Digital Twin and IIoT in Optimizing Manufacturing Process and Quality Management
Fig . 3-3 : Logical and information flows for quality exception handling to reduce wastes . furnace , etc . that come with different forms , such as trolley furnace , indoor furnace , ring furnace
etc . The configuration of the equipment is schematically illustrated in Fig . 3-4 . Each furnace can perform heat treatment of multiple products in production ( PiP ) at the same time . However , each of the PiP may be treated according to different process control requirements ( e . g ., under the same temperature but for different durations with strict temperature ramping up and down constraints ).
Each type of equipment deployed in a given process may be of different models with varying capability and capacity . All the equipment as a whole can be roughly considered as a node in matrix or a graph 9 in which each PiP moves through during the production process . Because special steel products have many varieties and are being made in small batches , with each product type needing to meet specific product specification and to be produced with specific process control parameters . Furthermore , multiple products are often being produced at the same time . Consequently , the production scheduling for each PiP is dynamic to maximizing equipment Overall Equipment Effectiveness ( OEE ) and production capacity . Therefore , each of
9 as a concept in computer science
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