Integrating the Taguchi Method and Response Surface Methodology for Process Parameter Optimization of the Injection Molding

Abstract

Abstract:The outer coating of an optical fiber cable protects the optical fiber, and the contraction rate of the outer coating can affect the communication capacity and distance, so the contraction rate is often regarded as the key factor in defining the quality of an optical fiber cable. For this reason, using the example of the circular single-pin optical fiber cable manufacturing process of the largest optical communication manufacturer in the world, the Taguchi Method (TM) is used to screen the variables that have significant effects on the contraction rate of the outer coating. Furthermore, the optimization engineering of Response Surface Methodology (RSM) is utilized for the empirical research to acquire a prediction model that can be used to optimize the optical fiber outer coating injection molding process. The research results show that the contraction rate predicted by the integration of the Taguchi Method and RSM is 2.28%. The empirical results reveal that the contraction rate of the outer coating indeed decreased from the original 3.83% down to 2.16%, indicating that the integration of the Taguchi Method and RSM could effectively improve the quality.

Intelligent Injection Molding on Sensing, Optimization, and Control

“…Noniterative optimization methods are easy to implement and require less computation. ey have been widely used in research, including the following methods: case-based reasoning (CBR) [3], expert system, fuzzy system [99], and the Taguchi method [100][101][102][103][104][105][106][107][108][109][110][111][112][113][114][115][116].…”

Metodología Integral para el Mejoramiento de la Calidad Mediante la Reducción de la Variabilidad Funcional: Un Caso de Estudio

“…Por ejemplo, Ordoobadi (2009) utilizó ésta técnica para evaluar tecnologías de fabricación avanzadas; Sahoo y Mohanty (2013) la usaron para encontrar valores de parámetros de proceso en una operación de torneado; Azadeh y Miri-nargesi (2012) emplearon el QLF para clasificar y analizar los sectores de fabricación. Por su parte Jou et al (2014), en una solución mixta usando QLF y el análisis de superficie de respuesta, determinaron las condiciones óptimas de moldeo para un proceso de inyección.…”

“…Ventajas Desventajas QLF  Alta reproducibilidad, pocos experimentos y fácil comprensión (Jou et al, 2014)  Amplia utilización en diferentes campos como indicador de toma de decisiones (Azadeh y Miri-nargesi, 2012)  Involucra costos ocultos que no se reflejan en otros métodos basados en costos (Cosmin, y Stanciuc, 2013).…”

Sisal-glass fiber hybrid biocomposite: Optimization of injection molding parameters using Taguchi method for reducing shrinkage

“…Various optimization methods such as Taguchi [12,13], integrated response surface method [18], genetic algorithm [19], grey theory [20] and neural network [21] have been implemented to improve process, product and design. Kamoun et al [14] applied sequential simplex method for on-line optimization of selected nine injection molding (IM) parameters in order to minimize rejects from 8.0% to 1.6%.…”

“…Kamoun et al [14] applied sequential simplex method for on-line optimization of selected nine injection molding (IM) parameters in order to minimize rejects from 8.0% to 1.6%. Other studies reported using a combination of computer simulation and statistical approach to optimize IM process parameters [16,18,19]. Despite various methods, Taguchi method is the most common IM parameter optimization tool due to its robust and simple experimental design approach based on the conventional statistical concepts [24,25].…”