Determining Optimal Moulding Process Parameters by Two Level Factorial Design with Center Points

Rajalingam, Sokkalingam; Bono, Awang; Sulaiman, Jumat

doi:10.4038/sljastats.v12i0.4968

Cited by 6 publications

(2 citation statements)

References 9 publications

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“…According to Yoshihara [89], transversal shrinkage was affected by injection pressure. According to Rajalingam, Bono, and Sulaiman [99], shrinkage along length was affected by mold temperature, injection pressure, screw rotation speed, mold temperature-injection pressure interaction, and mold temperature-screw rotation speed interaction; while along the width direction, shrink age was affected by mold temperature, injection pressure, screw rotation speed, mold temperature-screw rotation interaction. Prashantha et al [100] considered PP specimens molded by injection molding, and longitudinal shrinkage was between 2 and 4 times more (on the average) than shrinkage in transversal direction.…”

Section: Processing Parameter Influencesmentioning

confidence: 98%

Review of Factors that Affect Shrinkage of Molded Part in Injection Molding

Annicchiarico¹,

Alcock²

2014

Materials and Manufacturing Processes

123

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Purpose: This paper reviews the factors affecting shrinkage of molded parts in injection molding. Methods: A selective screening of the papers published in the last 10 years was adopted. The review was organized according to molding scale (macro or micro) and by considering four branches of influence: material behaviors, processing parameters, mold, and specimen design. Results: Within the interval of confidence, at the macroscale, critical processing parameters were the temperatures, the packing parameters, cooling time, and injection speed; temperatures and packing parameters resulted critical factors at the microscale as well. Concerning the design aspects, the runner size and the ribs affect shrinkage at the macro and microscale, respectively. The analysis of the literature review has shown an absence of statistical approach for determining the material influences, a lack of information on shrinkage occur in powder-molded parts and the absence of data in specimen with dimensions below 10 m. Conclusions: The review collected the factors that affect shrinkage in injection molding, and identified three possible areas for further works.

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Section: Processing Parameter Influencesmentioning

confidence: 98%

Review of Factors that Affect Shrinkage of Molded Part in Injection Molding

Annicchiarico¹,

Alcock²

2014

Materials and Manufacturing Processes

123

View full text Add to dashboard Cite

show abstract

“…However, method which determines proper DOE design is not included. S. Rajalingam et al [3] use three input factors with repetition. Abohashima et al [4] use four input factors with repetition to determine the influence of chosen factors on attributive characteristics.…”

Section: Introductionmentioning

confidence: 99%

Application of Non-Standard Doe and Its Validation in Determining Nominal Parameters in Production Process

Ignjatovska¹

2020

MESJ

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A structured approach is fundamental in designing a complex multivariable process, while achieving specified product quality. Nominal values of process parameters of an injection molding process are defined by implementing DOE methodology. Optimisation of experimental phase is achieved by progressive information acquiring concerning influential input factors and DOE design. Hence, most influential machine process parameters are varied using a non-standard fraction-factorial design. A linear regression model with included elements of second order interaction is defined based on obtained data. Additional testing of its validation is in order before reaching a final conclusion. Firstly, model significance is tested by conducting an ANOVA analysis. Only significant models prove that DOE has been adequately planned and factors which affect the controlled output have been chosen. Finally, DOE is completed by adequacy analysis of the regression model. Lack-of-fit test is chosen to test whether the model is a proper representation of the real process.

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Multi Response optimization of injection moulding Process parameters to reduce cycle time and warpage

Singh

Pradhan

Verma

2018

Materials Today: Proceedings

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Determining Optimal Moulding Process Parameters by Two Level Factorial Design with Center Points

Abstract: Determining optimal process parameter setting critically influences productivity, quality and cost of production in the injection moulding industry. Previously production engineers used trial and error method to determine optimal process parameter setting.

Cited by 6 publications

References 9 publications

Review of Factors that Affect Shrinkage of Molded Part in Injection Molding

Review of Factors that Affect Shrinkage of Molded Part in Injection Molding

Application of Non-Standard Doe and Its Validation in Determining Nominal Parameters in Production Process

Multi Response optimization of injection moulding Process parameters to reduce cycle time and warpage

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