Multivariate Analysis Overcomes Complexities in Injection Molding September 18, 2016 11/15/2018 Disclosure or duplication without consent is prohibited

Disclosure or duplication without consent is prohibited ABSTRACT Over the years, automotive exterior parts have become more complex and substantially larger, yet are molded at faster cycle times. The transformation in design and challenging manufacturing demands have driven changes in tool design, hot runner design, material formulation and molding machine functionality. With these increasing challenges, we have to ask ourselves if conventional methods of quality control, which are typically univariate, are still effective. The short answer is no. This presentation demonstrates how multivariate analysis extracts pertinent information from large amounts of complex data. It is then able to identify the correlation structure and relationships that exist between multiple process variables and present it visually. We’ll present a project comparing univariate and multivariate approaches. These methods hold the promise to both reduce the dependency on subjective, visual inspection and make lights-out manufacturing more viable. 11/15/2018 Disclosure or duplication without consent is prohibited

BACKGROUND- Purpose and Objectives Goal: Utilize MVA methodology as a tool for quality control Objectives: Reduce inspection by use of automated parametric analysis Expand process knowledge Streamline process troubleshooting Move to lights-out production 11/15/2018 Disclosure or duplication without consent is prohibited

Injection Moulding Quality Control Injection Moulding Process Evolution Automotive exterior parts have become more complex, substantially larger and are being moulded at faster cycle times The transformation in design and the challenging manufacturing demands has driven changes in tool design, hot runner design, material formulation, and moulding machine functionality 2001 Fascia 2015 Fascia Material Test 2001 TPO Spec. 2015 % Change Melt flow rate 18.5 35.5 91.9% Flexural Modulus (Mpa) 1020 1800 77.5% Mould Shrinkage (after bake) 15 8 46.7% Filler Content 12 ∞% Part Design Part design has changed noticeably Size and weight of a typical part has increased Some of our fascia weigh as much as 19 lbs. The overall shape and contours of the moulded part is more complex Intricate attachment features have been designed to minimize gap Tool Design Increased part complexity requires improved sequential valve gate control These designs require precise valve gate locations to minimize flow lines and weld line Faster cycle times requires that the cooling process be optimized with Improved cooling circuit designs Material Faster Cycle Times: Materials have changed as shown in the chart. Melt flow has increased to enable the part to be filled faster and at lower pressures We see melt flows today of 25 and even as high as 50 Additives have been designed to accelerate crystallization time, improve demoulding and many other benefits Flexural Modulus has moved from 800 MPA to about 1800 Mpa with 2500+ Mpa in the future Filler content is higher to increase flexural modulus as well as reduce the cost of the overall compound. This drives other concerns for downstream processes. Dimensional stability And all the while maintaining dimensional stability. Injection Fill Sequence Frozen Pressure Profile 11/15/2018 Disclosure or duplication without consent is prohibited

Disclosure or duplication without consent is prohibited As the injection moulding process evolves are the conventional methods of quality control still effective? Injection moulding has changed significantly since I started my plastics career back in the 70’s. We don’t twist knobs, adjust valves in the floor to adjust pressures, or set the travel on the screw with a thumbwheel and a limit switch. Everything is electronic today, so the question we need to ask ourselves is, …. As the injection moulding process has evolved, are conventional methods of quality control still effective ? 11/15/2018 Disclosure or duplication without consent is prohibited

Injection Moulding Quality Control Process Alarms and Univariate Analysis Most moulding machines offer process value alarms or conventional SPC charting capabilities Machine Controls have kept pace, allowing moulding operators to monitor many process conditions Many moulding machines offer process alarms or conventional SPC charting Key process values are readily available on a shot to shot basis and will trigger a process alarm when a specified limit has been reached This all leads to the concept of univariate analysis Alarm Page Control Chart 11/15/2018 Disclosure or duplication without consent is prohibited

Shot Size Hold Pressure Hot Runner Control Clamp Force Back Pressure Injection Speed Machine Down Time There are too many variables in the injection moulding process to rely on traditional methods of quality control Transfer Position Machine Calibration Check Ring Performance Screw Speed Mould Temperature As we measure more & more variables, there are just too many, to continue rejecting parts based on single variables. Valve Gate Sequence Barrel Temperature Material Lot Hold Time Screw Wear Regrind Percentage Transfer Pressure Cushion 11/15/2018 Disclosure or duplication without consent is prohibited

Expanded Process Monitoring Today we have many opportunities to monitor multiple process parameters 54 process output parameters are available More parameters mean more insights/relationships can be investigated BUT Increased multidimensional space require complex analytical methods 11/15/2018 Disclosure or duplication without consent is prohibited

Univariate is Not Enough Red dots are defective parts Max Injection Pressure is considered a critical process monitoring variable Ineffective detection: too many false positives and negatives 11/15/2018 Disclosure or duplication without consent is prohibited

Univariate, Bivariate, Trivariate ... Can’t visualize beyond three dimensions, so …. 11/15/2018 Disclosure or duplication without consent is prohibited

Disclosure or duplication without consent is prohibited Multivariate True Positives False Positive Can’t see a 4+ dimensional density ellipse but can consider Hotelling’s T2 Do not want to pass defective parts because of the significant cost of rejecting them downstream (prime, paint, assembly) 11/15/2018 Disclosure or duplication without consent is prohibited

Injection Moulding Quality Control Control Chart Signals and Defect Detection There was a direct correlation of visible defects to MVA signals above the upper control limit of 56 Dependent on the combination of multiple parameters the signals identified typical process situations associated with short shot and excessive flash defects So now we have a methodology of providing an alarm that would tell the operator to seriously look at a part, since there is a strong probability there is an issue. Most likely, this part would have gone through a number of downstream processes, before being found. Attachment Clip Feature Short Shot Excess Flash at Wing Tip 11/15/2018 Disclosure or duplication without consent is prohibited

Injection Moulding Quality Control Conclusions Multivariate analysis can be a very effective method of defect detection with the injection moulding process and is considerably more effective than traditional univariate methods The process of validating the MVA model provides further insight into understanding the injection moulding process window Principal component analysis identifies relationships between multiple parameters and enhances process troubleshooting In conclusion, we feel that: Multivariate analysis isa very effective method of defect detection with the injection moulding process MVA is a more effective indicator of quality than univariate methods The process of developing the MVA model provides significant process insight with regard to the injection moulding process But the process is not for the faint of heart. It is not ‘plug & play’ technology You should expect to spend significant amount of time developing your models on a tool / machine basis, and learn how to modify / tune your data to give you the best results. 11/15/2018 Disclosure or duplication without consent is prohibited

Injection Moulding Quality Control Next Steps Further evaluate and refine MVA model Develop online process monitoring for automated defect detection Integrate MVA inspection, classification and disposition with lights out manufacturing Look at new features in JMP®13 including DmodX available in the Principal Components platform 11/15/2018 Disclosure or duplication without consent is prohibited