Consumer Electronics Industry Research Articles

Imperialist competitive algorithm for unrelated parallel machine scheduling with sequence-and-machine-dependent setups and compatibility and workload constraints

In this paper, we present an in-depth analysis of the unrelated parallel machine scheduling problem (UPMSP) in the context of washing machine production at Vestel Electronics. Vestel Electronics is a leading producer of washing machines and holds a noteworthy market position in the European consumer electronics industry. The production process at Vestel Electronics is make-to-order (MTO) and requires 20 assembly lines to produce 200 different products. The decision maker must consider several important factors while forming the production schedule, including job-assembly line compatibility, the release times and due dates of the jobs, and a workload balance among the different assembly lines. This study aims to develop an algorithm to minimize the total earliness and tardiness while considering sequence-and-machine-dependent setups, unequal release times, machine-job compatibility restrictions, and workload balance requirements. To address this complex scheduling problem, we propose a novel algorithm, the imperialist competitive algorithm (ICA), which has a strong exploration–exploitation balance while mimicking real-world dynamics. Our numerical results show that the ICA significantly outperforms the current practice in Vestel by 39% and the best-performing algorithms in the literature by 23% and 12%.

Enhancing sustainability in mass customisation of consumer electronics with salvage value through supply chain financing

ABSTRACT The consumer electronics industry is crucial in the global shift toward sustainability. To meet customers’ personalised needs efficiently and reduce production costs, electronic product suppliers increasingly focus on Mass Customization (MC) and modular production. Implementing a buyback policy for unsold module products with salvage value is a sustainable practice that reduces waste. This study explores two buyback support financing tools to enhance sustainability in the industry, enabling successful MC production. We also investigate how the salvage value based on modularity level and the buyback policy impact operational and financing decisions in the Mass Customization Supply Chain (MCSC). The research reveals that a higher modularity level positively impacts supplier’s profits and optimal capacity levels under both financing strategies. Consequently, this study offers valuable insights into elevating sustainability practices and optimising operational and financing decisions in the context of MC within the consumer electronics industry.

Energy-Efficient UAV Scheduling and Probabilistic Task Offloading for Digital Twin-Empowered Consumer Electronics Industry

Energy-Efficient UAV Scheduling and Probabilistic Task Offloading for Digital Twin-Empowered Consumer Electronics Industry

Wavelength-scanning pixel-super-resolved lens-free on-chip quantitative phase microscopy with a color image sensor

We report a wavelength-scanning-based lens-free on-chip microscope using a color CMOS sensor and a matching modified phase retrieval algorithm for pixel super-resolution. Compared to traditional monochrome industrial cameras, color sensors favored by the consumer electronics industry have smaller pixel sizes, higher performance, and lower costs. However, the color filtering array (CFA) introduces inherent modulation to the holograms acquired under quasi-monochromatic illumination, which complicates the data processing in lens-free on-chip microscopy. Without physically removing the CFA positioned on the sensor chip, we demonstrate quantitative phase imaging (QPI) with a lateral half-width resolution of 615 nm over a wide field-of-view of 51.88 mm2 by exploiting the green-channel data from Bayer-masked holograms. The resulting spatial bandwidth product is 137.2 megapixels, over 10 times that of a conventional optical microscope. The rationale for using only green-channel data is that the information from each sampling point is not lost during propagation but rather distributed to all pixels in the image. Therefore, the missing data in other channels can be recovered by exploiting the sufficient differences among the raw images captured at different wavelengths. Compared to the scheme with monochrome sensors, this method requires the acquisition of several more images to guarantee the convergence of the algorithm. Experimental results show that we can achieve high-quality QPI performance, thus demonstrating the applicability of cost-effective color sensors in the field of lens-free holographic microscopy.

A Comparative Research on Competitiveness of Consumer Electronics Industry in China and the United States

In the era of technology dominance, the consumer electronics industry serves as a testament of global economic strength, particularly the US and China. This paper thoroughly analyzes consumer electronics sectors' competitiveness in China and United States. The study provides an overview on the industry, comparing the similarities and differences in China and the US consumer electronics markets. This research uses SWOT analysis to identify the strengths, weaknesses, opportunities, and threats of case companies Huawei and Apple with their respective nations. The research compares quantitative data with qualitative SWOT analysis insights. Furthermore, the TOWS matrix is also employed as analysis strategies and recommends ways to boost China's industry competitiveness. This study compares the Chinese and American consumer electronics industries, highlighting China's R&D needs and future challenges and opportunities, particularly in emerging technologies and consumer trust. This study provides insights on the consumer electronics industry's dynamics, advising industry players and policymakers on strategy optimization and highlighting potential pathways for China's ascension in the global arena.

The Thermal Conductivity of Near-Eutectic Galinstan (Ga68.4In21.5Sn10) Molten Alloy

The need for new heat transfer agent for many applications, namely in the consumer electronics industry, requires materials, liquids at room temperature, with high thermal conductivity. From the different possibilities, Galinstan, a eutectic alloy of Gallium, Indium, and Tin with a melting point (Tm = 283.4 K) has been proposed for many applications, namely for replacing the toxic mercury element, used for many years. It is the purpose of this paper to report thermal conductivity measurements of Galinstan, product name Gallium/Indium/Tin Eutectic (NL-011), Ga68.4In21.5Sn10. The method used was the transient hot strip (THS), using a platinum metal-film sensor, produced by PVD in ceramic substrates, and electrically insulated with a heat-shrinkable coating. The details of the data acquisition system and measuring procedure are reported. Measurements were performed between 28 °C and 103 °C (301 K to 376 K), at atmospheric pressure, with an estimated uncertainty of 6%, and compared with available literature. Data were correlated for linear interpolation. This type of sensor is applied to molten metals for the first time, proofing to concept to future applications in molten metals and molten salts at higher temperatures.Graphical

Cauchy DMP: Improving 3C industrial assembly quality with the Cauchy kernel and singular value decomposition

AbstractAlthough Dynamic Movement Primitives (DMP) is an effective tool for robotic arm trajectory generalisation, the application of DMP in the 3C (Computer, Communication, Consumer Electronics) industry still faces challenges such as low precision and high‐time consumption. To address this problem, we propose a novel Cauchy DMP framework. The main improvements and advantages of Cauchy DMP, compared to the original DMP, are (1) since the Cauchy distribution has a simpler model and wider shape, using the Cauchy distribution instead of the Gaussian distribution in the original DMP reduces the complexity of the algorithm and saves time. (2) Singular Value Decomposition (SVD) can effectively model the error. To reduce the interference of the rounding and human error on the trajectory, SVD can be used to obtain the weight of each basis function. The proposed Cauchy DMP framework combines the above two points and is validated on a real UR5 robotic arm. The results show that Cauchy DMP retains the learnability of the original DMP and has the advantages of short time consumption and low error rate.

Numerical prediction of glass molding process for 3D curved screen

With the rapid development of consumer electronics industry, the demand for 3D curved screen in industry is also growing. At present, 3D curved screen is mass produced through glass molding process. However, due to the complex rheological properties of glass melt and the intricate deformation mechanism of glass molding process, the final geometry of the screen is difficult to predict. In this paper, the glass molding process for 3D curved screen is analyzed by finite element transient analysis. The trend of screen shape change is obtained and the final geometry of the screen is predicted. The results show that geometric fillet and rheological parameters have great influence on the flow of glass melt in glass molding process. This study is helpful for the selection of parameters of glass molding process and the design of 3D curved screen.

Inverse kinematics and singularity analysis of a redundant parallel robot

The 3C (computer, communications, consumer electronics) industry belongs to labor-intensive and the requirements of the 3C industry are precisely high. The parallel robot is a good choice to replace human labor to manufacture these products. This paper presents a new 3- redundant parallel mechanism for 3C manufacturing. Firstly, some advantages of redundant parallel robots in the current industrial demand are discussed. Then, the inverse kinematics of the redundant parallel manipulator is analyzed according to the closed-loop equation, the inverse displacement problem is solved. The machine is simple and low cost, and as a less freedom robot, it has a higher precision than the traditional robot and has a broad prospect for 3C manufacturing. Finally, the Jacobian matrix of the redundant parallel manipulator was calculated and established by the inverse kinematics formula, and three kinds of the singularity of the mechanism were analyzed by the Jacobian matrix, which are the forward singularity, reverse singularity, mixed singularity respectively.

Sentiment and Emotion on Twitter: The Case of the Global Consumer Electronics Industry

Sentiment analysis is a new tool on new social media platforms, locations very attractive to the global consumer industry to investigate, due to their relevance and increased consumption in a pandemic. This study aims to determine the predominant sentiment and emotions on Twitter through a sentiment analysis in the consumer electronics industry, according to the top 30 companies of the Consumer Electronic Show 2020, by analyzing 96,000 tweets with a total of 273,221 words. The methodology used is quantitative, of a descriptive type, that integrates the study of emotions and sentiment through a statistical analysis of the tweets with R. The main results identify that the predominant sentiment is of positive assessment and the emotions of anticipation and confidence were the most representative. The contribution of this research is to provide empirical evidence of the global consumer electronics industry for correct decision-making through a data language analysis procedure on Twitter.

Optically Transparent Antenna for Smart Glasses

The optically transparent antenna technology has been gaining attention in consumer electronic industry owing to its potential to release the antenna volume constraints in compact mobile devices. Earlier studies have been heavily focused on the transparent antenna integration to the display for smartphone applications, for example, to improve its spatial coverage of 5G mm-wave at the forehead side. To our knowledge, the application of the transparent antenna technology to smart glasses and augmented reality glasses, especially considering the constraints from the coexistence with optical features in the lens stack-up, has remained unexplored. Thus, for the first time, we suggest a feasible existence solution between antennas and the RF lossy layers in the lens stack-up, to reduce the negative impacts on antenna performances. A slot loop antenna formed by metal-mesh based transparent antenna film and metallic glass frame has been investigated. Experimental results of such an antenna on human head phantom shows a total efficiency better than −4.5 dB in 2.4 GHz band. Even though it is demonstrated through a 2.4 GHz antenna example, the same principle can be applied to any other sub-6 GHz antenna applications, i.e., LTE, WiFi, GNSS, etc.

Joyce Weisbecker: The first indie game developer

Joyce Weisbecker was always interested in her father Joseph’s work. What child wouldn’t be? Joseph was the inventor of the Think-a-Dot and other games, a writer, and a magician who loved learning and teaching. But that’s not all. Joseph was also the engineer who led RCA into a new technological era with his 8-bit microprocessor architecture. Throughout the 1970s, he prototyped and developed a number of programmable video games, educational systems, and game consoles, all showcasing what a game changer the microprocessor was going to be to a nascent consumer electronics industry. These included the hobbyist’s build-it-yourself COSMAC Elf articles and the Studio II programmable video game console. Weisbecker followed along with her father’s inventions, spending time with him in his at-home workshop, and in the summer of 1976, before her freshman year in college, she sold her car race game <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Speedway</i> to RCA for its Studio II, making her the first indie game developer.

Pre- and post-COVID-19: The impact of the pandemic and stock market psychology on the growth and sustainability of consumer goods industries.

The objective of this study is to investigate the impact of the COVID-19 pandemic and stock market psychology on investor investment decisions in different business units operating in the Shandong stock market. The sample size of the study consists of 5,000 individuals from six different business units. The study used the event study statistical technique to analyze the market reaction to newly released information from the stock market perspective to assess whether the number of COVID-19 positive cases impacted it. With a Z score value of 40.345 and a P-value of 0.000, the Wilcoxon test indicated that stock prices before and after the pandemic were quite different. The test showed a positive relationship between the pandemic and the stock market. Further, the results indicated that COVID-19 and stock market psychology had a significant positive impact on investor investment decisions in cosmetic and beauty, consumer household, textiles and apparel, and consumer electronics industries; however, in the sporting and consumer appliance industries, it had an insignificant negative impact. This study serves to guide investors to make suitable changes in their stock market trading practices to counter these challenges to increase their required rate of return from their specific stock market investment. The findings have important insights for various stakeholders including governments, regulatory bodies, practitioners, academia, industry, and researchers.

Achieving sustainable industrial ecosystems by design: A study of the ICT and electronics industry in Taiwan

The environmental and economic aspects of sustainability have been the most common subjects in the manufacturing industry, while the social one tends to be neglected. The process of semistructured interviews is conducted with design practitioners in the computer, communication, and consumer electronics industry in Taiwan to comprehend how the participating companies can move from a business-as-usual model to a more sustainable business by design. Results show that ecodesign and design for circular economy are commonly applied as sustainable design strategies, highlighting the concept of dematerialization. The three pragmatic tools applied alongside for balancing the three pillars of sustainability are life cycle thinking, design thinking, and business model tools. To achieve sustainable industrial ecosystems, three key actors, namely, a driver, a facilitator, and a supporter, play an important role to create stakeholder engagement and supply chain collaboration. Hence, the companies must tackle major challenges related to organizational culture, social reputation and communication, resource availability, service at the end of life, and effective waste treatment. Relying solely on product level for sustainability is insufficient; the companies need to tap into socio-technical systems by creating new partnerships, supporting multidisciplinary teams, embracing new markets, integrating emerging technologies for social sustainability, and promoting innovative and social inclusive thinking.

Consumers’ Awareness Towards Sustainable Marketing Practices: A Study in Consumer Electronics Industry

Sustainability is presumed as a key concept in today’s scenario and more and more companies are jumping on this bandwagon to be successful. The present study is an attempt to understand the extent of awareness amongst consumers’ towards sustainable marketing practices adopted by the companies in consumer electronics sector. Another purpose of this paper is to analyze if there exist any difference in the awareness of consumers based on the demographics like gender and age. The study was conducted by collecting data from 204 consumers of electronic products like laptop, mobile phone, etc. Convenient sampling technique was chosen to select the respondents for the study. A structured questionnaire has been used to collect primary data from respondents in the last quarter of 2021. Descriptive statistics and inferential statistics are used for analyzing the data. The results show that there is fair level of awareness amongst consumers of the term sustainable marketing, its products, and practices.

Engagement on Twitter, a Closer Look from the Consumer Electronics Industry

Engagement represents the commitment and bond between a brand and its customers, and achieving high levels of engagement is now a competitive advantage for companies. Determining the engagement index was a high-cost activity for organizations and consumers in the past decade due to the time and cost of data collection. The massive use of social networks such as Twitter allows organizations and consumers to collect data without large costs, and determining the engagement rate is more feasible today. This research determines the effect of different interactions on Twitter on engagement in the consumer electronics industry. The methodology used is a mixed qualitative and quantitative, descriptive approach by analyzing (by regressions) 95,000 tweets from the 30 companies at the Consumer Electronics Show 2020. The main results show that Twitter mentions represent a relevant factor in determining engagement. The contribution of this research lies in the generation of empirical evidence on engagement in the consumer electronics industry and the identification of the key variable of mentions and their effects on Twitter.

The Effects of Social Media Tools Towards Online Retail Businesses in the Consumer Electronics Industry

Businesses nowadays have been adapting to technological advancements since the 21st century to promote their products. The majo]rity of the global population has been exposed to the digital world, and retail businesses have engaged themselves in the online environment. Social media tools have become a significant factor in advertising products and have taken big steps to create innovations in their platforms. Using social media has given online businesses options on managing their performance towards their brand and how to interact with consumers. These digital enhancements toward flourishing online retail businesses have boosted the consumer electronics industry. The study's objective was to provide extensive knowledge of how the different social media platforms and tools significantly affected the performance of online retail businesses belonging to the consumer electronics industry. A quantitative research approach was utilized in this study. The researchers conducted online survey questionnaires and were distributed to 185 respondents. Lastly, the study aims to benefit retail businesses, consumers, and future researchers, who engage in online businesses and how they can stand out from prospective competitors.

The Effects of Social Media Tools on Online Retail Businesses in the Consumer Electronics Industry

Abstract Businesses nowadays have been adapting to technological advancements since the start of the 21st century to promote their products. The majority of the global population has been exposed to the digital world, and businesses have engaged themselves in the online environment. Social media tools have become a vital component in advertising products and have contributed significantly to creating countless innovations. Using social media has given online businesses options for managing their performance towards their brand and interacting with consumers through social media platforms. These digital improvements have benefited the consumer electronics industry. The goal of the study was to gain a thorough understanding of how social media platforms and tools impact the performance of online retail businesses in the consumer electronics industry. The study used the quantitative approach, and online survey questionnaires were distributed to 185 respondents. Results revealed that perceived ease of use, social media advertising, and electronic word-of-mouth (eWOM) all have a positive effect on the performance of online retail businesses in the consumer electronics industry. The implications of this research aim to benefit aspiring online business owners, consumers, and future researchers, and help them maximize social media to make them stand out from prospective competitors. Keywords: customer engagement, digital advertising, online marketing, retail businesses, social media

The Effects of Social Media Tools on Online Retail Businesses in the Consumer Electronics Industry

Businesses nowadays have been adapting to technological advancements since the start of the 21st century to promote their products. The majority of the global population has been exposed to the digital world, and businesses have engaged themselves in the online environment. Social media tools have become a vital component in advertising products and have contributed significantly to creating countless innovations. Using social media has given online businesses options for managing their performance towards their brand and interacting with consumers through social media platforms. These digital improvements have benefited the consumer electronics industry. The goal of the study was to gain a thorough understanding of how social media platforms and tools impact the performance of online retail businesses in the consumer electronics industry. The study used the quantitative approach, and online survey questionnaires were distributed to 185 respondents. Results revealed that perceived ease of use, social media advertising, and electronic word-of-mouth (eWOM) all have a positive effect on the performance of online retail businesses in the consumer electronics industry. The implications of this research aim to benefit aspiring online business owners, consumers, and future researchers, and help them maximize social media to make them stand out from prospective competitors. Keywords: customer engagement, digital advertising, online marketing, retail businesses, social media

A Machine Learning Generative Method for Automating Antenna Design and Optimization

To facilitate the antenna design with the aid of computer, one of the practices in consumer electronic industry is to model and optimize antenna performances with a simplified antenna geometric scheme. The ease of handling multi-dimensional optimization problems and the less dependence on the engineers' knowledge and experience are the key to achieve the popularity of simulation-driven antenna design and optimization for the industry. In this paper, we introduce a flexible geometric scheme with the concept of mesh network that can form any arbitrary shape by connecting different nodes. For such problems with high dimensional parameters, we propose a machine learning based generative method to assist the searching of optimal solutions. It consists of discriminators and generators. The discriminators are used to predict the performance of geometric models, and the generators to create new candidates that will pass the discriminators. Moreover, an evolutionary criterion approach is proposed for further improving the efficiency of our method. Finally, not only optimal solutions can be found, but also the well trained generators can be used to automate future antenna design and optimization. For a dual resonance antenna design, our proposed method is better than the other mature algorithms.