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Developing a plant system prediction model for technology transfer
Yamane Y.a, Takahashi K.a, Hamada K.a, Morikawa K.a, Nur Bahagia S.b, Diawati L.b, Cakravastia A.b
a Faculty of Engineering, Hiroshima University, Higashi-Hiroshima, 739-8527, Japan
b Faculty of Industrial Technology, Bandung Institute of Technology, Bandung, 40132, Indonesia
[vc_row][vc_column][vc_row_inner][vc_column_inner][vc_separator css=”.vc_custom_1624529070653{padding-top: 30px !important;padding-bottom: 30px !important;}”][/vc_column_inner][/vc_row_inner][vc_row_inner layout=”boxed”][vc_column_inner width=”3/4″ css=”.vc_custom_1624695412187{border-right-width: 1px !important;border-right-color: #dddddd !important;border-right-style: solid !important;border-radius: 1px !important;}”][vc_empty_space][megatron_heading title=”Abstract” size=”size-sm” text_align=”text-left”][vc_column_text]© 2015 Elsevier B.V. All rights reserved.Technology transfer (TT) is the process of transferring skills, knowledge, technologies, methods of manufacturing, and facilities. Successful TT demands an integrated approach in order to plan, implement, evaluate and improve the transfer process comprehensively. For quantifying the technology level, various models have been developed and applied, however the total performance of a plant has not been quantified by the model. It is necessary to develop a mechanism of integrating the quantified technology level of each process into the total performance of the plant. This paper develops a plant system prediction model. In the model, a V-process model is utilized for defining the whole procedure for analyzing the plant system, and the technology level quantification model developed by Yamane, Y., Takahashi, K., Hamada, K., Morikawa, K., Nur Bahagia, S., Diawati, L., Cakravastia, A., 2011. Quantifying the technology level of production system for technology transfer. Ind. Eng. Manag. Syst., 10(2), 97-103 is utilized for quantifying the technology level of each process. Also, to integrate the quantified technology level into that of the plant system, some functions are formulated. A case study in a manufacturing industry shows the effectiveness of the developed model.[/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Author keywords” size=”size-sm” text_align=”text-left”][vc_column_text]Integrated approach,Learning curves,Management of technology,Manufacturing industries,Plant capacities,Production system,Quantification model,Total performance[/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Indexed keywords” size=”size-sm” text_align=”text-left”][vc_column_text]Learning curve,Management of technology,Plant capacity,Technology level[/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Funding details” size=”size-sm” text_align=”text-left”][vc_column_text][/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”DOI” size=”size-sm” text_align=”text-left”][vc_column_text]https://doi.org/10.1016/j.ijpe.2015.05.014[/vc_column_text][/vc_column_inner][vc_column_inner width=”1/4″][vc_column_text]Widget Plumx[/vc_column_text][/vc_column_inner][/vc_row_inner][/vc_column][/vc_row][vc_row][vc_column][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][/vc_column][/vc_row]