Digital Twin and IIoT in Optimizing Manufacturing Process and Quality Management
• IIoT , digital twin , industrial analytics are enabling technologies ( not applications by themselves ), most fitting for supporting a new generation data and analytics-driven industrial operation management applications .
• IoT , digital twin and industrial analytics technologies must be fused with proven management methodologies and best practice , such as Lean management and Six Sigma , to be truly effective to provide values to the industrial operation management settings . ( In other words , IoT or analytics decoupled from operation management only provides limited value .)
• IIoT , digital twin and industrial analytics technologies have great potential in advancing the digitalization of industrial operation management , in domains beyond equipment maintenance to include production process and product quality management ( as demonstrated in this article ), energy management ( as reported in our other article , see 4 , and possibly production planning and execution as well .
• Both equipment and product digital twins are effective methodology and technology to track product quality as the product being processed and to build product quality traceability records . Product digital twins in fact can be used to represent the value flows in the manufacturing floor .
• IIoT platform with a digital twin framework has been proven to greatly simplify the implementation of industrial operation management solutions that is secure , scalable and reliable .
ACKNOWLEDGEMENTS
The views expressed in the IIC Journal of Innovation are the contributing authors ’ views and do not necessarily represent the views of their respective employers nor those of the Industrial Internet Consortium .
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