Investigation of the effect of temperature and other significant factors on systematic error and measurement uncertainty in CMM measurements by applying design of experiments

Measurement ◽  
2020 ◽  
Vol 158 ◽  
pp. 107692 ◽  
Author(s):  
Branko Štrbac ◽  
Bojan Ačko ◽  
Sara Havrlišan ◽  
Ivan Matin ◽  
Borislav Savković ◽  
...  
Keyword(s):  
Design Of Experiments ◽  
Measurement Uncertainty ◽  
Systematic Error ◽  
Effect Of Temperature ◽  
Significant Factors

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.

Measurement uncertainty from physical sample preparation: estimation including systematic error

The Analyst ◽  
2003 ◽  
Vol 128 (11) ◽  
pp. 1391 ◽  
Author(s):  
Jennifer A. Lyn ◽  
Michael H. Ramsey ◽  
Richard J. Fussell ◽  
Roger Wood
Keyword(s):  
Sample Preparation ◽  
Measurement Uncertainty ◽  
Systematic Error

scholarly journals The Germination Responses of Five Bermudagrass Cultivars to Seedcoating and Temperature

HortScience ◽  
2014 ◽  
Vol 49 (9) ◽  
pp. 1225-1229 ◽  
Author(s):  
Gregg C. Munshaw ◽  
John M. Layton ◽  
Barry R. Stewart ◽  
H. Wayne Philley ◽  
Jeffrey S. Beasley ◽  
...  
Keyword(s):  
Cynodon Dactylon ◽  
Germination Percentage ◽  
Effect Of Temperature ◽  
The Past ◽  
Temperature Regimes ◽  
Cumulative Count ◽  
Turfgrass Quality ◽  
Standard Cultivar ◽  
Significant Factors

As turfgrass quality of seeded bermudagrass (SB) [Cynodon dactylon (L.) Pers.] cultivars has increased over the past 20 years, so has their use. Improved SB cultivars offer ease of establishment and convenience of storage while providing an economic advantage over vegetative propagation. Currently, most improved seeded cultivars are marketed with a seedcoating unique to each seed company. However, germination of some of the new cultivars is not ideal. The objectives of this study were to determine commercial coating effects on germination, compare germination among cultivars, and evaluate the effect of temperature on germination of five bermudagrass cultivars. ‘Princess-77’, ‘Riviera’, ‘Transcontinental’, and ‘Yukon’ were selected for a series of 21-day germination studies with ‘Arizona Common’ included as a standard cultivar. The study compared two seed lots of coated and uncoated samples of the five cultivars for germination response to six temperature regimes. Cumulative count intervals occurred on Day 7, Day 14, and Day 21. Overall, commercial seedcoating did not significantly affect SB germination. However, both temperature regime and cultivar were significant factors. Germination percentage was greatest with either the 35/25 °C or the 30/20 °C temperature regimes. ‘Riviera’ exhibited the lowest overall germination, whereas ‘Transcontinental’ and ‘Arizona Common’ exhibited the highest.

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.

Investigation of FEF process liquid phase migration using orthogonal design of experiments

2019 ◽  
Vol 25 (2) ◽  
pp. 388-396 ◽  
Author(s):  
Cunfu Yan ◽  
Shujuan Li ◽  
Leipeng Yang ◽  
Longfei He
Keyword(s):  
Liquid Phase ◽  
Design Of Experiments ◽  
Initial Conditions ◽  
Orthogonal Design ◽  
Analysis Method ◽  
Range Analysis ◽  
Content Type ◽  
Interval Time ◽  
Extrusion Head ◽  
Significant Factors

Purpose The purpose of this paper is to investigate the effects of parameters on the liquid phase migration (LPM) during the freeze-form extrusion fabrication (FEF) process. Design/methodology/approach To carry out this study, three factors were systematically investigated using orthogonal design of experiments. These three parameters are the extrusion velocity, the extrusion interval time and the extrusion head length. An orthogonal array with nine test units was selected for the experiments. Range analysis and analysis of variance were used to analyze the data obtained by the orthogonal experiments to identify the order of significant factors on LPM. Findings It was found that the LPM decreased with the increase of extrusion velocity and increased with the lengthening of extrusion interval time and the length of the extrusion nozzle. The order of significant factors for the LPM were found to be extrusion velocity > extrusion nozzle length > extrusion interval time. Practical implications Using an orthogonal design of experiments and a statistical analysis method, the liquid content of extrudate can be predicted and appropriate process parameter values can be selected. This leads to the minimization of LPM during the FEF process. Also, this analysis method could be used to study the LPM in other paste extrusion processes. Originality/value This paper suggests that the factors have significant impact on LPM during FEF process. The following analysis in this paper is useful for FEF users when prediction of LPM is needed. This methodology could be easily applied to different materials and initial conditions for optimization of other FEF-type processes. The research can also help to get better understanding of LPM during the FEF process.

Optimization on Selective Fiber Laser Sintering of Bimetallic Powder via Design of Experiments Method

2012 ◽  
Author(s):  
Hsin-Te Liao ◽  
Manh Trung Le ◽  
Dinh Vuong Long
Keyword(s):  
Design Of Experiments ◽  
Powder Mixture ◽  
Optimal Parameter ◽  
Process Analysis ◽  
Selective Laser Sintering ◽  
Base Material ◽  
Laser Sintering ◽  
Strong Interactions ◽  
Parameter Setting ◽  
Significant Factors

The objective of this study is to investigate the effect of various parameters on rapid prototyping parts for processes of sintering metallic powder mixture by using Ytterbium fiber optic laser via the design of experiments (DOE) method. Experiments based on the DOE method were utilized to determine an optimal parameter setting for achieving a minimum amount of porosities in specimens during the selective laser sintering (SLS) process. Analysis of variance (ANOVA) was further conducted to identify significant factors. A regression model predicting percentages of porosities under various conditions was developed when the traditional Taguchi’s approach failed to identify a feasible model due to strong interactions of controlled factors. The significant factors to the process were identified by ANOVA. Four controlled factors including pulse frequencies and scan rate of laser beams, laser power and scan line spacing with particle sizes of 75μm of the powder mixture base material had significant influence on the sintering process. Future investigation planned to be carried out for achieving multiple quality targets such as the hardness and the density for 3D parts. The implementation of the DOE method provided a systematic approach to identify an optimal parameter setting of the SLS process; thus, the efficiency of designing optimal parameters was greatly improved. This approach could be easily extended to 3D cases by just including additional parameters into the design. Additionally, utilization of the normality analysis on the residual data ensured that the selected model was adequate and extracted all applicable information from the experimental data.

scholarly journals A Possibilistic Kalman Filter for the Reduction of the Final Measurement Uncertainty, in Presence of Unknown Systematic Errors

Metrology ◽  
2021 ◽  
Vol 1 (1) ◽  
pp. 39-51
Author(s):  
Harsha Vardhana Jetti ◽  
Simona Salicone
Keyword(s):  
Kalman Filter ◽  
Measurement Uncertainty ◽  
Systematic Error ◽  
Kalman Filters ◽  
Systematic Errors ◽  
The State ◽  
Fuzzy Variables ◽  
Final Measurement ◽  
Random Fuzzy Variables ◽  
System States

A Kalman filter is a concept that has been in existence for decades now and it is widely used in numerous areas. It provides a prediction of the system states as well as the uncertainty associated to it. The original Kalman filter can not propagate uncertainty in a correct way when the variables are not distributed normally or when there is a correlation in the measurements or when there is a systematic error in the measurements. For these reasons, there have been numerous variations of the original Kalman filter, most of them mathematically based (like the original one) on the theory of probability. Some of the variations indeed introduce some improvements, but without being completely successful. To deal with these problems, more recently, Kalman filters have also been defined using random-fuzzy variables (RFVs). These filters are capable of also propagating distributions that are not normal and propagating systematic contributions to uncertainty, thus providing the overall measurement uncertainty associated to the state predictions. In this paper, the authors make another step forward, by defining a possibilistic Kalman filter using random-fuzzy variables which not only considers and propagates both random and systematic contributions to uncertainty, but also reduces the overall uncertainty associated to the state predictions by compensating for the unknown residual systematic contributions.

Uncertainty Analysis for Fiber Permeability Measurement

2005 ◽  
Vol 127 (4) ◽  
pp. 907-911 ◽  
Author(s):  
Chensong Dong
Keyword(s):  
Measurement Uncertainty ◽  
Uncertainty Propagation ◽  
Permeability Measurement ◽  
Parameter Uncertainties ◽  
Factors Affecting ◽  
Sources Of Uncertainty ◽  
Measurement Results ◽  
Simulation Results ◽  
Instrument Accuracy ◽  
Significant Factors

An uncertainty study for fiber permeability measurement is presented in this paper. The sources of uncertainty were identified. This paper focuses on the instrument and environmental uncertainties. The parameter uncertainties of both unsaturated and saturated measurements were estimated based on instrument accuracy limitations and environmental influences. Their influences on the permeability uncertainty were investigated by uncertainty propagation and Monte Carlo simulation. The significant factors affecting the permeability measurement uncertainty were identified. The results show that (1) unsaturated measurement has a higher accuracy than saturated measurement; (2) the significant factors affecting measurement results are pressure and viscosity. Based on the simulation results, the approaches to reduce measurement uncertainty were proposed.

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 Highly Optimized Nitrogen-Doped MWCNTs through In-Depth Parametric Study Using Design of Experiments

Nanomaterials ◽  
2019 ◽  
Vol 9 (4) ◽  
pp. 643 ◽  
Author(s):  
Alexander Plunkett ◽  
Katharina Kröning ◽  
Bodo Fiedler
Keyword(s):  
Carbon Nanotubes ◽  
Design Of Experiments ◽  
Doping Level ◽  
Gas Flow ◽  
Effect Of Temperature ◽  
Process Conditions ◽  
Nitrogen Doped ◽  
Aspect Ratios ◽  
Informative Content ◽  
Nitrogen Doped Carbon

The in-situ nitrogen doping of multiwalled carbon nanotubes via chemical vapor deposition is investigated employing design of experiments (DoE). The establishment of empirical DoE models allowed for the prediction of product features as a function of process conditions in order to systematically synthesize tailor-made nitrogen-doped carbon nanotubes. The high informative content of this approach revealed effects of individual parameters and their interaction with each other. Hence, new valuable insights into the effect of temperature, injection rate, and carrier gas flow on the doping level were obtained which give motivation to approach further theoretical studies on the doping mechanism. Ultimately, competitive nitrogen-doped carbon nanotube features were optimized and yielded promising combinations of achieved doping level, graphitization, and aspect ratios in comparison to present literature values.

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