The Method for Optimum Design of Resin Injection Molding Process Conditions using Multivariate Analysis with Robust Parameter Design

In recent years, the demand for plastic products has increased, and along with the deepening of academics, mass production, weight reduction, and high precision are progressing. In the fields of design development and production technology, there are many issues related to quality assurance such as molding defects and product strength. In particular, in the resin molding process, there is a high degree of freedom in product shape and mold structure, and it is an important issue to create quality functions that apply analysis of complex multidimensional information. In this study, the important factors of the resin molding process related to the optimization of resin strength are extracted by applying the multivariate analysis method and robust parameter design. As a result of verification of the proposed method, it is clarified that uniformization of the resin filling density in the mold is extremely important for stabilizing the resin strength.

Robust Parameter Design of Shielded Metal Arc Welding (SMAW) for Optimum Tensile Strength

Shielded Metal Arc Welding (SMAW), an arc welding process, is widely used in applications. In practice, SMAW is widely applied to the welding process on hollow square pipe. Performance expected from this welding is the tensile strength of weld joint. The tensile strength is influenced by parameters process which have possibility for an optimization process to become ‘robust’. Robust is a design which less sensitive to the effect of uncertain quantities or noise factors. Taguchi method is the most efficient optimization method which accommodates the noise factors effect and requires less experiment. This study is focusing on optimizing the welding process on hollow square pipe. Parameters process such as welding current (I), electrode angle (θ), root gap (d) and electrode type (E) are adopted as parameters design. Taguchi method are chosen as a strategy and L9 fractional orthogonal array are chosen as the design experiment, which only 9 experiment samples needed from 81 experiments that should have been carried out for full factorial design. The objectivity is to maximize the tensile strength of weld joint. Three replications of L9 fractional orthogonal array Taguchi had been performed to generate the tensile strength and estimates the fluctuation of the output caused by noise factors. This study found that the welding current of 100A (I), electrode angle (θ) of 90°, root gap (d) of 2 mm, and electrode type (E) of E7018 produce the optimum results. Tensile strength improved from this robust parameter design is about 98.39 MPa based on initial parameter design.

Application of robust parameter design in the development of a quantitative chemical analysis procedures in metallurgy

The paper presents the results of experimental research for the quantitative chemical analysis procedures using the robust parameter design methodology. There is an example of the parameter design in development of the measurement procedure for the mass fraction of chlorine in dusty waste in the ferronickel production. Results of experiment analysis has provided an information about the optimal conditions for sample preparation procedure.

Robust parameter design and economical multi-objective optimization on characterizing rubber for shoe soles

Within Taguchi methods, robust parameter design is a widely used tool for quality improvement in processes and products. The loss function is another quality improvement technique with a focus on cost reduction. Traditional Taguchi methods focus on process improvement or optimization with a unique quality characteristic. Analytical approaches for optimizing processes with multiple quality characteristics have been presented in the literature. In this investigation, a case of analysis for two quality characteristics in rubber for shoe sole is presented. A methodology supported in robust parameter design in combined array is used in order to obtain optimal levels in the vulcanization process. Optimization techniques based on the loss function and the use of restricted nonlinear optimization with genetic algorithms are proposed.