Apparel 4.0: A Review of the Apparel Industry’s Adoption of Frontier Technologies

The Textile & Apparel (T&A) industry has been recognized for its modest shifts. This review paper, however, has examined the state of the apparel industry’s technology adoption, with special reference to 4IR technologies and fast-evolving market preferences in the post-pandemic era. Based on an extensive literature survey, the study concludes that the fourth industrial revolution (4IR) technologies have started gaining ground and disrupting the global apparel value chain. Likewise, Covid-19 too has brought considerable disruptions, driving organizational changes faster than ever. On one hand, Covid-19 has caused a significant adverse impact on the apparel industry, impacting brands, producers, and workers across the world. On the other hand, it has accelerated the adoption of frontier technologies by the industry. The Fourth Industrial Revolution (4IR) is transforming the apparel sector in design, development, production, supply chain, and marketing value segments. Besides process automation, frontier 4IR technologies such as 3D knitting and printing, robotics and intelligent manufacturing, virtual and augmented reality, artificial intelligence, business analytics, IoT, etc., have started shaping the future of the T&A industry. The paper should be of interest to both market actors (e.g., producers and marketers) and market facilitators (e.g., policymakers and academia). Keywords:Textile & Apparel (T&A) industry, Fourth Industrial Revolution (4IR), COVID-19, frontier technologies, fashion cycle, automation, biotechnology, apparel 4.0 DOI: 10.7176/EJBM/14-22-04 Publication date: November 30th 2022

Bridging Web 4.0 and Education 4.0 For Next Generation User Training in ERP Adoption

This study addresses the critical issue of user comprehension and application within the sphere of cloudbased Enterprise Resource Planning (ERP) systems, a recurrent challenge exacerbated by the intricate nature of these systems. To bridge the existing gaps in training methodologies, a novel paradigm that synergizes Web 4.0 and Education 4.0 modules with traditional ERP systems is proposed. This innovative framework ushers in a paradigm shift in ERP adoption strategies, promising a marked enhancement in user interaction and efficiency. Rigorous qualitative evaluations, conducted with expert panels and potential end-users, provided robust validation of the framework's transformative potential in the realm of user training for ERP systems. This pioneering approach not only makes a substantial academic contribution by reframing the perception of ERP systems but also holds a significant practical value in ameliorating the user experience with cloud-based ERP systems. In essence, the adoption of a Web 4.0-oriented approach in user training heralds a revolutionary shift in ERP adoption strategies, setting a solid foundation for future explorations in this domain

A Conceptual Design for Smell Based Augmented Reality: Case Study in Maintenance Diagnosis

The trend of Industry 4.0 encourages the next generation of manufacturing to be flexible, intelligent, and interoperable. The implementations of the Artificial Intelligence (AI) technology could potentially enhance maintenance in efficiency, and accuracy. However, it will not be a substitution to the human operator's flexibility, decision-making and information received by the natural five senses. Augmented reality (AR) is commonly understood as a technology that overlays virtual information onto the existing environment to provide users a new and improved experience to assist their daily activities. However, AR can be used to enhance all human five senses rather than just overlay virtual imagery. In this paper, a design and a practical plan of smell augmentation for diagnosis is initialised, via a case study in maintenance. The aim of this paper is to evaluate the feasibilities, identify challenges, and summarise initial results of overlaying information through smell augmentations

Natural User Interface for Education in Virtual Environments

Education and self-improvement are key features of human behavior. However, learning in the physical world is not always desirable or achievable. That is how simulators came to be. There are domains where purely virtual simulators can be created in contrast to physical ones. In this research we present a novel environment for learning, using a natural user interface. We, humans, are not designed to operate and manipulate objects via keyboard, mouse or a controller. The natural way of interaction and communication is achieved through our actuators (hands and feet) and our sensors (hearing, vision, touch, smell and taste). That is the reason why it makes more sense to use sensors that can track our skeletal movements, are able to estimate our pose, and interpret our gestures. After acquiring and processing the desired – natural input, a system can analyze and translate those gestures into movement signals

Technology enablers for the implementation of Industry 4.0 to traditional manufacturing sectors: A review

The traditional manufacturing sectors (footwear, textiles and clothing, furniture and toys, among others) are based on small and medium enterprises with limited capacity on investing in modern production technologies. Although these sectors rely heavily on product customization and short manufacturing cycles, they are still not able to take full advantage of the fourth industrial revolution. Industry 4.0 surfaced to address the current challenges of shorter product life-cycles, highly customized products and stiff global competition. The new manufacturing paradigm supports the development of modular factory structures within a computerized Internet of Things environment. With Industry 4.0, rigid planning and production processes can be revolutionized. However, the computerization of manufacturing has a high degree of complexity and its implementation tends to be expensive, which goes against the reality of SMEs that power the traditional sectors. This paper reviews the main scientific-technological advances that have been developed in recent years in traditional sectors with the aim of facilitating the transition to the new industry standard.This research was supported by the Spanish Research Agency (AEI) and the European Regional Development Fund (ERDF) under the project CloudDriver4Industry TIN2017-89266-R

Function-Based Mapping of Industrial Assistance Systems to User Groups in Production

Abstract By looking at the last few decades, industrial production has undergone great changes. Industry 4.0, also called the fourth industrial revolution, describes the change in the entire value chain through the digital networking of systems, machines, and products. In addition, product variety and complexity in assembly increased due to customization. Big Data Analytics, Internet of Things, Horizontal and Vertical Data Integration and Cyber-Physical Production Systems are just some examples of technologies that find their way from research into industrial practice. However, the most important resource is often neglected, when talking about industry: the human. When we look at companies, we find different types of personnel in production, each with different requirements and capabilities. Assistance systems can be used to counteract these new challenges and offer adequate support to each individual worker. In the past, much research has been done to develop new worker assistance systems, while the analysis of specific needs of user groups in production has been ignored. This paper presents a function-based mapping of industrial worker assistance systems to different user groups and proposes a method for selecting the most appropriate assistance system to each user group

Virtual reality substation training tool for industry workers

Performing specific tasks or operating hazardous machinery or materials requires a specialized skill set. Often this means training workers! Such task involves risks and many times the assignment of specialized personnel for teaching, what could mean delays and consequent money lost for the companies. This is where the Substation Training Tool comes in, a Virtual Reality system that with the use of two inertial sensors (hand control), will allow the control and handling of a multitude of objects, teaching new employees in a safer/controlled way for a scenario of maintenance in a substation. This research evidence that this new learning methodology works and motivates users to learn the proposed procedures. All the users felt that they had improved their skill set, a lot due to the possibility of trial/error and to the system which has short and easy to follow indications. Due to the used inertial sensors it was possible to collect data from each training session, providing more efficient final feedback for the users. The final prototype will allow EFACEC to train technicians, exploring multiple cases and avoiding all the mentioned problems that come with the traditional training methods.Executar tarefas especializadas, operar maquinaria ou materiais perigosos requer um conjunto especializado de conhecimentos. Frequentemente isto significa treinar operários! Adquirir este conhecimento envolve riscos e muitas vezes a alocação de pessoal especializado para ensinar, o que pode significar atrasos e consequentes perdas de dinheiro para as empresas. Aqui entra a ferramenta de treino em Substações, um sistema de realidade virtual que com o uso de dois sensores inerciais (controlo das mãos) permite o controlo e manuseamento dos mais diversificados objetos, ensinando assim novos funcionários de uma forma mais segura e controlada num cenário de manutenção numa sub-estação. O trabalho de investigação evidencia que esta nova técnica de ensino funciona e motiva os utilizadores a aprender os procedimentos propostos. Todos os utilizadores sentiram que melhoraram o seu conjunto de habilidades, muito pela possibilidade de tentativa/erro e pelo sistema que possui indicações curtas e fáceis de seguir. Graças à utilização dos dois sensores inerciais foi possível recolher informação de cada uma das sessões de treino, o que permite transmitir aos utilizadores no final informação mais precisa de todo o seu desempenho. A solução final (protótipo) irá permitir à EFACEC treinar técnicos, explorando múltiplos casos e evitando os já mencionados problemas que advêm do uso dos métodos tradicionais