Taguchi Optimization and Experimental Investigation of the Penetration Rate of Compact Polycrystalline Diamond Drilling Bits in Calcareous Rocks

Previous studies have not agreed on factors that affect the success of different kinds of products. These studies have used independent variables with a different number of success factors to examine several products, and some of these variables have been redundant. No standardized factor predicts the success of various products; thus, no generalizable result has provided a reference for further studies or use recommendations for practices. Therefore, this study produced a model that not only examined specific products and scope but also used a number of standardized success factors by building a mathematical model of the success factors that affect the success of various products. The study utilized 304 products from the Indonesian market as well as design of experiment to build the mathematical model. The results suggested that six standardized success factors affected the success of various products: (1) price, (2) product performance, (3) brands, (4) aesthetic design, (5) services and (6) marketing. Services and marketing (i.e., appropriately timed marketing) were positively correlated and proportional to the increase of market share. Therefore, focusing on the services and marketing factors that will drive the success of a product is important for many companies. The factors that positively drive success can be determined by characteristic sales in the Indonesian market.

Section: Methodsmentioning

confidence: 99%

A Mathematical Model of Factors Driving Product Success in an Indonesian Market using Design of Experiment

Setyaningrum¹,

Subagyo²,

Wijaya³

2020

“…One of the benefits of the Taguchi method is the consideration of noise factors, in this case, factors that cannot be controlled (Rathi and Salunke, 2012;Yang et al, 2008), in this Processing Temperature and Pressure Optimization study, we have considered only controllable factors. This experiment uses the S/N ratio with the larger-the-better approach to analyzing the signal-to-noise ratio (S/N) as shown by (Wicaksono, Budiyantoro, and Rochardjo, 2019;Khentout, Kezzar, and Khochemane, 2019) using equation (1).…”

Section: Design Of Experimentsmentioning

confidence: 99%

Impact and Tensile Properties of Injection-Molded Glass Fiber Reinforced Polyamide 6 –Processing Temperature and Pressure Optimization

Budiyantoro,

Rochardjo,

Wicaksono

et al. 2024

Polyamide 6-short glass fiber composite is one of the advanced materials used for lightweight-high strength applications. To some extent, the mechanical properties of the composite depend on its manufacturing process. The most common method to produce thermoplastic polymer products is injection molding. Production of injection-molded components may use process parameters that can vary significantly since it is a variable that depends on the type of polymer materials. This study intends to find the relationship between tensile strength and impact strength of short glass fiber reinforced polyamide-6 composite with the injection molding process parameters, namely barrel temperature, holding pressure, and injection pressure. The Taguchi method was used for the analysis. The result shows that barrel temperature is the most influencing parameter for tensile strength and impact strength.

“…In addition, ANOVA can determine the effect of machining parameters on various responses, including power consumption, cutting force, and material removal rate (MRR), etc. (Khentout et al, 2019). In the analysis, Dry Milling Machining: Optimization of Cutting Parameters Affecting Surface Roughness of Aluminum 6061 using the Taguchi Method the sum of squares (SS) and variance of square are calculated, and the F-test ratio at the 95% confidence level is employed to determine the significant factors that affect machining (Ahmed et al, 2015).…”

Section: Introductionmentioning

confidence: 99%

Dry Milling Machining: Optimization of Cutting Parameters Affecting Surface Roughness of Aluminum 6061 using the Taguchi Method

Sulaiman¹,

Alajmi²,

Isahak³

et al. 2022

In this paper, the application of dry machining as part of contributions for development of a sustainable environment in the machining industry is explained. Achieving a good surface roughness product is one the most important factors that must be considered in the metal machining process. Surface quality control is a complicated process, and a reliable technique is required during machining operation. Currently, an appropriate cutting conditions in most of machining cases are determined by trial and error, which leads to time increased, energy consumption, and manufacturing costs. Most of the previous studies have investigated factors that affect surface roughness, but different machining conditions require the control of different factors. In this study, experiments were conducted to optimize cutting parameters and determine the factors significant for the surface roughness quality. Machining experiments were conducted on a vertical milling machine using square non-coated two flutes HSS Co end mill with selected cutting parameters on aluminum 6061. This study focused on the surface roughness in one direction and combined with the Taguchi design method. Signal-to-noise (S/N) ratio and analysis of variance (ANOVA) were employed to examine and reveal the factors that are significant in affecting surface roughness quality. The analysis result revealed that cutting speed exerts the highest effect on surface roughness, followed by feed rate and depth of cut. Finally, the combination of dry machining performance and an eco-friendly environment would result in competitive sustainable growth of the machining industry.