Production Process Optimization
based on
Defect Early Warning
Online early warning / closed-loop control of production
process. Firstly, select a defect and establish the
correlation between the defect and parameters for process,
product and equipment. Once the defect is predicted based on
the online model: (1) the Online Early Warning system prompts
the on-site operators to take measures to avoid the defect;
(2) If the defect is found in the on-line monitoring of the
product, or the defect is predicted based on the on-line
model, when the data is sufficient, the system can judge which
of the parameters causes the defect, so the system will make
sure
the same defect will not appear twice by adjusting the
production parameters of the front end!
Establishment of defect prediction model.
Even
if there is online defect measurement, the possible parameter
combination is limited. When the defect is measured, the loss
has already been caused! We want to predict the possible
defect before the defect actually exists! Therefore, the defect prediction model
for production line is always needed! When there is online
measurement, the defect prediction model can be crated more
accurately.
The model needs on-line data for real-time self-learning
optimization. On the one hand, its accuracy is continuously
improved, on the other hand, it also keeps up with the
continuous update of production line technology, products and
equipment.
Production process optimization.
Common optimization includes:
(1) online tracking of defect value change; (2) Defect early
warning (table display and curve display); (3) Automatic
formation of optimal combination value of process parameters
and equipment parameters.
The following is the overall functional architecture of
manufacturing optimization, guidance and execution system
development based on SCADA:
-
Intelligent diagnosis and control system for
product quality (data model diagnosis optimization)
-
Near / remote diagnosis and pre maintenance
system of equipment quality (data model diagnosis
optimization)
-
Diagnostic optimization system for production efficiency
(data model diagnosis optimization)
-
Standardized development of data information
collection template (model data standardization)
-
Robot configuration quick development platform
(primary system → Level 2)
-
Establishment of communication standard protocol based on
OPC-UA (automatic OPC)
-
Whole process simulation and feasibility
identification system of products (data model diagnosis
optimization)
-
Etc.
Defect Warning System Series
Development case of lithium
battery defect early warning system
Function and application of defect early warning system
products
Customer requirements of defect early warning system
Technical consultation of defect data based on Prediction
Production process optimization based on defect early warning
Introduction to defect early
warning system technology
Planning &
Consulting
Biz discuss, Planning, Maturity,
Consulting Area,
Predict Maint.
Defect
Early Warning, Models, Manufacturing, Li-Battery, Steel
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