡑࡇ࡛⌧ᅾࡣ㸪ᐇ㝿ࡢḞⅬ࡟ࡣගࡢᙜ࡚᪉࡟ࡼࡗ࡚どㄆᛶࡀኚ໬ࡍࡿ࡜࠸࠺≉ᚩ࡟╔┠ࡋ㸪ẚ㍑ⓗᑡ㔞ࡢ㉁ࡢ㧗࠸ධຊ⏬ീࡢࡳࢆ⏝࠸࡚Ꮫ⩦῭ࡳࢿࢵࢺ࣮࣡ࢡࢆᵓ⠏ࡍࡿࡇ࡜࡛㸪㛤Ⓨࡋࡓసᴗᨭ᥼ࢩࢫࢸ࣒ࡢ㐺⏝ྍ⬟⠊ᅖࢆᣑ኱ࡍࡿࡇ࡜ࢆヨࡳ࡚࠸ࡿ㸬

40

0.4

30
200.2100ࡠ‫ࢩۂ‬ԋεητϞ͵͢ ࡠ‫ࢩۂ‬ԋεητϞ͍Ε ࡠ‫ࢩۂ‬ԋεητϞ͍Εʤ݃Վනࣖ͵͢ʥ0ʤ݃Վන͍ࣖΕʥ‫ंࠬݗ‬͹‫ࠬݗ‬๏๑

Fig.5 Verification result of the effectivenessof the work support system 㻌ࡋ㸪ᚓࡽࢀࡓ⤖ᯝ࡞࡝࡟ࡘ࠸࡚ࡣ✚ᴟⓗ࡟Ⓨ⾲ࡍࡿࡇ࡜ࢆ⪃࠼࡚࠸ࡿࠋㅰ  ㎡ ᮏ◊✲ࢆᐇ᪋ࡍࡿ࡟࠶ࡓࡾ㸪ᐇ㝿ࡢእほ᳨ᰝࡢࣇ࢕࣮ࣝࢻࢆᥦ౪ࡋ࡚࠸ࡓࡔࡁ㸪ᐇែㄪᰝࡸᐇ㦂࡟ࡈ༠ຊ࠸ࡓࡔ࠸ࡓ〇㐀ᴗࡢⓙᵝ࡟ឤㅰࡢពࢆ⾲ࡍࡿࠋࡲࡓ㸪ᮏ◊✲ࡢ୍㒊ࡣ -636 ⛉◊㈝ⱝᡭ◊✲㸦.㸧࡜㟁Ẽ㏻ಙ኱Ꮫࠕ◊✲ࡢ㐃ᦠ࣭⤫ྜ໬➼࡟ࡼࡿᮏᏛࡢᶵ⬟ᙉ໬࡟ಀࡿྲྀ⤌ᨭ᥼㸸ᶵᲔᏛ⩦࡜ࢫ࣐࣮ࢺࢹࣂ࢖ࢫࢆ⼥ྜࡋࡓࢧࢫࢸࢼࣈࣝ⏕⏘ᨭ᥼ࢩࢫࢸ࣒ࡢ࢖ࣀ࣮࣋ࢩࣙࣥ࡟㛵ࡍࡿ◊✲ࠖࡢຓᡂࢆཷࡅࡓࡶࡢ࡛࠶ࡿࠋ


Designシンポジウム2021 講演論文集㻌‫ͤࠬݗ‬Ζ‫ࠬݗ‬ଲেͶ߻Κͦͪ‫ڧ؂ࠬݗ‬͹અ‫ܯ‬‫ڧ؂ࠬݗ‬[2]‫ڧ؂ࠬݗ‬͹અ‫ܯ‬Ͷ‫ͤؖ‬Ζ‫ݗ‬౾
[2-3]͞ΗΉͲ͹‫ڂݜ‬υʖνΝ౹߻ͪ͢૱߻ద͵ࡠ‫ۂ‬અ‫ܯ‬͹๏๑࿨͹ߑ஛Ͷ‫ͤؖ‬Ζ‫ڂݜ‬‫ࠬݗ‬ଲে[1]‫ࠬݗ‬ଲে͹඲Ճ๏๑Ͷ‫ͤؖ‬Ζ‫ڂݜ‬[1-3]‫ࠬݗ‬ଲেͳ఼ܿ͹ಝ௅Ͷ‫ͪ͏Ͱخ‬ਕؔʀ‫ؽ‬փͶ෾‫ۂ‬๏๑Ͷ‫ͤؖ‬Ζ‫ڂݜ‬‫ࠬݗ‬ϕϫιη‫݃ࠬݗ‬Վనਜ਼͵֐؏‫ۂࡠࠬݗ‬͹ࣰ‫ݳ‬[3]‫ंࠬݗ‬͹‫ࠬݗ‬๏๑͹અ‫ܯ‬ʀ‫܉‬࿇ʀ؇ཀྵͶ‫ͤؖ‬Ζ‫ݗ‬౾‫ͤࠬݗ‬Ζ‫ࠬݗ‬ଲেͶ߻Κͦͪ‫ࠬݗ‬๏๑͹અ‫ܯ‬[3-4]͞ΗΉͲ͹‫ڂݜ‬υʖνΝ౹߻ͪ͢૱߻ద͵ࡠ‫ۂ‬અ‫ܯ‬͹๏๑࿨͹ߑ஛Ͷ‫ͤؖ‬Ζ‫ڂݜ‬[3-5]ࣰࡏ͹֐؏‫޽ࠬݗ‬ఖͲ͹‫܉‬࿇εητϞʀ؇ཀྵεητϞ͹ࣰৄ‫ڂݜ‬

ʀྒྷ඾/෈ྒྷ඾൓พིʀ‫ؔ࣎ࠬݗ‬͹޴৏

[4]ࣙಊ‫ࠬݗ‬εητϞ͹֋൅Ͷ‫ͤؖ‬Ζ‫ݗ‬౾
[4-3]ࣰ੣඾͹ժ଀Ν༽͏ࣰͪৄ‫ڂݜ‬[4-4]ঙ͵͏೘ྙժ଀Ͳ‫ࠬݗ‬੠ౕΝ޴৏ͦ͠ Ζ๏๑Ͷ‫ͤؖ‬Ζ‫ڂݜ‬[4-5]ಝ੓͹ҡ͵ΖΩϟϧͲࡳӪͪ͢ժ଀͹༙ް੓Ͷ‫ͤؖ‬Ζ‫ڂݜ‬ࣙಊ‫ࠬݗ‬εητϞ‫ंࠬݗ‬Fig.6 Overview of future research plans㻌ᩥ  ⊩(1) Druty, C. G., et al.: Improving Visual Inspection Using
Binocular Rivalry, International Journal of Production
Research, Vol. 39, No. 10, pp. 2143-2153, 1986(2) ⤒῭⏘ᴗ┬: 2020 ᖺᗘ∧ࡶࡢ࡙ࡃࡾⓑ᭩, 2020
https://www.meti.go.jp/report/whitepaper/mono/2020/honb
un_pdf/index.html (ཧ↷ 2020-12-26)(3) Megaw E. D., et al.: Eye Movements and Industrial
Inspection, Applied Ergonomics, Vol. 10, No. 3, pp. 145-154,
1979(4) Nickles G. M., et al.: A Comparison of Three Levels ofTraining Designed to Promote Systematic Search Behavior
in Visual Inspection, International Journal of Industrial
Ergonomics, Vol. 32, pp. 331-339, 2003
(5) Chang J. J., et al.: The Development of a Training Expert
System for TFT-LCD Defects Inspection, International
Journal of Industrial Engineering: Theory, Applications andPractice, Vol. 16, No. 1, pp. 41-50, 2009
(6) Krzysztof K., et al.: Evaluating and Improving theEffectiveness of Visual Inspection of Products from theAutomotive Industry, Advances in Manufacturing II, pp.
231-243, 2019(7) ᩪ⸨ࡴࡽᏊ: ┠ど᳨ᰝసᴗ࡜⑂ປ, ࠿ࡽࡔࡢ⛉Ꮫ, Vol.
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