Design of Experiments as Effective Design Tools

2008 ◽  
Author(s):  
Mohamed Nasser ◽  
Badih Jawad
Keyword(s):  
Design Of Experiments ◽  
Statistical Technique ◽  
Product Performance ◽  
Design Tools ◽  
Key Factors ◽  
Multiple Variables ◽  
Problem Design ◽  
System Variables ◽  
Effective Design ◽  
Significant Factors

Design of Experiment (DOE) provides a highly structured way to study the effects of multiple variables on product performance as well as efficient and effective methods for determining the most significant factors and interactions in a given design problem. Design of Experiments (DOE) is an off line quality improvement methodology that dramatically improves industrial products and processes. Input factors are varied in a planned manner to optimize output responses with minimal variability. Design of Experiments is a standard statistical technique used in quality engineering, pharmaceuticals, manufacturing, and other industries to identify key factors and levels that influence system performance and variability. This technique is especially useful when there is the need to understand the interactions and effects of several system variables and an absence of concrete information. In industry, designed experiments can be used to systematically investigate the process or product variables that influence product quality.

scholarly journals PENGARUH SISTEM PEMBELAJARAN DAN KEPUASAN KERJA DOSEN TERHADAP KINERJA DOSEN DI STIKES KARSA HUSADA GARUT

2018 ◽  
Vol 15 (3) ◽  
pp. 213
Author(s):  
Eti Suliyawati
Keyword(s):  
Job Satisfaction ◽  
Teacher Performance ◽  
Statistical Technique ◽  
Teacher Job Satisfaction ◽  
Learning System ◽  
Survey Method ◽  
Descriptive Data ◽  
System Variables ◽  
Variable Performance ◽  
Variable Analysis

Central issue in this study is teacher performance is not optimal, the researchers observed due to learning andjob satisfaction of teachers who have not been going well. On the basis of thought and consideration, theresearchers wanted to investigate further in the form of research thesis entitled "Effect of learning and teachers'job satisfaction on the performance of teachers in STIKes Karsa Husada Garut.." The method used isexplanatory survey method, ie a method that aims to test the hypothesis that has been formulated previously.Technical analysis is a statistical technique that serves to classify descriptive data, work, conclude, explain andpresent the processed results. It aims to make the pattern a causal relationship between the value of a variable toanother variable. Analysis of the data processing using path analysis (Path analisys). The results showed that theperformance of teachers affected by the learning system variables and job satisfaction of teachers, eitherpartially or simultaneously. Partially influenced by the variable performance of teachers learning system by47,2%, and influenced by teachers' job satisfaction variables of 18,8%, and the rest is influenced by othervariables. The conclusion of this research is learning and teacher job satisfaction has been empirically to giveeffect to the performance of teachers in STIKes Karsa Husada Garut, either partially or simultaneously. Theresults also found that teacher performance is also influenced by other factors academically recognized.

scholarly journals Significant factors in the technological profile of innovative companies in the return of capital in technological innovation

2013 ◽  
Vol 1 (1) ◽  
pp. 26-37
Author(s):  
Eloisa De Moura Lopes ◽  
Henio Fontão ◽  
Amílcar Dos Santos Gonçalves
Keyword(s):  
Design Of Experiments ◽  
Factorial Design ◽  
Technological Innovation ◽  
Open Innovation ◽  
New Products ◽  
Innovation System ◽  
Field Research ◽  
Significant Factors

Aim to analyze the significance of factors of technological profile in innovative companies that contribute to the return of capital in innovation (ROEI). The method used was design of experiments, by the structure of non-balanced factorial design. The field research was done with seventy companies. The main return of the capital applied in innovation, should support the open innovation system, and exclusively systematic studies of ideas for new products.

Simulation Research on Cross-Sectional Stability of Expanded Diameter Conductors Based on ANSYS

2012 ◽  
Vol 256-259 ◽  
pp. 2838-2843
Author(s):  
Jia Jun Si ◽  
Jian Cheng Wan ◽  
Bin Liu ◽  
Yao Ding
Keyword(s):  
Power Transmission ◽  
Element Model ◽  
Aluminum Wire ◽  
Key Factors ◽  
Cross Sectional ◽  
Simulation Research ◽  
Contact Points ◽  
Electricity Power ◽  
The Wire ◽  
Significant Factors

The expanded diameter conductors are widely used for high voltage electricity power transmission due to its superior ability to prevent electronic corona phenomenon. However an undesired stability problem of wire distribution configuration within the cross-section of the conductor often occurs during the power line stringing processes, especially for the not-well-designed conductor structures. This phenomenon is typically characterized by the appearance of outer wire/wires jumping out of the layer; therefore it is also referred as wire jump-out problem. Finite element model which can predict the wire jump-out phenomenon has been successfully developed in this research project. Series of stimulations have been carried out to investigate the key factors to cause the wire jump-out problem. The reduction of radial distances between the adjacent aluminum wire layers due to the obvious indentation deformation at the trellis contact points were identified to be one of the most significant factors to lead to the wire jump-out problem. Numerical results show that keeping sufficient initial gap between the adjacent outer layer wires in the initial design can be a simple effective way to relieve/avoid the wire jump-out problem.

scholarly journals Addressing Cognitive Challenges in Design – A Review on Existing Approaches

2019 ◽  
Vol 1 (1) ◽  
pp. 2775-2784
Author(s):  
Weining Ning ◽  
Joy Goodman-Deane ◽  
P. John Clarkson
Keyword(s):  
Capability Approach ◽  
Human Cognition ◽  
Design Tools ◽  
Cognitive Modelling ◽  
Cognitive Level ◽  
Future Directions ◽  
Underlying Causes ◽  
Effective Design ◽  
Supporting Materials ◽  
Cognitive Design

AbstractInsufficient design often causes challenges to users on a cognitive level, hindering them from interacting with products smoothly. There is a lack of effective design tools and supporting materials that can help designers to understand human cognition and how it affects the way that users experience and use products and services. This paper aims to identify current approaches that can be applied to address this issue, and to examine their strengths and weaknesses. This helps to identify future directions for developing and improving cognitive design supports. A literature review was conducted of research publications in the fields of both design and cognition. Four key approaches are identified: cognitive design principles/guidelines, the demand-capability approach, cognitive walkthrough and cognitive modelling. Their strengths and weaknesses are analyzed from a design standpoint. The paper also analyses the underlying causes of the insufficient uptake of cognitive design approaches by designers.

Prediction of Drivers' Eye Location

1974 ◽  
Vol 18 (2) ◽  
pp. 189-191 ◽  
Author(s):  
Susanne M. Gatchell ◽  
James M. Miller
Keyword(s):  
Automotive Industry ◽  
Future Research ◽  
Design Tools ◽  
Laboratory Setting ◽  
Design Standards ◽  
Driving Task ◽  
Eye Location ◽  
Important Design ◽  
Straight Ahead ◽  
Significant Factors

The set of guidelines for establishing the location of drivers' eyes as a function of a vehicle's workspace geometry and percentile representation of driving population is one of the most important design tools in the automotive industry. This tool is called an Eyellipse which allows designers to minimize structures that interfere with a driver's vision to his environment. The Eyellipses were, however, based on data gathered while subjects were in a static laboratory setting looking straight ahead at a picture of a driving scene instead of a real driving task. The objectives of this paper are threefold: (1) to examine literature that has laid the foundations for current automotive design standards on drivers' eye location, (2) to describe models for predicting drivers' eye location, and (3) to determine significant factors that should be used in these models by re-analyses of raw data from previous studies. This discussion also indicates weaknesses in previous research and proposes areas where future research is needed in order to determine the true distribution of subjects' eyes during a real driving task.

scholarly journals Statistical Design of Experiments: An introductory case study for polymer composites manufacturing applications

2021 ◽  
Vol 347 ◽  
pp. 00028
Author(s):  
Natasha Botha ◽  
Helen M. Inglis ◽  
Roelof Coetzer ◽  
F. Johan W.J. Labuschagne
Keyword(s):  
Optimal Design ◽  
Design Of Experiments ◽  
Polymer Composites ◽  
Response Surface ◽  
Statistical Design ◽  
Efficient Design ◽  
Statistical Design Of Experiments ◽  
Wide Range ◽  
Multiple Variables

Statistical design of experiments (DoE) aims to develop a near efficient design while minimising the number of experiments required. This is an optimal approach especially when there is a need to investigate multiple variables. DoE is a powerful methodology for a wide range of applications, from the efficient design of manufacturing processes to the accurate evaluation of global optima in numerical studies. The contribution of this paper is to provide a general introduction to statistical design of experiments for a non-expert audience, with the aim of broadening exposure in the applied mechanics community. We focus on response surface methodology (RSM) designs — Taguchi Design, Central Composite Design, Box-Behnken Design and D-optimal Design. These different RSM designs are compared in the context of a case study from the field of polymer composites. The results demonstrate that an exact D-optimal design is generally considered to be a good design when compared to the global D-optimal design. That is, it requires fewer experiments while retaining acceptable efficiency measures for all three response surface models considered. This paper illustrates the benefits of DoE, demonstrates the importance of evaluating different designs, and provides an approach to choose the design best suited for the problem of interest.

scholarly journals Some Probability Distributions and L-Moment in Hydrological Engineering

2020 ◽  
Vol 9 (5) ◽  
pp. 1131-1134
Keyword(s):  
Historical Data ◽  
Probability Distributions ◽  
Statistical Technique ◽  
Parametric Estimation ◽  
Distribution Fitting ◽  
The Earth ◽  
Testing Techniques ◽  
Reliable Testing ◽  
Moment Ratio Diagram ◽  
Significant Factors

Extreme hydrological situations constantly disturb the earth activities and life, to envisage such extreme activities we need a system that alarms well on time and recognized the expected danger; to prepare such systems one must have knowledge of the significant factors that are actively responsible for such extreme situations and we should have a reliable statistical technique that helps to prepare a useful model for such systems. In this paper we investigate the historical data of peak flood from several gauging stations of river Jhelum in Kashmir, India. A reliable estimation technique (L-moment) is applied for parametric estimation of the probability distributions and a reliable testing techniques are used to check the accuracy of fitting of the distribution, in additional to that L-moment ratio diagram (LMRD) is used to impart information about fitting of distribution. Log Pearsons-III distribution shows better results and satisfies tests of distribution fitting, same probability distribution is globally accepted for flood forecasting.

scholarly journals A Random Factorial Design of Experiments Study on the Influence of Key Factors and Their Interactions on the Measurement Uncertainty: A Case Study Using the ZEISS CenterMax

2019 ◽  
Vol 10 (1) ◽  
pp. 37 ◽  
Author(s):  
Michaela Kritikos ◽  
Lissette Concepción Maure ◽  
Alfredo Alejandro Leyva Céspedes ◽  
Daynier Rolando Delgado Sobrino ◽  
Róbert Hrušecký
Keyword(s):  
Design Of Experiments ◽  
Measurement Uncertainty ◽  
Factorial Design ◽  
Coordinate Measuring Machine ◽  
Standard Uncertainty ◽  
Step Width ◽  
Key Factors ◽  
Measuring Machine ◽  
Factorial Design Of Experiments ◽  
Measurement And Evaluation

This paper addresses the uncertainty analysis in the case of a coordinate measuring machine. The main goal was analyzing, quantifying, and drawing conclusions on the influence of key factors and their interactions on the measurements’ uncertainty of the variable’s parallelism, angularity, roundness, diameter, and distance. In order to achieve this goal, a Random Factorial Design of Experiments was designed and implemented. It focused on the factors Stylus diameter, Step width, and Speed using three random levels each. For the solution of the experiment, an analysis of variance was used. The study was carried out on the coordinate measuring machine (CMM) ZEISS CenterMax. It was concluded that the interaction effects among Stylus diameter, Step width, and Speed were active at a confidence level of 95%. Besides, it was possible to estimate random factors‘ variance and their contribution to the total variation. Among the main effects, the Stylus diameter showed to be the one with the biggest influence. The paper also quantifies the influence in the measurement uncertainty, where the highest value of standard uncertainty belonged to the Stylus diameter in the evaluation of the variable’s angularity and diameter. Besides, the Speed factor was proved to have the biggest influence on the roundness’ measurement and evaluation.

A Study of the Impact of Knurling Parameters on Knurl Quality With the Design of Experiments Approach

1999 ◽  
Author(s):  
Chang-Xue (Jack) Feng ◽  
Chinh Tran
Keyword(s):  
Design Of Experiments ◽  
Process Parameters ◽  
Process Design ◽  
Fractional Factorial ◽  
Key Factors ◽  
Local Company ◽  
Factor Interactions ◽  
The Impact ◽  
Error Method

Abstract A local company produces various types of connecting cables for a number of military and civilian customers. A key part of these cables is the knurled component to provide proper frictional force for easy assembly and maintenance. In the past, the company has usually faced a problem of inconsistent knurl quality. There has been no report in the literature about knurling process design. Vendors of knurling tools could only recommend the traditional try-and-error method. This research uses the design of experiments (or 2n-k fractional factorial design) approach to examine the impact of different knurling process parameters on the knurl quality. Our purpose is to determine the key factors and factor interactions that have significant effect on the knurl quality so that we could set the process parameters in such a way that the process is robust (or insensitive) to any uncontrollable factors. As a result, a robust knurl quality is achieved. A case study illustrates our approach.

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