Person:
KARATEPE MUMCU, YELDA

Profile Picture

Email Address

Birth Date

Research Projects

Organizational Units

OrgUnit Logo
Organizational Unit

Job Title

Last Name

KARATEPE MUMCU

First Name

YELDA

Name

Filters

2012 - 201922020 - 20222
Reset filters

Settings

Search Results

Now showing 1 - 4 of 4
  • Thumbnail Image
    PublicationOpen Access
    Application of heuristic assembly line balancing methods to lighting automation industry
    (2022-12-01) KARATEPE MUMCU, YELDA; Karatepe Mumcu Y.
    The assembly line balancing problem is an important issue for every manufacturing company. A balanced assembly line ensures that a product is produced in the optimum time, and as a result of this effect, less machinery, materials and labour are used during this production. In this article, theoretical information about assembly line balancing has been given, and then the data needed for assembly line balancing has been obtained by making a time study of the production of Downlight Luminaire. With these data obtained, assembly line balancing was done and compared by using Hoffman and Comsoal methods. The aim of this study is to investigate the applicability of Hoffman and Comsoal methods, which are one of the heuristic assembly line balancing methods, in the assembly lines of the companies producing in the lighting sector.
  • No Thumbnail Available
    PublicationMetadata only
    The levels of awareness about the renewable energy sources of university students in Turkey
    (PERGAMON-ELSEVIER SCIENCE LTD, 2012) VARBAK NEŞE, SEÇİL; Karatepe, Yelda; Nese, Secil Varbak; Kecebas, Ali; Yumurtaci, Mehmet
    Concerns about fossil fuel consumption increase daily because of the limited nature of the reserves and its impact on the environment. Research and Development studies suggest an optimistic future for the use of renewable energy sources. To create such a bright future, however, renewable energy education must be quickly and efficiently spread to future generations. The current study explores Turkish university students' levels of awareness regarding renewable energy sources. For this purpose, a questionnaire was given to students in Turkish universities. The questionnaire comprised questions that address students' personal and demographic characteristics levels of awareness levels regarding renewable energy sources. The data obtained from the questionnaire were evaluated using the SPSS program. Finally, actions that should be taken to increase university students' awareness levels are described. (C) 2012 Elsevier Ltd. All rights reserved.
  • Thumbnail Image
    PublicationOpen Access
    Estimation of Screen Density According to Different Screening Methods With Artificial Neural Network Method in Flexo Printing System
    (GAZI UNIV, 2018-01-30) ÖZDEMİR, LUTFİ; Kurt, Mustafa Batuhan; Karatepe Mumcu, Yelda; Ozdemir, Lutfi
    Choice of dot shape is the most important factors that affect the printing quality in the flexographic printing system. The aim of the operations performed by the machine operator during the printing process (densitometric measurements, ink settings, etc.) is to achieve the same quality from the first printing to last printing. This study attempts to estimate screen density values obtained from the same polymer structure (DFR), 175 Lpi screening and 10 different screen structures using the Artificial Neural Networks method (ANN). Data necessary for calculations were obtained from real values as a result of experimental studies. The correlation coefficient of the data obtained from the model created with ANN for screen density values was found to be 98,902% and this value was found to be consistent with scientific values. According to the results, the neural network model used in flexographic printing systems of different screening methods predictable effect on the printing result.
  • Thumbnail Image
    PublicationOpen Access
    An application of Artificial Neural Network solution in the apparel industry for Job distribution to subcontractors
    (2022-10-01) KARATEPE MUMCU, YELDA; KAYAR, MAHMUT; Karatepe Mumcu Y., Kayar M., Bulur Ö. C.
    In this study, the results of the work distribution made with the TOPSIS method, which is frequently used in the distribution of work to the subcontractor workshops, were estimated using the Artificial Neural Networks Method (ANN). Here, the C* values used in the work distribution with the TOPSIS method were estimated by ANN. The correlation coefficient of the data obtained from the created model was found to be 99.99895% for learning. According to the results, it has been concluded that work distribution can be made by using the ANN method without making complex mathematical calculations in the distribution of work to the contract workshops.