Diagnosing Multistage Manufacturing Processes With Engineering-Driven Factor Analysis Considering Sampling Uncertainty

2013 ◽  
Vol 135 (4) ◽  
Author(s):  
Jian Liu ◽  
Jionghua Jin
Keyword(s):  
Factor Analysis ◽  
Spatial Variation ◽  
Identification Problem ◽  
Factor Loading ◽  
Manufacturing Processes ◽  
Multistage Manufacturing ◽  
Factor Rotation ◽  
Variation Patterns ◽  
True Values

A new engineering-driven factor analysis (EDFA) method has been developed to assist the variation source identification for multistage manufacturing processes (MMPs). The proposed method investigated how to fully utilize qualitative engineering knowledge of the spatial variation patterns to guide the factor rotation. It is shown that ideal identification can be achieved by matching the rotated factor loading vectors with the qualitative indicator vectors (IV) that are defined according to spatial variation patterns based on the design constraints. However, the random sampling variability may significantly affect the estimation of the rotated factor loading vectors, leading to the deviations from their true values. These deviations may change the matching results and cause misidentification of the actual variation sources. By using implicit differentiation approach, this paper derives the asymptotic distribution and the associated variance-covariance matrix of the rotated factor loading vectors. Therefore, by considering the effect of sample estimation variability, the variation sources identification problem is reformulated as an asymptotic statistical test of the hypothesized match between the rotated factor loading vectors and the indicator vectors. A real-world case study is provided to demonstrate the effectiveness of the proposed matching method and its robustness to the sample uncertainty.

Engineering-Driven Factor Analysis for Variation Source Identification in Multistage Manufacturing Processes

2008 ◽  
Vol 130 (4) ◽  
Author(s):  
Jian Liu ◽  
Jianjun Shi ◽  
S. Jack Hu
Keyword(s):  
Factor Analysis ◽  
Source Identification ◽  
Domain Knowledge ◽  
Measurement Data ◽  
Factor Loading ◽  
Data Driven ◽  
Manufacturing Processes ◽  
Multistage Manufacturing ◽  
Engineering Models

Variation source identification is an important task of quality assurance in multistage manufacturing processes (MMPs). However, existing approaches, including the quantitative engineering-model-based methods and the data-driven methods, provide limited capabilities in variation source identification. This paper proposes a new methodology that does not depend on accurate quantitative engineering models. Instead, engineering domain knowledge about the interactions between potential variation sources and product quality variables is represented as qualitative indicator vectors. These indicator vectors guide the rotation of the factor loading vectors that are derived from factor analysis of the multivariate measurement data. Based on this engineering-driven factor analysis, a procedure is presented to identify multiple variation sources that are present in a MMP. The effectiveness of the proposed methodology is demonstrated in a case study of a three-stage assembly process.

scholarly journals Empirically derived dietary patterns: interpretability and construct validity according to different factor rotation methods

2015 ◽  
Vol 31 (2) ◽  
pp. 298-310 ◽  
Author(s):  
Michelle Alessandra de Castro ◽  
Valéria Troncoso Baltar ◽  
Soraya Sant'Ana de Castro Selem ◽  
Dirce Maria Lobo Marchioni ◽  
Regina Mara Fisberg
Keyword(s):  
Factor Analysis ◽  
Construct Validity ◽  
Exploratory Factor Analysis ◽  
Dietary Patterns ◽  
Goodness Of Fit ◽  
Factor Loading ◽  
Model Fit ◽  
Factor Rotation ◽  
Rotation Methods ◽  
Fit Indexes

This study aimed to investigate the effects of factor rotation methods on interpretability and construct validity of dietary patterns derived in a representative sample of 1,102 Brazilian adults. Dietary patterns were derived from exploratory factor analysis. Orthogonal (varimax) and oblique rotations (promax, direct oblimin) were applied. Confirmatory factor analysis assessed construct validity of the dietary patterns derived according to two factor loading cut-offs (≥ |0.20| and ≥ |0.25|). Goodness-of-fit indexes assessed the model fit. Differences in composition and in interpretability of the first pattern were observed between varimax and promax/oblimin at cut-off ≥ |0.20|. At cut-off ≥ |0.25|, these differences were no longer observed. None of the patterns derived at cut-off ≥ |0.20| showed acceptable model fit. At cut-off ≥ |0.25|, the promax rotation produced the best model fit. The effects of factor rotation on dietary patterns differed according to the factor loading cut-off used in exploratory factor analysis.

A Comparison of Simple Structure Rotation Criteria in Temporal Exploratory Factor Analysis for Event-Related Potential Data

Methodology ◽  
2019 ◽  
Vol 15 (Supplement 1) ◽  
pp. 43-60 ◽  
Author(s):  
Florian Scharf ◽  
Steffen Nestler
Keyword(s):  
Factor Analysis ◽  
Exploratory Factor Analysis ◽  
Simple Structure ◽  
Ground Truth ◽  
Event Related Potential ◽  
Suitable Alternative ◽  
Factor Rotation ◽  
Rotation Methods ◽  
Simple Structure Rotation ◽  
Temporal Overlap

Abstract. It is challenging to apply exploratory factor analysis (EFA) to event-related potential (ERP) data because such data are characterized by substantial temporal overlap (i.e., large cross-loadings) between the factors, and, because researchers are typically interested in the results of subsequent analyses (e.g., experimental condition effects on the level of the factor scores). In this context, relatively small deviations in the estimated factor solution from the unknown ground truth may result in substantially biased estimates of condition effects (rotation bias). Thus, in order to apply EFA to ERP data researchers need rotation methods that are able to both recover perfect simple structure where it exists and to tolerate substantial cross-loadings between the factors where appropriate. We had two aims in the present paper. First, to extend previous research, we wanted to better understand the behavior of the rotation bias for typical ERP data. To this end, we compared the performance of a variety of factor rotation methods under conditions of varying amounts of temporal overlap between the factors. Second, we wanted to investigate whether the recently proposed component loss rotation is better able to decrease the bias than traditional simple structure rotation. The results showed that no single rotation method was generally superior across all conditions. Component loss rotation showed the best all-round performance across the investigated conditions. We conclude that Component loss rotation is a suitable alternative to simple structure rotation. We discuss this result in the light of recently proposed sparse factor analysis approaches.

Professional Stress among Junior Commissioned Officers and Non Commissioned Officers of Indian Military Intelligence – A Case Study

GIS Business ◽  
2019 ◽  
Vol 14 (6) ◽  
pp. 133-145
Author(s):  
Dr. S. S. Nirmala ◽  
Dr. N. Kogila ◽  
T. Porkodi
Keyword(s):  
Factor Analysis ◽  
Correlation Matrix ◽  
Null Hypothesis ◽  
Primary Data ◽  
Questionnaire Data ◽  
Military Intelligence ◽  
Sphericity Test ◽  
Professional Stress ◽  
Structured Questionnaire

The present study is focusing on the professional stress on organisation among the Junior Commissioned Officers (JCOs) and Non-Commissioned Officers (NCOs) of Indian Military Intelligence. 384 samples of Military Intelligence personnel will be taken for this study. Sources of data is Primary data include a structured questionnaire. Data was collected through structured questionnaire and measure through Likert’s scale, using KMO measure of sampling adequacy, Cronbach’s alpha for checking internal consistency, Bartlett sphericity test for testing the null hypothesis and various factor analysis including Eigenvalues, Extract square Sum loading, variance percent and Accumulation percent values relative comparison and Correlation matrix will be used as tools to arrive at desired results and statistical interpretations. The hypotheses put for test and the resultant values at 0.01 and 0.05 (for different factors) clearly indicated that there is an existence of association between different level of cadres and professional stress among personnel of Indian Military Intelligence. The authority who can formulate the rules and regulations and binding them on the lower cadres and professions to accept and adopt.

Depression among children at shelter care institutions in Terengganu Malaysia

2020 ◽  
Vol 11 (1) ◽  
pp. 17
Author(s):  
Siti Hajar Abdul Rauf ◽  
Asmah Ismail ◽  
Nuratikah Azima Razali ◽  
Ahmad Bisyri Husin Musawi Maliki
Keyword(s):  
Factor Analysis ◽  
Quantitative Research ◽  
Family Stress ◽  
Factor Loading ◽  
Self Esteem ◽  
Keywords Children ◽  
Self Confidence ◽  
Confirmatory Factor ◽  
The Status ◽  
Forward Stepwise

Background: Depression is a state of psychological disease that occurs to someone divers in age due to certain reasons. Among the factors include lack of self-confidence, problematic family, stress, low self-esteem and social environment. It could lead to a mental disorder that endangers the mental health. Aim: To investigate the status of children depression using the Children Depression Inventory (CDI) at 21 shelter care institutions in Terengganu Malaysia. Methodology: Quantitative research design was used. The sample consists of 404 respondents from 21 Islamic shelter cares such as Tahfiz, Madrasah and Orphanage in Terengganu Malaysia from the age of 10 to 18 years. Data was analyzed using Exploratory Factor Analysis (EFA), Confirmatory Factor Analysis (CFA) and Discriminant Analysis (DA) which then computed to identify the most dominant factors whereas reducing the initial five parameters with recommended >0.50 of factor loading. Results: Forward stepwise of DA shows the total of groups validation percentage by 92.08% (17 independent). The result showed that the highest frequency of respondent index was at a moderate level (62.87% respondents). This showed that children still can be controlled and cared to reduce depression. Keywords: Children Depression Index, Depression, Children, Institution, Shelter Care

On the Dimensionality of Measuring Tourist Satisfaction towards Homestay

2015 ◽  
Vol 8 (2) ◽  
Author(s):  
Gangaram Biswakarma
Keyword(s):  
Factor Analysis ◽  
Data Collection ◽  
Exploratory Factor Analysis ◽  
Life Style ◽  
Factor Loading ◽  
Primary Data ◽  
Cultural Performance ◽  
Latent Construct ◽  
Tourist Satisfaction ◽  
The Relationship

This study focuses on measuring tourist satisfaction towards home stay. This paper emphasized to identify the variables that are related to tourist satisfaction during tourist homestay. It is also focused on analyzing the relationship and impact of these latent construct of factors to overall tourist satisfaction towards home stay. In an attempt to visualize the purpose, tourists satisfaction in a homestay in Nepal has taken into as a case, with an aim to identify the underlying dimensions of tourist satisfaction during tourist homestay. Twenty six (26) manifest variables of homestay has been formulated to understand the dimensions. Likewise, for a conforming the latent construct (1) statement as dependent variable of overall satisfaction was developed for the purpose of the primary data collection. The manifest variables are basically focused on aspects of home stay attributes namely cultural attraction, hospitality, amenities and safety & security at the home stay destination. Post Exploratory Factor Analysis indicates factor loading for twenty two (22) items manifest variables as significant, loaded with five (5) factors of home stay attributes named as Amenities & Safety, Reception, Local Cuisine & Accommodation, Local Life style & Costumes, and Cultural Performance. This study contributes to the development of survey instrument for exploring tourist satisfaction for Home stay for future researchers.

Indigenization in a downgraded continuum: Ideologies behind phonetic variation in Namibian Afrikaans

2020 ◽  
Vol 0 (0) ◽  
Author(s):  
Gerald Stell
Keyword(s):  
South Africa ◽  
Power Relations ◽  
African Country ◽  
Language Ideologies ◽  
Ethnically Diverse ◽  
Official Language ◽  
Phonetic Variation ◽  
Variation Patterns ◽  
Standard Models

AbstractThis study generally looks at indigenization in languages historically introduced and promoted by colonial regimes. The case study that it presents involves Namibia, a Subsaharan African country formerly administered by South Africa, where Afrikaans was the dominant official language before being replaced by English upon independence. Afrikaans in Namibia still functions as an informal urban lingua franca while being spoken as a native language by substantial White and Coloured minorities. To what extent does the downranking of Afrikaans in Namibia co-occur with divergence from standard models historically located in South Africa? To answer this question, the study identifies variation patterns in Namibian Afrikaans phonetic data elicited from ethnically diverse young urban informants and links these patterns with perceptions and language ideologies. The phonetic data reveal divergence between Whites and Non-Whites and some convergence among Black L2 Afrikaans-speakers with Coloured varieties, while suggesting that a distinctive Black variety is emerging. The observed trends generally reflect perceived ethnoracial distinctions and segregation. They must be read against the background of shifting inter-group power relations and sociolinguistic prestige norms in independent Namibia, as well as of emergent ethnically inclusive Black urban identities.

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