Attribute Identification and Predictive Customisation Using Fuzzy Clustering and Genetic Search for Industry 4.0 Environments

Today´s factory involves more services and customisation. A paradigm shift is towards “Industry 4.0” (i4) aiming at realising mass customisation at a mass production cost. However, there is a lack of tools for customer informatics. This paper addresses this issue and develops a predictive analytics framework integrating big data analysis and business informatics, using Computational Intelligence (CI). In particular, a fuzzy c-means is used for pattern recognition, as well as managing relevant big data for feeding potential customer needs and wants for improved productivity at the design stage for customised mass production. The selection of patterns from big data is performed using a genetic algorithm with fuzzy c-means, which helps with clustering and selection of optimal attributes. The case study shows that fuzzy c-means are able to assign new clusters with growing knowledge of customer needs and wants. The dataset has three types of entities: specification of various characteristics, assigned insurance risk rating, and normalised losses in use compared with other cars. The fuzzy c-means tool offers a number of features suitable for smart designs for an i4 environment

Comparative study of design: application to Engineering Design

A recent exploratory study examines design processes across domains and compares them. This is achieved through a series of interdisciplinary, participative workshops. A systematic framework is used to collect data from expert witnesses who are practising designers across domains from engineering through architecture to product design and fashion, including film production, pharmaceutical drugs, food, packaging, graphics and multimedia and software. Similarities and differences across domains are described which indicate the types of comparative analysis we have been able to do from our data. The paper goes further and speculates on possible lessons for selected areas of engineering design which can be drawn from comparison with processes in other domains. As such this comparative design study offers the potential for improving engineering design processes. More generally it is a first step in creating a discipline of comparative design which aims to provide a new rich picture of design processes

Layered Fabrication of Branched Networks Using Lindenmayer Systems

A current challenge impeding the growth of bone tissue engineering is the lack of functional scaffolds of geometric sizes greater than 10mm due to the inability of cells to survive deep within the scaffold. It is hypothesized that these scaffolds must have an inbuilt nutrient distribution network to sustain the uniform growth of cells. In this paper, we seek to enhance the design and layered fabrication of scaffold internal architecture through the development of Lindenmayer systems, a graphical language based theory to create nutrient delivery networks. The scaffolds are fabricated using the Texas Instruments DLP™ system through UV‐photopolymerization to produce polyethylene glycol hydrogels with internal branch structures. The paper will discuss the Lindenmayer system, process planning algorithms, layered fabrication of samples, challenges and future tasks.Mechanical Engineerin

The future of computing beyond Moore's Law.

Moore's Law is a techno-economic model that has enabled the information technology industry to double the performance and functionality of digital electronics roughly every 2 years within a fixed cost, power and area. Advances in silicon lithography have enabled this exponential miniaturization of electronics, but, as transistors reach atomic scale and fabrication costs continue to rise, the classical technological driver that has underpinned Moore's Law for 50 years is failing and is anticipated to flatten by 2025. This article provides an updated view of what a post-exascale system will look like and the challenges ahead, based on our most recent understanding of technology roadmaps. It also discusses the tapering of historical improvements, and how it affects options available to continue scaling of successors to the first exascale machine. Lastly, this article covers the many different opportunities and strategies available to continue computing performance improvements in the absence of historical technology drivers. This article is part of a discussion meeting issue 'Numerical algorithms for high-performance computational science'

An Architectural Approach to Managing Knowledge Stocks and Flows: Implications for Reinventing the HR Function

Sustainable competitive advantage is increasingly dependent upon a firm’s ability to manage both its knowledge stocks and flows. We examine how different employees’ knowledge stocks are managed within a firm and how—through their recombination and renewal—those stocks can create sustainable competitive advantage. To do this, we first establish an architectural framework for managing human resources and review how the framework provides a foundation for studying alternative employment arrangements used by firms in allocating knowledge stocks. Next, we extend the architecture by examining how knowledge stocks (human capital) can be both recombined and renewed through cooperative and entrepreneurial archetypes. We then position two HR configurations to focus on facilitating these two archetypes. By identifying and managing different forms of social capital across employee groups within the architecture, HR practices can facilitate the flow of knowledge within the firm, which ultimately leads to sustainable competitive advantage

Special Session on Industry 4.0

No abstract available

Eco‐Holonic 4.0 Circular Business Model to Conceptualize Sustainable Value Chain Towards Digital Transition

The purpose of this paper is to conceptualize a circular business model based on an Eco-Holonic Architecture, through the integration of circular economy and holonic principles. A conceptual model is developed to manage the complexity of integrating circular economy principles, digital transformation, and tools and frameworks for sustainability into business models. The proposed architecture is multilevel and multiscale in order to achieve the instantiation of the sustainable value chain in any territory. The architecture promotes the incorporation of circular economy and holonic principles into new circular business models. This integrated perspective of business model can support the design and upgrade of the manufacturing companies in their respective industrial sectors. The conceptual model proposed is based on activity theory that considers the interactions between technical and social systems and allows the mitigation of the metabolic rift that exists between natural and social metabolism. This study contributes to the existing literature on circular economy, circular business models and activity theory by considering holonic paradigm concerns, which have not been explored yet. This research also offers a unique holonic architecture of circular business model by considering different levels, relationships, dynamism and contextualization (territory) aspects