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Development of real time machine tools component utilization data acquisition for developing dynamic model of maintenance scheduling
Harja H.B.a, Prakosa T.a, Yuwana Martawirya Y.a, Nurhadi I.b, Januartha A.S.b
a Department of Manufacturing Engineering, Politeknik Manufaktur Bandung, Bandung, 40135, Indonesia
b Department of Mechanical Engineering, Institut Teknologi Bandung, 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]© 2019 The Authors, published by EDP Sciences.Maintenance scheduling accuracy of CNC machine tools components should be calculated based on actual data utilization of each component. Actual usage of each component can be approached by component grouping based on machine operation phase utilization, which is divided into Power-On, cutting and noncutting phase. This paper describes a study on development of machine monitoring data utilization for obtaining real time information of spindle and machine axis positions as well as current consumption of spindle servo motor. Data collection was conducted by a termination method on wiring feedback control of spindle encoder signal and axes encoder signals. On the other hand, current consumption of spindle servo motor was measured by a CT current transducer. Afterward, a WEMOS microcontroller was used to process and to transfer data wirelessly to a Raspberry which acted as a broker. The data will used to update the data status of CNC Machine Tools utilization database, where it was communicated by using a MQTT protocol. A monitoring system has been developed and resulted the real time information of machine phase utilization. It will be further utilized as primary data input for building a dynamic maintenance 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]Component utilization,Current consumption,Current transducer,Dynamic maintenances,Machine data,Maintenance scheduling,Real time,Real-time information[/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]Data real time,Dynamic maintenance model,Machine data utilization[/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]This work was supported by Minister of Research, Technology and Higher Education of The Republic Indonesia for Doctoral Dissertation Research Project 2018 with contract number 23/PL11/PP/2018. The authors would like to thank them for the support.[/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/10.1051/e3sconf/201913001015[/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]