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Extract from the Register of European Patents

EP About this file: EP3705964

EP3705964 - A METHOD FOR THE SCALABLE REAL-TIME STATE RECOGNITION OF PROCESSES AND/OR SUB-PROCESSES DURING PRODUCTION WITH ELECTRICALLY DRIVEN PRODUCTION PLANTS [Right-click to bookmark this link]
StatusNo opposition filed within time limit
Status updated on  29.09.2023
Database last updated on 31.08.2024
FormerThe patent has been granted
Status updated on  21.10.2022
FormerGrant of patent is intended
Status updated on  23.06.2022
FormerExamination is in progress
Status updated on  24.09.2021
FormerRequest for examination was made
Status updated on  12.03.2021
FormerThe application has been published
Status updated on  07.08.2020
Most recent event   Tooltip14.06.2024Lapse of the patent in a contracting state
New state(s): MC		published on 17.07.2024  [2024/29]
Applicant(s)For all designated states
Technische Universität Berlin
Strasse des 17. Juni 135
10623 Berlin / DE
[2020/37]
Inventor(s)01 / EMEC, Soner
Alt-Moabit 43
10555 Berlin / DE
 [2020/37]
Representative(s)Hertin und Partner Rechts- und Patentanwälte PartG mbB
Kurfürstendamm 54/55
10707 Berlin / DE
[2020/37]
Application number, filing date20153765.127.01.2020
[2020/37]
Priority number, dateDE20191010536904.03.2019         Original published format: DE102019105369
DE2019100183806.03.2019         Original published format: DE102019001838
[2020/37]
Filing languageEN
Procedural languageEN
PublicationType: A1 Application with search report 
No.:EP3705964
Date:09.09.2020
Language:EN
[2020/37]
Type: B1 Patent specification 
No.:EP3705964
Date:23.11.2022
Language:EN
[2022/47]
Search report(s)(Supplementary) European search report - dispatched on:EP28.07.2020
ClassificationIPC:G05B19/418
[2020/37]
CPC:
G05B19/4184 (EP); G05B2219/34465 (EP); Y02P90/02 (EP);
Y02P90/80 (EP)
Designated contracting statesAL,   AT,   BE,   BG,   CH,   CY,   CZ,   DE,   DK,   EE,   ES,   FI,   FR,   GB,   GR,   HR,   HU,   IE,   IS,   IT,   LI,   LT,   LU,   LV,   MC,   MK,   MT,   NL,   NO,   PL,   PT,   RO,   RS,   SE,   SI,   SK,   SM,   TR [2021/15]
Former [2020/37]AL,  AT,  BE,  BG,  CH,  CY,  CZ,  DE,  DK,  EE,  ES,  FI,  FR,  GB,  GR,  HR,  HU,  IE,  IS,  IT,  LI,  LT,  LU,  LV,  MC,  MK,  MT,  NL,  NO,  PL,  PT,  RO,  RS,  SE,  SI,  SK,  SM,  TR 
TitleGerman:VERFAHREN ZUR SKALIERBAREN ECHTZEITZUSTANDSERKENNUNG VON PROZESSEN UND/ODER TEILPROZESSEN BEI DER HERSTELLUNG MIT ELEKTRISCH ANGETRIEBENEN PRODUKTIONSANLAGEN[2020/37]
English:A METHOD FOR THE SCALABLE REAL-TIME STATE RECOGNITION OF PROCESSES AND/OR SUB-PROCESSES DURING PRODUCTION WITH ELECTRICALLY DRIVEN PRODUCTION PLANTS[2020/37]
French:PROCÉDÉ DE RECONNAISSANCE D'ÉTAT ÉVOLUTIF EN TEMPS RÉEL DE PROCESSUS ET/OU DE SOUS-PROCESSUS PENDANT LA PRODUCTION AVEC DES INSTALLATIONS DE PRODUCTION À ENTRAÎNEMENT ÉLECTRIQUE[2020/37]
Examination procedure05.03.2021Amendment by applicant (claims and/or description)
05.03.2021Examination requested  [2021/15]
05.03.2021Date on which the examining division has become responsible
24.09.2021Despatch of a communication from the examining division (Time limit: M04)
21.01.2022Reply to a communication from the examining division
24.06.2022Communication of intention to grant the patent
18.10.2022Fee for grant paid
18.10.2022Fee for publishing/printing paid
18.10.2022Receipt of the translation of the claim(s)
Opposition(s)24.08.2023No opposition filed within time limit [2023/44]
Fees paidRenewal fee
17.01.2022Renewal fee patent year 03
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Responsibility for the accuracy, completeness or quality of the data displayed under the link provided lies entirely with the Unified Patent Court.
Lapses during opposition  TooltipAL23.11.2022
AT23.11.2022
CZ23.11.2022
DK23.11.2022
EE23.11.2022
ES23.11.2022
FI23.11.2022
HR23.11.2022
IT23.11.2022
LT23.11.2022
LV23.11.2022
MC23.11.2022
PL23.11.2022
RO23.11.2022
RS23.11.2022
SE23.11.2022
SI23.11.2022
SK23.11.2022
SM23.11.2022
IE27.01.2023
LU27.01.2023
BE31.01.2023
NO23.02.2023
GR24.02.2023
IS23.03.2023
PT23.03.2023
[2024/29]
Former [2024/26]AL23.11.2022
AT23.11.2022
CZ23.11.2022
DK23.11.2022
EE23.11.2022
ES23.11.2022
FI23.11.2022
HR23.11.2022
IT23.11.2022
LT23.11.2022
LV23.11.2022
PL23.11.2022
RO23.11.2022
RS23.11.2022
SE23.11.2022
SI23.11.2022
SK23.11.2022
SM23.11.2022
IE27.01.2023
LU27.01.2023
BE31.01.2023
NO23.02.2023
GR24.02.2023
IS23.03.2023
PT23.03.2023
Former [2024/08]AL23.11.2022
AT23.11.2022
CZ23.11.2022
DK23.11.2022
EE23.11.2022
ES23.11.2022
FI23.11.2022
HR23.11.2022
LT23.11.2022
LV23.11.2022
PL23.11.2022
RO23.11.2022
RS23.11.2022
SE23.11.2022
SI23.11.2022
SK23.11.2022
SM23.11.2022
IE27.01.2023
LU27.01.2023
BE31.01.2023
NO23.02.2023
GR24.02.2023
IS23.03.2023
PT23.03.2023
Former [2023/51]AL23.11.2022
AT23.11.2022
CZ23.11.2022
DK23.11.2022
EE23.11.2022
ES23.11.2022
FI23.11.2022
HR23.11.2022
LT23.11.2022
LV23.11.2022
PL23.11.2022
RO23.11.2022
RS23.11.2022
SE23.11.2022
SI23.11.2022
SK23.11.2022
SM23.11.2022
LU27.01.2023
BE31.01.2023
NO23.02.2023
GR24.02.2023
IS23.03.2023
PT23.03.2023
Former [2023/49]AL23.11.2022
AT23.11.2022
CZ23.11.2022
DK23.11.2022
EE23.11.2022
ES23.11.2022
FI23.11.2022
HR23.11.2022
LT23.11.2022
LV23.11.2022
PL23.11.2022
RO23.11.2022
RS23.11.2022
SE23.11.2022
SK23.11.2022
SM23.11.2022
LU27.01.2023
BE31.01.2023
NO23.02.2023
GR24.02.2023
IS23.03.2023
PT23.03.2023
Former [2023/43]AL23.11.2022
AT23.11.2022
CZ23.11.2022
DK23.11.2022
EE23.11.2022
ES23.11.2022
FI23.11.2022
HR23.11.2022
LT23.11.2022
LV23.11.2022
PL23.11.2022
RO23.11.2022
RS23.11.2022
SE23.11.2022
SK23.11.2022
SM23.11.2022
LU27.01.2023
NO23.02.2023
GR24.02.2023
IS23.03.2023
PT23.03.2023
Former [2023/38]AL23.11.2022
AT23.11.2022
CZ23.11.2022
DK23.11.2022
EE23.11.2022
ES23.11.2022
FI23.11.2022
HR23.11.2022
LT23.11.2022
LV23.11.2022
PL23.11.2022
RO23.11.2022
RS23.11.2022
SE23.11.2022
SK23.11.2022
SM23.11.2022
NO23.02.2023
GR24.02.2023
IS23.03.2023
PT23.03.2023
Former [2023/37]AL23.11.2022
AT23.11.2022
CZ23.11.2022
DK23.11.2022
EE23.11.2022
ES23.11.2022
FI23.11.2022
HR23.11.2022
LT23.11.2022
LV23.11.2022
PL23.11.2022
RO23.11.2022
RS23.11.2022
SE23.11.2022
SM23.11.2022
NO23.02.2023
GR24.02.2023
IS23.03.2023
PT23.03.2023
Former [2023/35]AT23.11.2022
CZ23.11.2022
DK23.11.2022
EE23.11.2022
ES23.11.2022
FI23.11.2022
HR23.11.2022
LT23.11.2022
LV23.11.2022
PL23.11.2022
RO23.11.2022
RS23.11.2022
SE23.11.2022
SM23.11.2022
NO23.02.2023
GR24.02.2023
IS23.03.2023
PT23.03.2023
Former [2023/34]AT23.11.2022
DK23.11.2022
EE23.11.2022
ES23.11.2022
FI23.11.2022
HR23.11.2022
LT23.11.2022
LV23.11.2022
PL23.11.2022
RS23.11.2022
SE23.11.2022
SM23.11.2022
NO23.02.2023
GR24.02.2023
IS23.03.2023
PT23.03.2023
Former [2023/33]AT23.11.2022
DK23.11.2022
ES23.11.2022
FI23.11.2022
HR23.11.2022
LT23.11.2022
LV23.11.2022
PL23.11.2022
RS23.11.2022
SE23.11.2022
SM23.11.2022
NO23.02.2023
GR24.02.2023
IS23.03.2023
PT23.03.2023
Former [2023/25]AT23.11.2022
ES23.11.2022
FI23.11.2022
HR23.11.2022
LT23.11.2022
LV23.11.2022
PL23.11.2022
RS23.11.2022
SE23.11.2022
NO23.02.2023
GR24.02.2023
IS23.03.2023
PT23.03.2023
Former [2023/23]AT23.11.2022
ES23.11.2022
FI23.11.2022
LT23.11.2022
LV23.11.2022
SE23.11.2022
NO23.02.2023
GR24.02.2023
PT23.03.2023
Former [2023/22]AT23.11.2022
ES23.11.2022
FI23.11.2022
LT23.11.2022
SE23.11.2022
NO23.02.2023
PT23.03.2023
Former [2023/20]LT23.11.2022
NO23.02.2023
Documents cited:Search[A]US2011288660  (WOJSZNIS WILHELM K [US], et al) [A] 1-17* paragraphs [0063] - [0119]; figures 3, 8-15 *;
 [X]CN108776276  (UNIV HEFEI TECHNOLOGY) [X] 1-17 * the whole document *;
 [X]  - WANG YULIN ET AL, "An analysis framework for characterization of electrical power data in machining", INTERNATIONAL JOURNAL OF PRECISION ENGINEERING AND MANUFACTURING, KOREAN SOCIETY FOR PRECISION ENGINEERING, SPRINGER, vol. 16, no. 13, doi:10.1007/S12541-015-0347-Z, ISSN 2234-7593, (20151208), pages 2717 - 2723, (20151208), XP035720013 [X] 1-17 * the whole document *

DOI:   http://dx.doi.org/10.1007/s12541-015-0347-z
by applicant   - "Making Time-series Classification More Accurate Using Learned Constraints", RATANAMAHATANA, C.A.KEOGH, E., Proceedings of the Fourth SIAM International Conference on Data Mining. Society for Industrial and Applied Mathematics, (20040000), pages 11 - 22
    - SAKOE, H.CHIBA, S., "Dynamic programming algorithm optimization for spoken word recognition", IEEE Transactions on Acoustics, Speech, and Signal Processing, (19780000), vol. 26, no. 1, pages 43 - 49, XP000647286
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