OPTIMIZATION OF THE PLASTIC INJECTION MOLDING … · 2020-07-04 · Florian Seybold, Steffen...
Transcript of OPTIMIZATION OF THE PLASTIC INJECTION MOLDING … · 2020-07-04 · Florian Seybold, Steffen...
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DATE: 18.06.2020 Florian Seybold, Steffen Aldinger
Alfred Kärcher SE & Co. KG
OPTIMIZATION OF THE PLASTIC INJECTION MOLDING PROCESS
AND COMPONENT QUALITY USING MOLDEX3D AND OPTISLANG
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KÄRCHER IS THE MARKET LEADER WORLDWIDE FOR CLEANING SOLUTIONS
Florian Seybold, Steffen Aldinger | Injection Molding Process Optimization using MOLDEX3D and optiSLang | June 2020 1
2.578 Billion € sales volume in 2019
65% Growth since
2010
85 % Foreign sales
We offer over 3000 products – almost all products include at least one molded part
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The goal is to find the balance between high quality and the lowest possible cost
HOW CAN WE OPTIMIZE THE INJECTION MOLDING PROCESS?
Florian Seybold, Steffen Aldinger | Injection Molding Process Optimization using MOLDEX3D and optiSLang | June 2020 2
• Construction of the plastic component
• Mold design
• Manufacturing process conditions
• Quality
Warpage
Surface Smoothness
etc.
• Costs
Machine operating cost and cycle time
etc.
INFLUENCING FACTORS
RESPONSE METRICS
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Function and costs define the optimization goals
EXAMPLE: OPTIMIZATION OF A BATTERY SLOT
Florian Seybold, Steffen Aldinger | Injection Molding Process Optimization using MOLDEX3D and optiSLang | June 2020 3
COMPONENT QUALITY REQUIREMENTS
1. Straight assembly surface
2. Straight battery slide
3. Screw dome position
ECONOMICAL REQUIREMENTS
Cycle time
1
3
2
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This allows the consideration of the component design, the mold design and the molding process at once
OUR WORKFLOW INTEGRATES MOLDEX3D AND CAD SOFTWARE
Florian Seybold, Steffen Aldinger | Injection Molding Process Optimization using MOLDEX3D and optiSLang | June 2020 4
Kärcher Software
Component
Design
• MOLDEX3D performs injection
molding simulations
• „Kärcher Software“ enables the
integration of MOLDEX3D
• More flexibility due to integrated
CAD Software
• Result: The workflow can
consider the entire development
and manufacturing process
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There are 38 geometry related non-dependent parameters
SETUP STEP 1: VARIATION OF THE COMPONENT DESIGN
Florian Seybold, Steffen Aldinger | Injection Molding Process Optimization using MOLDEX3D and optiSLang | June 2020 5
• Height
• Position and angle
• Thickness
VARIATION OF ADDITIONAL RIBS
• Position
• Thickness
VARIATION OF EXISTING RIBS
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Only the injection location is varied
SETUP STEP 2: VARIATION OF THE MOLD DESIGN
Florian Seybold, Steffen Aldinger | Injection Molding Process Optimization using MOLDEX3D and optiSLang | June 2020 6
• Injection position
• Also possible:
Cooling channel positions
Entire injection system
VARIATION OF THE MOLD DESIGN
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There are 14 manufacturing process related parameters
SETUP STEP 3: VARIATION OF THE MOLDING PROCESS CONDITIONS
Florian Seybold, Steffen Aldinger | Injection Molding Process Optimization using MOLDEX3D and optiSLang | June 2020 7
• Filling time
• Packing time
• Cooling time
• Temperature of the coolant
• etc.
Coolant
VARIATION OF MANUFACTURING PROCESS
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The warpage is probed at 32 locations
SETUP STEP 4: RESPONSE VALUES
Florian Seybold, Steffen Aldinger | Injection Molding Process Optimization using MOLDEX3D and optiSLang | June 2020 8
Root mean square of five groups:
• RMS warpage 1
• RMS warpage 2
• RMS warpage 3
• RMS warpage SD1
• RMS warpage SD2
WARPAGE PROBING
Group
SD 2
Group
SD 1
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To control the strong impact of cycle time the optimization is divided into two steps
• Single objective optimization
• Cycle time related parameters are held constant
• Optimization of the warpage
• Multiple objective optimization
• Only cycle time related parameters are varied
• Trade-off between warpage and cycle time
OPTIMIZATION STRATEGY
Florian Seybold, Steffen Aldinger | Injection Molding Process Optimization using MOLDEX3D and optiSLang | June 2020 9
#Design
Warpage
Cycle Time
Warpage
FIRST OPTIMIZATION SECOND OPTIMIZATION
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Cycle time related parameters are held constant
• 50 parameters in total
• 175 designs
• 137 successful designs (78%)
FIRST SENSITIVITY ANALYSIS
Florian Seybold, Steffen Aldinger | Injection Molding Process Optimization using MOLDEX3D and optiSLang | June 2020 10
RMS
warpage 1
RMS
warpage 2
RMS
warpage 3
RMS_warpage
SD 1
RMS_warpage
SD 2
COP MATRIX The CoP‘s of the first three groups
are good (≈90%)
The CoP‘s of the screw domes are
acceptable (≈70%)
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Cycle time related parameters are held constant
FIRST OPTIMIZATION
Florian Seybold, Steffen Aldinger | Injection Molding Process Optimization using MOLDEX3D and optiSLang | June 2020 11
• Single objective optimization for the warpage
objective function
• Evolutionary algorithm with standard settings
SINGLE OBJECTIVE OPTIMIZATION Objective of the best design:
0.64
Objective of the validated design:
0.78
Objective of the reference design:
2.20
Optimization Design
Ob
jecti
ve
Warp
ag
e
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Only cycle time related parameters are varied
SECOND SENSITIVITY ANALYSIS
Florian Seybold, Steffen Aldinger | Injection Molding Process Optimization using MOLDEX3D and optiSLang | June 2020 12
• 3 parameters in total
• 65 designs
• 62 successful designs (95%)
COP MATRIX The CoP‘s of the first three groups
are very good (>95%)
The CoP‘s of the screw domes are
acceptable (>60%)
RMS
warpage 1
RMS
warpage 2
RMS
warpage 3
RMS_warpage
SD 1
RMS_warpage
SD 2
Cycle time
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Only cycle time related parameters are varied
SECOND OPTIMIZATION
Florian Seybold, Steffen Aldinger | Injection Molding Process Optimization using MOLDEX3D and optiSLang | June 2020 13
• Multiple objective optimization for the warpage
objective function and the cycle time
• Evolutionary algorithm
MULTIPLE OBJECTIVE OPTIMIZATION Objective of the validated design:
0.62
Objective of the reference design:
2.20
Cycle time of the validated design:
32s
Cycle time of the reference design:
29s
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The warpage was strongly reduced while maintaining cycle time at an economically viable level
FINAL RESULTS
Florian Seybold, Steffen Aldinger | Injection Molding Process Optimization using MOLDEX3D and optiSLang | June 2020 14
Reference
Scale 5x
Second
optimization
Scale 5x
Edge warpage:
1.6 mm Edge warpage:
0.6 mm
Objective warpage: 2.20
Cycle time: 29s Cycle time: 32s
Objective warpage: 0.62
• More than 3 times less warpage
• 10% more cycle time
SUMMARY: BATTERY SLOT
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SUMMARY: KEY BENEFITS OF
OUR WORKFLOW
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Optimization of the entire injection molding
development process
Enables better collaboration
Enables better trade-offs
Get it right the first time
Overall less development effort
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We aim to establish our workflow in the daily injection molding development
External meshing software:
• More geometric flexibility
• More control over mesh sizes
Balancing of the injection system:
• Balancing multi cavity molds
• Optimize the filling behaviour
Are you interested?
• Don‘t hesitate to contact us
• We are planning to offer our workflow
as a consulting service
WHAT‘S NEXT?
Florian Seybold, Steffen Aldinger | Injection Molding Process Optimization using MOLDEX3D and optiSLang | June 2020 16
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MAKE A DIFFERENCE
THANK YOU
Florian Seybold, Steffen Aldinger | Injection Molding Process Optimization using MOLDEX3D and optiSLang | June 2020 17
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Florian Seybold, Steffen Aldinger | Injection Molding Process Optimization using MOLDEX3D and optiSLang | June 2020
CONTACT
Florian Seybold
Virtual Engineer
Advanced Research & Development
T. +49 7195 14 5178
Steffen Aldinger
Virtual Engineer
Advanced Research & Development
T. +49 7195 14 5933
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