Presentation 2022-01-27
Improvement of work element estimation for forklift operator
Toshimasa Aso,
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Abstract(in Japanese) (See Japanese page)
Abstract(in English) This paper describes improvement of work element estimation for forklift operators, performance comparisons and implementation of automation to write operation reports. The improved estimation can detect getting on and out of a forklift and grey durations. This paper uses data measured in an actual warehouse and compares performance. The results show thatthe average matching rate increases by 5% to 89.3% and that the average error rate is reduced from 2.8% to 2.3%. This paper implements the automation to write operation reports in a cloud server to support visualization of work analysis.
Keyword(in Japanese) (See Japanese page)
Keyword(in English) forklift / work measurement / work element estimation
Paper # ICM2021-36,LOIS2021-34
Date of Issue 2022-01-20 (ICM, LOIS)

Conference Information
Committee LOIS / ICM
Conference Date 2022/1/27(2days)
Place (in Japanese) (See Japanese page)
Place (in English) Online
Topics (in Japanese) (See Japanese page)
Topics (in English) Practical Use of Lifelog, Office Information System, Business Management, etc.
Chair Toru Kobayashi(Nagasaki Univ.) / Kazuhiko Kinoshita(Tokushima Univ.)
Vice Chair Hiroyuki Toda(NTT) / Haruo Ooishi(NTT) / Eiji Takahashi(NEC)
Secretary Hiroyuki Toda(Nagasaki Univ.) / Haruo Ooishi(NTT) / Eiji Takahashi(Bosco)
Assistant Kazuki Fukae(Nagasaki Univ.) / Yoshifumi Kato(NTT)

Paper Information
Registration To Technical Committee on Life Intelligence and Office Information Systems / Technical Committee on Information and Communication Management
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Improvement of work element estimation for forklift operator
Sub Title (in English)
Keyword(1) forklift
Keyword(2) work measurement
Keyword(3) work element estimation
1st Author's Name Toshimasa Aso
1st Author's Affiliation Tokyo University of Marine Science and Technology(Tokyo Univ. of Marine Science and Technology)
Date 2022-01-27
Paper # ICM2021-36,LOIS2021-34
Volume (vol) vol.121
Number (no) ICM-354,LOIS-355
Page pp.pp.19-24(ICM), pp.19-24(LOIS),
#Pages 6
Date of Issue 2022-01-20 (ICM, LOIS)