Browsing by Author "Shin, Yung C."

Now showing 1 - 1 of 1
  • Thumbnail Image
    Item
    A Framework for Estimating Mold Performance Using Experimental and Numerical Analysis of Injection Mold Tooling Prototypes
    (Springer, 2019) Jahan, Suchana; El-Mounayri, Hazim; Tovar, Andres; Shin, Yung C.; Mechanical Engineering and Energy, School of Engineering and Technology
    Additive Manufacturing (AM), 3D printing, rapid prototyping, or rapid tooling refer to a range of technologies that are capable of translating virtual CAD model data into physical model. It is executed in growing number of applications nowadays. A wide range of materials are currently being used to produce consumer products and production tools. AM has brought in revolutionary changes in traditional manufacturing practices. Yet, there are certain drawbacks that hinder its advancement at mass manufacturing. High cost associated with AM is one of them. Using 3D printed tooling can provide long-time cost effectiveness and better product quality. Additively manufactured injection molds can increase the cooling performance, reduce production cycle time, and improve surface finish and part quality of the final plastic product. Yet, manufacturers are still not using the printed molds for industrial mass production. Numerical analysis can provide approximation of such improved performance, but, factual experimental results are necessary to satisfy performance criteria of molds to justify the large investment into tooling for existing industries. In this research work, a desktop injection molding machine is used to evaluate performance of 3D printed molds to develop a cost and performance analysis tool. It serves as a baseline to predict the performance of molds in real-time mass manufacturing of consumer products. The analysis describes how appropriate the estimation can be from any simulation study of molds, how much the scaling down of tool and molding system can affect the prediction of actual performance, what correction factors can be used for better approximation of performance matrices. Several “scaled down” prototypes of injection molds have been used. They have design variations as: with or without cooling system, conformal or straight cooling channels, solid or lattice matrix, and metal or tough resin as the mold material. The molds are printed in in-house printing machines and can also be printed online with limited charges. This also provides an excellent demonstration of using inexpensive material and manufacturing process, such as resin to estimate the performance of highly expensive 3D printed stainless steel molds. The work encompasses a framework to reduce overall cost of implementing AM, by lowering time and monetary expenses during the research and development, and prototyping phases.