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The study primarily aims to examine an emerging fashion technology, direct-to-garment (DTG) printing, using data mining-driven social network analysis (SNA). Simultaneously, the study also demonstrates application of a group novel computational technique to capture, analyze and visually depict data for strategic insight into the fashion industry.

A total of 5,060 tweets related to DTG were captured using Crimson Hexagon. Python and Gephi were applied to convert, calculate and visualize the yearly networks for 2016–2019. Based on graph theory, degree centrality and betweenness centrality indices guide interpretation of the outcome networks.

The findings reveal insights into DTG printing technology networks through identification of interrelated indicators (i.e. nodes, edges and communities) over time. Deeper interpretation of the dominant indicators and the unique changes within each of the DTG communities were investigated and discussed.

Three SNA models suggest directions including the dominant apparel categories for DTG application, competing alternatives for apparel decorating approaches to DTG and growing market niches for DTG. Interpretation of the yearly networks suggests evolution of this domain over the investigation period.

The social media based, data mining-driven SNA method provides a novel path and a powerful technique for scholars and practitioners to investigate information among complex, abstract or novel topics such as DTG. Context specific findings provide initial insight into the evolving competitive structures driving DTG in the fashion market.

This paper aims to discuss how acrylic resin influences the smoke generation of intumescent flame retardant coatings.

Thermal decomposition kinetics is used in this study to simulate the burning process. The thermal decomposition of acrylic resin can be identified in the intumescent coatings through the multi-peak fitting of derivative thermogravimetric (DTG) curves. The dormant influence of acrylic resin, combined with the smoke density, is calculated.

Multiple peaks fitting method of DTG curves helps estimate the decomposition process of acrylic resin in flame retardant coating. Combining DTG data with the smoking curve, smoking generation of acrylic resin during the combustion could be evaluated. The decomposition conversion rate of acrylic resin is 21.13 per cent. Acrylic resin generates 34.64 per cent of the total amount of smoke produced during the combustion of intumescent flame retardant coatings.

All the other intumescent flame retardant coating systems could be studied using the same approach as that used in this work to achieve an improved understanding of the smoke generation process during combustion.

The method developed here provided a simple and practical solution to analyse the decomposition and smoking generation of acrylic resin in the coating mixtures. It also can be used to analyse any thermal decomposition process of any mixed compounds.

The analysis method to evaluate resin’s smoking generation of coating’s total generation is novel, and it could be applied in all kinds of coatings and mixtures to estimate the smoking generation of one composition.

The behavior of tourists strongly depends on the availability and quality of information. Too little information as well as too much can be disorienting and forces many tourists to join the majority visiting major sights. This causes a few crowded places in contrast to many which are under‐utilized. A Destination Management Organization has the goal to spread tourists more evenly, whereas the tourists would like to enjoy the destination to its full potential according to their personal interests. The paper aims to focus on the issues surrounding the creation of a mobile tourist guide.

A field trial was conducted in the summer of 2005 to study the following questions as a precondition for the development: Is it possible to seed generic interest profiles in the mobile context that allow the accurate prediction of actual rankings? Are the interest profiles sufficiently diverse to base personalized tours on individual interest profiles instead of interest prototypes? How do personalized tours affect the spatial behavior of tourist? Three methods to elicit the generic preferences of tourist in the mobile context are compared with actual rankings using Spearman's rank order coefficient.

The diversity of the interest profiles is analyzed in various ways leading to the conclusion that personalized interest profiles are necessary. For the gathered profiles tours are computed and simulated in order to gain a first insight into the effect on the spatial behavior of tourists.

The dynamic tour guide is supporting both goals by means of pervasive computing based on the actual context which is defined by personal interests, location and schedule of a tourist. It enables a personalized, spontaneous and guided tour.

Mechanical properties are highly sensitive to the microstructure, and these are indirectly related to solidification parameters and processing conditions. AA7075 possesses lightweight and excellent properties as structural material which can be optimized with SiCp addition and a good fabrication technique.

7000 series aluminium alloys exhibit the highest mechanical properties. They are used for high-strength structural applications such as aircraft parts and sporting goods. The desirable properties of these alloys are: low density, high stiffness, specific strength, good wear resistance and creep resistance. The focus of this work is to investigate the microstructure of composites formed by the dispersion of silicon carbide particles (SiC) into AA7075 by stir casting processes. 7075 Al alloy is reinforced with 10 and 15 wt.% SiCp of size 10–20 µm by stir casting process. The composites have been characterized by X-ray diffraction and scanning electron microscopy, differential thermal analysis and electron probe microscopic analysis.

SiCp distribution and interaction with AA7075 matrix have been studied. AA7075/10 wt.%/SiCp (10–20 µm) and AA7075/15 wt.%/SiCp (10–20 µm) composites microstructure showed excellent SiCp distribution into AA7075 matrix. In addition, no evidence of secondary chemical reactions has been observed in X-ray diffraction and electron probe microscopic analysis.

Little experimental work has been reported so far about effect of addition of 10 and 15 wt.% SiCp of size (10–20 µm) on the microstructure of 7075 Al alloy fabricated by stir casting process. The present investigation has been carried out to study the microstructure and carry out XRD, DTA and EPMA analysis of 7075 Al alloy, 10 and 15 wt.% SiCp of size (10–20 µm) composite and detect the interfacial reactions with the objective to minimize the formation of Al4C3.

The purpose of this paper is to evaluate the fire resistance of an innovative carbon-reinforced PEKK composite for aeronautical applications. To this end, thermal degradation analysis under inert and oxidative atmosphere is carried out. Moreover, a linear model fitting approach is compared to a generally used isoconversional method to validate its reliability for kinetic triplet estimation.

Thermogravimetric analysis carried out under inert and oxidative atmospheres, between 25 and 1000°C for three different heating rates (5, 15, 25°C/min), followed by a qualitative SEM observation of the samples before and after thermal treatment. After the reaction identification by TG/DTG curves, an isoconversional analysis is carried out to estimate the activation energy as a function of the reaction conversion rate. For the identified reactions, the kinetic triplet is estimated by different methods and the results are compared to evaluate their reliability.

In inert case, one global reaction, observed between 500-700°C, seems able to describe the degradation of carbon-PEKK resin. Under oxidative atmosphere, three main reactions are identified, besides the resin degradation, the other two are attributed to char and fiber oxidation. Good agreement achieved between isoconversional and linear model fitting methods in activation energy calculation. The achieved results demonstrate the high thermal resistance of PEKK associated with the ether and ketone bonds between the three aromatic groups of its monomer.

This paper provides a possible degradation model useful for numerical implementation in CFD calculations for aircraft components design, when exposed to high temperatures and fire conditions.

The purpose of this paper is to evaluate local biodegradable oils with long chain fatty acids namely: castor (Ricinus communis L.), jojoba (Simmondsia chinensis L.), olive (Oleo europaea L.), and sunflower (Helianthus annuus L.) oils for lubrication candidacy as a substitute to petroleum mineral oils.

Evaluation criteria includes antiwear, lubricity, and extreme pressure (load carrying capacity) using the four‐ball configuration, oxidation induction by pressure differential scanning calorimetry, thermal stability by thermo‐gravimetric analyses, and viscometry using relevant American Society of Testing and Materials (ASTM) standards.

The results show that the lubrication films at the interface failed by the decomposition of the metallic soaps formed by the chemical reaction of the constituent fatty acid molecules and the rubbing surfaces. The biodegradable oils show superior lubricant performance compared to the paraffin‐based mineral oil, despite their poor oxidation stability. Oxidation induction and thermo‐gravimetric characteristics of the biodegradable oils are closely related to their polyunsaturated and monounsaturated fatty acid composition.

The paper shows how these biodegradable oils could be used as good substitute for petroleum mineral oils in as‐received state or little antioxidant additives.

This paper aims to provide a framework for the choice, design, set-up and management of a fully flexible assembly system (F-FAS). Many industrial applications for small batch productions require highly flexible automated manufacturing systems. Moreover, some extensions of the F-FAS concept are provided.

The paper reviews recent findings regarding the F-FAS with a top-down approach, and defines an integrated implementation framework. This framework is structured into three strictly correlated phases, and the presented procedure is organized to be readily used for new industrial applications. Practical applications are presented to show how the system can satisfy flexibility demands in a variety of cases.

The proposed framework is organized in three steps: convenience analysis of the F-FAS compared to a traditional flexible assembly system; an optimal design of the feeder; a choice of the set-up and sequencing algorithm yielding the highest throughput. Following these steps, the F-FAS can become an effective solution for small batch productions with frequent reconfigurations. However, due to the limited throughput, the system is not well suited for large batches.

The presented framework allows to implement an F-FAS for a given industrial application, and to evaluate its efficacy with respect to other assembly technologies. Moreover, with the same implementation framework, the F-FAS concept can be applied to production fields that are different from assembly, as shown by the provided examples. This represents an important element of originality and of interest for its strong practical implications in different production environments.

The purpose of this paper is to extend a routing model so that it may be applied to a real case study of material deliveries involved in a development operation, typical of regular humanitarian logistics, and to explore the impact of variations in available logistic assets.

The introduced model is a conceptual evolution of the study recently presented. It concerns the resource allocation and vehicle routing decisions in the well-known Haitian case. Different scenarios are analyzed and a sensitivity analysis is provided. Constraints related to transportation resources in a complex environment, transportation vehicle capacities, and delivery time restrictions are here considered.

This research shows how the logistic assets characteristics and their availability affect the distribution system performances, in terms of total distribution cost and shortages.

The present work explores the last mile distribution problem by providing a case study to assist decision makers in making effective and efficient distribution across the last mile. The research focusses upon the distribution systems management coupled with material distribution modalities.

The paper aims to address the modelling and optimization of fully flexible assembly systems (F‐FAS), a new concept in flexible automation recently introduced by the authors.

The paper presents a mathematical model of the F‐FAS, which makes it possible to predict its efficiency, throughput and unit direct production costs, correlating such values with system and production variables. The mathematical model proposed in the paper was derived from experimental and simulation data, which were analysed for a wide range of different productions and system settings.

Correlation analysis revealed that there are three main determinants of the efficiency of the F‐FAS: the number of components (types of parts) used to assemble the models (production variable); the average complexity of the models to be assembled (production variable); the ratio of the average perimeter of components (production variable) over a significant dimension of the working plane (system variable). Such parameters makes it possible to estimate the maximum attainable efficiency of the F‐FAS, and to calculate the optimal setting of the feeder which makes it possible to obtain such efficiency during the execution of the whole production order.

The model presented in the paper makes it possible to quantify in advance the real potential of the F‐FAS, according to the characteristics of the production mix and type of components to be assembled. By using the methodologies presented in the paper, one can first evaluate the convenience of the F‐FAS approach with respect to traditional FAS technology and manual assembly, then identify the optimal design and settings of the F‐FAS, according to the needs of a specific application. As a result, not only can the investment on the automated assembly system be accurately evaluated in advance, but also the return on investment can be maximized.

Enterprise social media (ESM) platforms are rapidly diffusing in the business context because they can bring substantial benefits to companies by enhancing their knowledge management (KM) processes. However, such benefits materialize only if active employee participation is ensured. Therefore, it is crucial to understand how individual employees use an ESM platform to assist their knowledge-related activities. This paper contributes to this topic by proposing a classification of ESM users based on two dimensions: frequency and type (active or passive) of use.

The paper presents the results of a survey of 262 employees of an international engineering service company that has adopted an ESM platform to support its KM processes. Statistical methods (e.g. ANOVA, Tukey’s b) were applied to verify the usefulness of the proposed typology and identify the main aspects that characterize the different user groups.

The survey results confirm the existence of different types of ESM users and provide the empirical basis for developing a bi-dimensional classification from which four user groups were derived and characterized: frequent contributors, sporadic contributors, frequent lurkers and sporadic lurkers.

The main limitation is that only one company in one sector with specific knowledge needs and capabilities was investigated.

The study provides useful suggestions for how to promote the use of an ESM and particularly for how to encourage less frequent and less active users to increase their participation in a platform.

The paper contributes to a better understanding of how employees approach ESM by identifying factors that characterize different user groups.