Combination of importance-performance analysis and response surface methodology for enhancing satisfaction

2016 ◽  
Vol 33 (6) ◽  
pp. 792-802 ◽  
Author(s):  
Ro Jin Pak
Keyword(s):  
Response Surface Methodology ◽  
Performance Analysis ◽  
Response Surface ◽  
Online Courses ◽  
Current Status ◽  
Entrance Examination ◽  
College Entrance Examination ◽  
College Entrance ◽  
Statistical Tool ◽  
Content Type

Purpose – In order to know how to enhance the satisfaction of online courses in preparing for the college entrance examination in Korea, the purpose of this paper is to combine both the importance-performance analysis (IPA) and the response surface methodology (RSM). Design/methodology/approach – IPA is a simple but powerful tool for understanding the current status of factors or attributes in management problems. However, it lacks to provide the proper indication of what to do next on those factors or attributes to optimize a goal. RSM is a statistical tool helping us to set up a direction of factors or attributes in optimizing an output. The author attempts to combine both IPA and RSM in order to discover the next step after IPA for optimizing the goal. As an example, the author considers how to enhance the satisfaction of online courses in preparing for the college entrance examination in Korea. Findings – The combination of IPA and RSM enables us to find a way to attain a goal, for example, satisfying customers in a concrete and creative way. Research limitations/implications – Sample size is enough for research purpose but is a bit small for general purpose. Practical implications – This research tries to answer what to do next after IPA. Social implications – This research provides a predictive guide to satisfy customers. Originality/value – As far as the author knows, combining both IPA and RSM has not been made so far. It is a fusion of managerial and engineering techniques.

Modeling of the machining parameters in turning of Al-5052/TiC/SiC composites: a statistical modeling approach using grey relational analysis (GRA) and response surface methodology (RSM)

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Venkateshwar Reddy Pathapalli ◽  
Meenakshi Reddy Reddigari ◽  
Eswara Kumar Anna ◽  
P. Srinivasa Rao ◽  
D V. Ramana Reddy
Keyword(s):  
Response Surface Methodology ◽  
Response Surface ◽  
Metal Matrix ◽  
Machining Parameters ◽  
Matrix Composites ◽  
Content Type ◽  
Relational Analysis ◽  
Desirability Approach ◽  
Grey Relational ◽  
Grey Taguchi

PurposeMetal matrix composites (MMC) has been a section which gives an overview of composite materials and owing to those exceptional physical and mechanical properties, particulate-reinforced aluminum MMCs have gained increasing interest in particular engineering applications. Owing to the toughness and abrasive quality of reinforcement components such as silicon carbide (SiC) and titanium carbide (TiC), such materials are categorized as difficult materials for machining. The work aims to develop the model for evaluating the machinability of the materials via the response surface technique by machining three distinct types of hybrid MMCs.Design/methodology/approachThe combined effects of three machining parameters, namely “cutting speed” (s), “feed rate” (f) and “depth of cut” (d), together with three separate composite materials, were evaluated with the help of three performance characteristics, i.e. material removal rate (MRR), cutting force (CF) and surface roughness (SR). Response surface methodology and analysis of variance (ANOVA) both were initially used for analyzing the machining parameters results.FindingsThe contours were developed to observe the combined process parameters along with their correlations. The process variables were concurrently configured using grey relational analysis (GRA) and the composite desirability methodology. Both the GRA and composite desirability approach obtained similar results.Practical implicationsThe results obtained in the present paper will be helpful for decision-makers in manufacturing industries, who work on metal cutting area especially composites, to select the suitable solution by implementing the Grey Taguchi and modeling techniques.Originality/valueThe originality of this research is to identify the suitability of process parameters combination based on the obtained research results. The optimization of machining parameters in turning of hybrid metal matrix composites is carried out with two different methods such as Grey Taguchi and composite desirability approach.

Improving the electromagnetic compatibility of electronic products by using response surface methodology and artificial neural network

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Ching-Hsiang Chen ◽  
Chien-Yi Huang ◽  
Yan-Ci Huang
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Response Surface Methodology ◽  
Response Surface ◽  
Electromagnetic Compatibility ◽  
Heat Dissipation ◽  
Optimal Parameter ◽  
Content Type ◽  
Early Stages ◽  
Artificial Neural

Purpose The purpose of this study is to use the Taguchi Method for parametric design in the early stages of product development. electromagnetic compatibility (EMC) issues can be considered in the early stages of product design to reduce counter-measure components, product cost and labor consumption increases due to a number of design changes in the R&D cycle and to accelerate the R&D process. Design/methodology/approach The three EMC characteristics, including radiated emission, conducted emission and fast transient impulse immunity of power, are considered response values; control factors are determined with respect to the relevant parameters for printed circuit board and mechanical design of the product and peripheral devices used in conjunction with the product are considered as noise factors. The optimal parameter set is determined by using the principal component gray relational analysis in conjunction with both response surface methodology and artificial neural network. Findings Market specifications and cost of components are considered to propose an optimal parameter design set with the number of grounded screw holes being 14, the size of the shell heat dissipation holes being 3 mm and the arrangement angle of shell heat dissipation holes being 45 degrees, to dispose of 390 O filters on the noise source. Originality/value The optimal parameter set can improve EMC effectively to accommodate the design specifications required by customers and pass test regulations.

Sign in / Sign up

Export Citation Format

Share Document