Fashion Industry

Fashion is a lot more than providing an answer to primary needs. It is a way of communication, of distinction, of proclaiming a unique taste and expressing the belonging to a group. Sometimes to an exclusive group. Currently, the fashion industry is moving towards hyperspace, to a multidimensional world that is springing from the integration of smart textiles and wearable technologies. It is far beyond aesthetics. New properties of smart textiles let designers experiment with astonishing forms and expressions. There are also surprising contrasts and challenges: a new life for natural fibers, sustainable fabrics and dyeing techniques, rediscovered by eco-fashion, and "artificial apparel," made of wearable electronic components. How is this revolution affecting the strategies of the fashion industry

Customising with 3D printing: The role of intelligent control

© 2018 Elsevier B.V. The emergence of direct digital manufacturing creates new opportunities for the production of highly customised goods especially when it is combined with conventional manufacturing methods. Nevertheless, this combination creates a need for systems that can effectively manage and control the resulting distributed manufacturing process. In this paper, we explore three different configurations that can enable direct digital manufacturing for customisation, ranging from fully integrated to inter-organisational set up. Additionally, control requirements of such systems are developed and the suitability of intelligent control is explored. By ‘intelligent control’ we mean production control that is capable of assessing and interacting with the production environment and adapting production accordingly. We argue that the so called intelligent product paradigm provides a suitable mechanism for the development of such intelligent control systems. In this approach, the intelligent product directly co-ordinates with design agent, 3D printing agents and other conventional manufacturing system agents to schedule, assign and execute tasks independently. Via a case example of a realistic production system, we propose and implement such an intelligent control system and we analyse its feasibility in supporting 3D printing enabled customisation

Design choices for next-generation IIoT-connected MES/MOM:An empirical study on smart factories

The role of enterprise information systems is becoming increasingly crucial for improving customer responsiveness in the manufacturing industry. However, manufacturers engaged in mass customization are currently facing challenges related to implementing Industrial Internet of Things (IIoT) concepts of Industry 4.0 in order to increase responsiveness. In this article, we apply the findings from a two-year design science study to establish the role of manufacturing execution systems/manufacturing operations management (MES/MOM) in an IIoT-enabled brownfield manufacturing enterprise. We also present design recommendations for developing next-generation MES/MOM as a strong core to make factories smart and responsive. First, we analyze the architectural design challenges of MES/MOM in IIoT through a selective literature review. We then present an exploratory case study in which we implement our homegrown MES/MOM data model design based on ISA 95 in Aalborg University's Smart Production Lab, which is a reconfigurable cyber-physical production system. This was achieved through the use of a custom module for the open-source Odoo ERP platform (mainly version 14). Finally, we enrich our case study with three industrial design demonstrators and combine the findings with a quality function deployment (QFD) method to determine design requirements for next-generation IIoT-connected MES/MOM. The results from our QFD analysis indicate that interoperability is the most important characteristic when designing a responsive smart factory, with the highest relative importance of 31% of the eight characteristics we studied

Intelligent products: the grace experience

Product intelligence is a new industrial manufacturing control paradigm aligned with the context of cyber-physical systems and addressing the current requirements of flexibility, reconfigurability and responsiveness. This paradigm introduces benefits in terms of improvement of the entire product׳s life-cycle, and particularly the product quality and customization, aiming the customer satisfaction. This paper presents an implementation of a system of intelligent products, developed under the scope of the GRACE project, where an agent-based solution was deployed in a factory plant producing laundry washing machines. The achieved results show an increase of the production and energy efficiency, an increase of the product quality and customization, as well as a reduction of the scrap costs.info:eu-repo/semantics/publishedVersio

A Review of Supply Chain Data Mining Publications

The use of data mining in supply chains is growing, and covers almost all aspects of supply chain management. A framework of supply chain analytics is used to classify data mining publications reported in supply chain management academic literature. Scholarly articles were identified using SCOPUS and EBSCO Business search engines. Articles were classified by supply chain function. Additional papers reflecting technology, to include RFID use and text analysis were separately reviewed. The paper concludes with discussion of potential research issues and outlook for future development

Agent and cyber-physical system based self-organizing and self-adaptive intelligent shopfloor

The increasing demand of customized production results in huge challenges to the traditional manufacturing systems. In order to allocate resources timely according to the production requirements and to reduce disturbances, a framework for the future intelligent shopfloor is proposed in this paper. The framework consists of three primary models, namely the model of smart machine agent, the self-organizing model, and the self-adaptive model. A cyber-physical system for manufacturing shopfloor based on the multiagent technology is developed to realize the above-mentioned function models. Gray relational analysis and the hierarchy conflict resolution methods were applied to achieve the self-organizing and self-adaptive capabilities, thereby improving the reconfigurability and responsiveness of the shopfloor. A prototype system is developed, which has the adequate flexibility and robustness to configure resources and to deal with disturbances effectively. This research provides a feasible method for designing an autonomous factory with exception-handling capabilities

Impacts of the implementation of Industry´s 4.0 technologies in the portuguese footwear industry

The first three industrial revolutions came about as a result of mechanization, electricity and IT. It is safe to state that a fourth revolution is currently taking place in manufacturing, with it being generally branded as Industry 4.0. These Cyber-Physical Systems comprise smart machines, storage systems and production facilities capable of autonomously exchanging information, triggering actions and controlling each other independently. The present investigation takes this premise into account and focuses in pursuing what are the main implications of the implementation of Industry´s 4.0 technologies in the Portuguese Footwear Industry. In order to lay the foundations for the study, an extensive literature review was executed. This was followed by a qualitative and exploratory investigation, based on twelve interviews with various relevant actors of the Portuguese footwear scene. The interviews resulted in insightful conclusions. Firstly, it is possible to notice that the Portuguese Footwear industry is generally well equipped and informed. Generally, the manufacturers are aware of the new technologies that are made available, being that there are already successful examples of companies using them. The study has highlighted the importance for companies to develop an extensive evaluation regarding their specific needs in order to better decide in which technologies to invest. The path is being designed in order to continuously simplify technologies, so that they are easier to work with. The main constraint, to the present day, is linked with finding skilled workforce to perform tasks at the shop floor level and also with the generation of enough value that allows the manufacturers to invest in more advanced technology

Rapid manufacturing as a tool for agile manufacturing: applications and implementation perspectives

Manufacturing engineers and technologists around the globe are already well familiar with manufacturing methodologies and systems developments in the last part of the twentieth century. Many are probably also familiar with the current state of Rapid Prototyping (RP) technologies, especially in the areas of concept model making and prototype development. They may not however, be so familiar with the more recent developments of these technologies towards Rapid Manufacturing (RM) and the directions which the applications of RM technologies are taking for agile manufacturing purposes in particular. This paper critically reviews the various technologies currently available, outlines development trends in RM, discusses the approach, application and implementation perspectives by which these RM technologies are applied for increasing agility and responsiveness in manufacturing. Furthermore, the paper describes two case study examples to further illustrate the application scenarios in agile manufacturing before concluding remarks

Literature review on the ‘Smart Factory’ concept using bibliometric tools

The objective of this paper is to depict a landscape of the scientific literature on the concept of the ‘Smart Factory’, which in recent years is gaining more and more attention from academics and practitioners because of significant innovations in the production systems within the manufacturing sector. To achieve this objective, a dynamic methodology called "Systematic Literature Network Analysis (SLNA)" has been applied. This methodology combines the Systematic Literature Review approach with the analysis of bibliographic networks. The adopted methodology allows complementing traditional content-based literature reviews by extracting quantitative information from bibliographic networks to detect emerging topics, and by revealing the dynamic evolution of the scientific production of a discipline. This dynamic analysis allowed highlighting research directions and critical areas for the development of the "Smart Factory". At the same time, it offers insights on the fields on which companies, associations, politicians and technology providers need to focus in order to allow a real transition towards the implementation of large-scale Smart Factory