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Decision support system for product quality development using on-line patent database
Tesavrita C.a, Suryadi K.b
a Industrial Engineering Department, Parahyangan Catholic University, Indonesia
b Industrial Engineering Department, Laboratory of Information System and Decision Making, Bandung Institute of Technology, 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]This research, proposes a model of decision support system for product quality development in idea generation phase. This model will use two forms of knowledge, tacit knowledge is gathered from expert opinions and explicit knowledge is gathered from on-line patent database. In this research cathecin (green tea) is used as a case study. The proposed model in this research is based on combination of data mining model from Dou and Manullang (2004) and Analytic Hierarchy Process Model by Chiu (2003). This model represents the data mining process for gathered patent data from on-line patent database and analyzes them as a resource (think tank) for innovative thinking in product’s idea generation. Based on those output, product mapping and technology mapping will be generated. After the patent analysis, some product and process alternative can be generated. Selection process for the best alternative uses AHP (Analytic Hierarchy Process) model. The AHP model that used in this research is modification from Chiu (2003) AHP model in patent valuation. Using this model, the best alternative for catechin’s product can be selected.[/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]Ahp,AHP (analytic hierarchy process),Catechin,Data mining process,Explicit knowledge,Innovative thinking,Patent analysis,Technology mapping[/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]Ahp,Catechin,Data mining,Innovation,Patent analysis[/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][/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]