Effect of crosslinking agents on the strength characteristics of cellulosic fabrics using 23 32 mixed level factorial

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Farhana Naeem ◽  
Fareha Asim ◽  
Muhammad Tufail
Keyword(s):  
High Strength ◽  
Strength Characteristics ◽  
Blend Ratio ◽  
Tear Strength ◽  
Content Type ◽  
Factors Affecting ◽  
Acrylate Copolymer ◽  
Curing Method ◽  
Crosslinking Agents ◽  
Significant Factors

Purpose Low pilling and wrinkle-free appearance of cellulosic fabrics are always demanded. Resin finishes are applied to improve these properties, but there is an adverse effect of the resin finish as it tends to reduce the strength of the fabrics. Therefore, the effect of the two most important finishes; anti-pilling and resin finish, on the strength characteristics of 100% viscose and 50:50 Viscose/cotton plain and satin fabrics were investigated in this paper. The purpose of this study is to identify significant factors affecting the strength of fabrics finished with crosslinking agents [non-ionic acrylate copolymer and (dimethyloldihydroxyethyleneurea)]. Design/methodology/approach A statistical model of 23 32 mixed level factorial design was used for the study. Appratan N9211 (A) and Arkofix NF (B) were tested at three concentrations, whereas three factors fabric; weave (C), blend ratio (D) and curing method (E) were tested at two levels. The performance of the finish was evaluated by two response variables, which were tensile and tear strength. Findings The various conditions of high strength values of the fabrics were presented in this paper. It was found that the tear strength of the fabrics increased after finishing except for 50:50 viscose/cotton plain fabric, whereas the tensile strength of plain fabrics is better at shock cure and for a satin normal cure is better. The model adequacy plots exhibit that the assumptions of normality and independence are not desecrated. Moreover, the values of “predicted R2” are in reasonable agreement with the “adjusted R2,” which confirms that models have been accounted for most of the inconsistency. Originality/value This paper is a part of my PhD dissertation. Unlike the previous studies, this paper investigated the effect of two crosslinking agents, Appretan N9211 as anti-pilling and Arkofix NF as wrinkle resistant agents on 100% viscose and 50:50 viscose/cotton plain and satin. Three different concentrations of both the crosslinking agents were used. Also, fixation of the finishes was carried out at a normal cure and shock cure.

Assessment of the significance of factors affecting the growth of women entrepreneurs: study based on experience categorization

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Sucheta Agarwal ◽  
Veland Ramadani ◽  
Leo-Paul Dana ◽  
Vivek Agrawal ◽  
Jitendra Kumar Dixit
Keyword(s):  
Emerging Economies ◽  
Women Entrepreneurs ◽  
Uttar Pradesh ◽  
Sustainable Growth ◽  
Gender Orientation ◽  
Content Type ◽  
Factors Affecting ◽  
Emerging Nations ◽  
Practical Implications ◽  
Significant Factors

Purpose The ascent of women enterprising community (WEC) in a couple of decades draws the attention of various government and non-government bodies. Literature has mentioned various studies that focus on the factors affecting the success or failure of women entrepreneurs (WEs), but understanding of the ranking of the factors depending on the experiences of different WEs is needed. This study aims to identify the significant factors essential for the growth of WEC. Design/methodology/approach This study examines the factors through interview of 33 WEs having different entrepreneurial experiences (less than 1 year, more than 1 year but less than 10 years and more than 10 years of experiences) from different regions of Uttar Pradesh, India, and with the help of analytical hierarchical process, ranks the factors affecting the sustainable growth of WEs. Findings Through analysis, significant factors have been identified such as determination, education, entrepreneurial resilience, personal satisfaction and provide employment, and these factors have been analysed according to the different experiences of WEs. An investigation of ranking these factors of WEC, especially in the emerging nations, can assist policymakers in designing projects that improve the mindfulness associated with women enterprise and define the compelling methodologies. Practical implications The growth of the WEC is significantly affected by gender orientation ways of thinking as driven by entrepreneurship models. Originality/value This study gives a direction to policymakers by emphasizing on significant factors of various stages of enterprise development for the encouragement of WEs in the emerging economies.

scholarly journals Fatigue Performance of Thin Laser Butt Welds in HSLA Steel

Metals ◽  
2021 ◽  
Vol 11 (10) ◽  
pp. 1499
Author(s):  
Patricio G. Riofrío ◽  
Fernando Antunes ◽  
José Ferreira ◽  
António Castanhola Batista ◽  
Carlos Capela
Keyword(s):  
Fatigue Strength ◽  
Fatigue Behavior ◽  
Hsla Steel ◽  
High Strength ◽  
Butt Joints ◽  
Factors Affecting ◽  
Weld Profile ◽  
The Relationship ◽  
Good Agreement ◽  
Significant Factors

This work is focused on understanding the significant factors affecting the fatigue strength of laser-welded butt joints in thin high-strength low-alloy (HSLA) steel. The effects of the weld profile, imperfections, hardness, and residual stresses were considered to explain the results found in the S-N curves of four welded series. The results showed acceptable fatigue strength although the welded series presented multiple-imperfections. The analysis of fatigue behavior at low stress levels through the stress-concentrating effect explained the influence of each factor on the S-N curves of the welded series. The fatigue limits of the welded series predicted through the stress-concentrating effect and by the relationship proposed by Murakami showed good agreement with the experimental results.

Identifying interrelationships among factors affecting innovation archetypes: the case of China

2020 ◽  
Vol 12 (4) ◽  
pp. 409-432
Author(s):  
Rafif Al-Sayed ◽  
Jianhua Yang
Keyword(s):  
Statistical Analysis ◽  
Multivariate Statistical Analysis ◽  
Design Methodology ◽  
Decision Makers ◽  
Innovation Ecosystem ◽  
Multivariate Statistical ◽  
Content Type ◽  
Factors Affecting ◽  
Practical Implications ◽  
Significant Factors

Purpose This paper aims at studying the concept of innovation ecosystems and investigating the factors affecting them based on their interrelationships with respect to different innovation archetypes. Design/methodology/approach The methodology is based on using multivariate statistical analysis of the inter-correlations among a number of variables which led to extracting a reduced set of new significant factors that affect China’s innovation ecosystem. Findings The results showed that innovation archetypes differ significantly with respect to the majority of the new factors. Practical implications Through identifying these challenges, decision-makers can develop a better understanding of the variables affecting each archetype of innovation and act accordingly. Originality/value The study is the first to fill the gap of addressing a large number of variables affecting innovation and analyzing their interrelationships.

A new model for analyzing the role of new ICT-based technologies on the success of employees' learning programs

Kybernetes ◽  
2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Amir Masoud Rahmani ◽  
Ali Ehsani ◽  
Mokhtar Mohammadi ◽  
Adil Hussein Mohammed ◽  
Sarkhel H. Taher Karim ◽  
...  
Keyword(s):  
Content Management ◽  
Evaluation Tools ◽  
Employee Education ◽  
Content Type ◽  
Factors Affecting ◽  
Learning Programs ◽  
Virtual Classes ◽  
E Learning ◽  
Significant Factors

PurposeThe concept of e-learning is essential in employee education since it provides different ways to develop employees' knowledge, skills and attitudes using modern technologies. E-learning has been overgrowing in employee education because learning can be held anytime and anywhere. In order to succeed in implementing e-learning and benefiting from its capacities, and avoiding potential threats in the country, it is necessary to address the factors affecting its success. This paper aims to test the role of internet of Things (IoT)-based systems, cloud-based services, virtual classes, evaluation tools, attitude, content management and creativity on the success of employees' e-learning programs based on a framework.Design/methodology/approachE-learning systems receive ever-increasing attention in academia, business and public administration. With the development of e-learning, employee education has also benefited from its capacities in various fields. To succeed in implementing e-learning and benefiting from its capacities, and avoiding potential threats in the country, it is necessary to address its success. The proposing of Information and Communications Technology (ICT)-based technologies such as the IoT, cloud, etc., in e-learning, can help transform education. Therefore, this paper aims to test the role of IoT-based systems, cloud-based services, virtual classes, evaluation tools, attitude, content management and creativity on the success of employees' e-learning programs based on a framework. The research model and the data collected from the questionnaires have been analyzed via Smart PLS 3.2. This study has utilized the SEM to evaluate the causal model's reliability and validity based on measurement. According to the literature in this study, a framework has been proposed that examines the impact of IoT-based systems, cloud-based services, virtual classes, evaluation tools, attitude, content management and creativity on employees' learning programs' success.FindingsThe results have shown that IoT-based systems, cloud-based services, virtual classes and evaluation tools are four significant factors affecting attitude, content management and creativity. The results have also shown that attitude, content management and creativity are three significant factors affecting employees' learning programs' success. The factors above are considered critical in explaining the success of employees' e-learning programs, but, as far as we know, there has been no study in which all these factors were demonstrated together.Practical implicationsFrom a practical viewpoint, the statistical outcomes support the important role of the following factors: IoT-based systems, cloud-based services, virtual classes, evaluation tools, attitude, content management and creativity. Henceforth, aspects relating to these factors got the attention of any organization to develop e-learning processes.Originality/valueThis research will contribute to the literature related to employees' e-learning programs' success by integrating all the mentioned variables. As far as we know, it is the first study to test these variables in Iran.

Factors affecting the number of building defects and the approaches to reduce their negative impacts in Malaysian public universities’ buildings

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Ali Hauashdh ◽  
Junaidah Jailani ◽  
Ismail Abdul Rahman ◽  
Najib Al-Fadhali
Keyword(s):  
Environmental Sustainability ◽  
Qualitative Data ◽  
Maintenance Phase ◽  
Research Strategy ◽  
Content Type ◽  
Factors Affecting ◽  
Building Maintenance ◽  
Safety And Health ◽  
Negative Impacts ◽  
Significant Factors

Purpose The largest share of a building maintenance budget goes towards preventing or repairing building defects. Also, building defects shorten a building’s lifetime, impact the user’s safety and health, prevent the buildings from performing their functions well and repairing building defects generates waste. Therefore, this study aims to specify the factors that affecting the number of building defects and how to reduce their negative impacts. Design/methodology/approach A case study was used as a research strategy and convergent parallel mixed methods were used as research design. Quantitative and qualitative data were collected concurrently, followed by independent analyses of the quantitative and qualitative data, and then merged the two sets of results according to the procedure of using the convergent parallel design. Descriptive statistics analysed quantitative data, whilst qualitative data was analysed by the content analysis technique. Findings The findings of this study explored the factors that affect the number of defects in buildings, the significant factors were related to the building’s life cycle in terms of design, construction, operation and maintenance phase; relevant attributes were construction teams, building users and maintenance teams. The study also addressed the approaches to minimise the negative impacts of those factors. Their negative impacts mainly contributed to increased building defects that increase maintenance costs, affect users’ safety and health, reduce buildings’ lifespan and cause environmental impact due to resource extraction. Originality/value The existing studies have not adequately addressed the significant factors that affect the number of building defects. Also, emerging technologies and environmental sustainability considerations related to building defects have not been linked in previous related work. Therefore, the present study has contributed to filling this gap.

Wavelet and multiple linear regression analysis for identifying factors affecting particulate matter PM2.5 in Mumbai City, India

2019 ◽  
Vol 36 (10) ◽  
pp. 1750-1783 ◽  
Author(s):  
Vivekanand Venkataraman ◽  
Syed Usmanulla ◽  
Appaiah Sonnappa ◽  
Pratiksha Sadashiv ◽  
Suhaib Soofi Mohammed ◽  
...  
Keyword(s):  
Regression Analysis ◽  
Linear Regression ◽  
Multiple Linear Regression ◽  
Linear Regression Analysis ◽  
Multiple Linear Regression Analysis ◽  
Control Measures ◽  
Data Set ◽  
Content Type ◽  
Factors Affecting ◽  
Significant Factors

Purpose The purpose of this paper is to identify significant factors of environmental variables and pollutants that have an effect on PM2.5 through wavelet and regression analysis. Design/methodology/approach In order to provide stable data set for regression analysis, multiresolution analysis using wavelets is conducted. For the sampled data, multicollinearity among the independent variables is removed by using principal component analysis and multiple linear regression analysis is conducted using PM2.5 as a dependent variable. Findings It is found that few pollutants such as NO2, NOx, SO2, benzene and environmental factors such as ambient temperature, solar radiation and wind direction affect PM2.5. The regression model developed has high R2 value of 91.9 percent, and the residues are stationary and not correlated indicating a sound model. Research limitations/implications The research provides a framework for extracting stationary data and other important features such as change points in mean and variance, using the sample data for regression analysis. The work needs to be extended across all areas in India and for various other stationary data sets there can be different factors affecting PM2.5. Practical implications Control measures such as control charts can be implemented for significant factors. Social implications Rules and regulations can be made more stringent on the factors. Originality/value The originality of this paper lies in the integration of wavelets with regression analysis for air pollution data.

Redesigning one-warehousen-retailer routing model in inter-store stock transfer operations of an international retail chain distribution

2018 ◽  
Vol 30 (3) ◽  
pp. 536-554 ◽  
Author(s):  
Eugene Wong ◽  
Allen H. Tai ◽  
Yan Wei ◽  
Iris Yip
Keyword(s):  
Factor Analysis ◽  
Waiting Time ◽  
Six Sigma ◽  
Principal Component ◽  
Transfer Model ◽  
Delivery Time ◽  
Content Type ◽  
Factors Affecting ◽  
Retail Chain ◽  
Significant Factors

PurposeThe effectiveness of product replenishment and responsiveness of customer service delivery impact largely on satisfaction and retention of customers in retail chain logistics distribution. The fast moving goods in the complex delivery network and limited vehicle resource often lead to long customer waiting time in stock replenishment. With lack of literature systematically reviewing factors affecting retail distribution in inter-store stock transfer services and improving the operations, the purpose of this paper is to analyse and enhance this service for the retail to reduce customer dissatisfaction by developing an integrated quality service improvement methodology and an optimisation tool to improve the product delivery services.Design/methodology/approachThis paper reviews inter-store stock transfer operations and the process capability of an international retail chain, and proposes improvements by integrating Six Sigma, factor analysis, and optimisation modelling. User experience and expectations are evaluated through an empirical survey. A novel principle component factored inter-store stock transfer model is developed to improve replenishment operations. A total of 11 factors affecting inter-store stock transfer delivery time are analysed. An extended model with principal component factors incorporated is developed for the simulation.FindingsTheCpkvalue of 0.51 shows significant difference between the experienced and expected waiting time. With the inter-store stock transfer optimisation model developed, the model assists traffic personnel on the vehicle route planning with multiple pick-up and drop-off locations. The system also ensures the best routing with a minimal travelling time planned, facilitating a reduction of the inter-store stock transfer time, thus improving the customer waiting time. Four significant factors affecting the delivery time are also identified from exploratory and confirmatory factor analysis. The results are analysed with an extended principal component factored inter-store stock transfer model.Practical implicationsThe developed inter-store stock transfer models minimise stock transfer time, increase customer satisfaction, and reduce loss of sales. An integrated service quality improvement methodology has been developed and applied in reviewing significant factors affecting inter-store stock transfer operations.Originality/valueThis paper presents an analysis on inter-store stock transfer operations of an international retail and proposes enhancements on the operations by integrating Six Sigma, factor analysis, and optimisation modelling. A novel principal component factored inter-store stock transfer model is developed to improve the stock replenishment operations.

Development of similarity evaluation method between virtual and actual clothing

2017 ◽  
Vol 29 (5) ◽  
pp. 743-750 ◽  
Author(s):  
Seo Hyo Kim ◽  
Sungmin Kim ◽  
Chang Kyu Park
Keyword(s):  
Design Process ◽  
Design Methodology ◽  
Evaluation Method ◽  
Objective Evaluation ◽  
Virtual Space ◽  
Content Type ◽  
Factors Affecting ◽  
Garment Design ◽  
Practical Implications ◽  
Significant Factors

Purpose The purpose of this paper is to develop a similarity evaluation method between virtual and actual clothing. Design/methodology/approach The paper analyzes the subjective and objective evaluation results of virtual and actual clothing. Findings In this paper, significant factors affecting the evaluation of similarity between actual and virtual clothing have been found. Research limitations/implications Evaluation experiment was performed only for a skirt. However, the method can be easily applied for other types of garments. Practical implications The evaluation of similarity between actual and virtual garment will be facilitated. Social implications The garment design process can be facilitated by simulating garments in virtual space. Originality/value There has not been any quantitative evaluation method for the similarity of virtual and actual garment.

Application of natural dye on polytrimethylene terephthalate fiber

2019 ◽  
Vol 23 (1) ◽  
pp. 71-90 ◽  
Author(s):  
Arnab Sen ◽  
Avijit Bhowal ◽  
Siddhartha Datta
Keyword(s):  
Ferrous Sulfate ◽  
Design Methodology ◽  
Stannous Chloride ◽  
Natural Dye ◽  
Color Strength ◽  
Content Type ◽  
Factors Affecting ◽  
Dyeing Process ◽  
Initial Ph ◽  
Significant Factors

PurposeThis paper aims to investigate the feasibility of developing an eco-friendly dyeing process for a regenerated polyester fiber (polytrimethylene terephthalate) using a natural dye (Lac) and bio-mordant.Design/methodology/approachThe effects of temperature, time, initial pH of dye bath, material to liquor ratio and mordant concentration on color strength of polytrimethylene terephthalate fiber dyed with Lac were examined. The results were compared using three bio-mordant (catechu, myrobalan and pomegranate) and three inorganic mordant (alum, ferrous sulfate and stannous chloride). Single replicate of 25-design methodology was used to identify three significant factors affecting color strength, and optimization was done using response surface methodology based on 23-central composite rotatable design.FindingsColor strength achieved using catechu as a bio-mordant was close to that with ferrous sulfate and higher than with stannous chloride. Temperature, initial pH and mordant concentration were identified as significant factors affecting color strength of dyed fiber with catechu. Optimization revealed temperature of 133OC, initial pH of 6 and bio-mordant (Catechu) concentration of 10 per cent to be the optimal conditions for dyeing, with K/S value of 4.55.Originality/valueThe study revealed the possibility of satisfactory dyeing of regenerated polyester fibers with natural dyes, replacing disperse dyes. The comparison of color strength achieved indicated the possibility of replacing inorganic mordant with bio-mordant in such dyeing process. The dyeing process could thus be made more eco-friendly by removal of toxic chemicals from effluents.

Exploring influential factors affecting guest satisfaction

2020 ◽  
Vol 11 (1) ◽  
pp. 137-153 ◽  
Author(s):  
Minwoo Lee ◽  
Yanjun (Maggie) Cai ◽  
Agnes DeFranco ◽  
Jongseo Lee
Keyword(s):  
Social Media ◽  
Big Data ◽  
Online Reviews ◽  
Influential Factors ◽  
Business Analytics ◽  
Content Type ◽  
Factors Affecting ◽  
Starting Point ◽  
Guest Satisfaction ◽  
Significant Factors

Purpose Electronic word of mouth in the form of user-generated content (UGC) in social media plays an important role in influencing customer decision-making and enhancing service providers’ brand images, sales and service innovations. While few research studies have explored real content generated by hotel guests in social media, business analytics techniques are still not widely seen in the literature and how such techniques can be deployed to benefit hoteliers has not been fully explored. Thus, this study aims to explore the significant factors that affect hotel guest satisfaction via UGC and business analytics and also to showcase the use of business analytics tools for both the hospitality industry and the academic world. Design/methodology/approach This study uses big data and business analytics techniques. Big data and business analytics enable hoteliers to develop effective and efficient strategies improving products and services for guest satisfaction. Therefore, this study analyzes 200,431 hotel reviews on Tripadvisor.com through business analytics to explore and assess the significant factors affecting guest satisfaction. Findings The findings show that service, room and value evaluations are the top-three factors affecting overall guests’ satisfaction. While brand type and negative emotions are negatively associated with guests’ satisfaction, all other factors considered were positively associated with guests’ satisfaction. Originality/value The current study serves as a great starting point to further explore the relationship between specific evaluation factors and guests’ overall satisfaction by analyzing user-generated online reviews through business analytics so as to assist hoteliers to resolve performance-related problems by analyzing service gaps that exist in these influential factors.

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