Digital Twin and IIoT in Optimizing Manufacturing Process and Quality Management
Fig . 3-2 : Information flow of data and analytic-driven total quality management supported by real time process control .
Fig . 3-1 , Fig . 3-2 and Fig . 3-3 illustrate some of the design ideas resulting from the Lean management and Six Sigma principles with regard to product process control and product quality management .
Most of the capabilities described above can and must be designed into and implemented in the software application to cement the methodology and best practice so they are exercised in the production processes largely automatically . The foundation of realizing most of these capabilities is data collection across all equipment and other operational systems involved in the production processes . On this basis , the project use software to comprehensively digitize the operation processes and procedures , enforcing to a large degree standardized operation workflow . It then leverages advanced analytics to help to optimize the operation management .
In a strong sense , the project leverages the power of data and analytics , and the capabilities of software to implement and enforce Lean management and Six Sigma principles , realizing a dataand analytic-driven digital Lean management and Six Sigma system for production process and product quality management .
3.2 Production Environment Configuration
The phase I of the project reported here limits its scope to a special steel plant , part of a larger steelmaking process , that consists of multiple heat treatment and forging processes and production lines that include electric furnace production line , electroslag furnace production line , double vacuum production line and forging production line . The furnace equipment involved includes electric arc furnace , induction furnace , refining furnace , conventional electroslag furnace , gas-protected electroslag furnace , vacuum induction furnace , vacuum consumable
IIC Journal of Innovation - 69 -