The Industrial Internet and the Potentially Economically Disruptive Technologies

This first chapter is based on Industry 4.0 in its entirety; origin, definition of the Fourth Industrial Revolution, its main characteristics, current transformation segments, challenges and opportunities, the presence of companies in worldwide network Industry 4.0, the disruptive technologies with a significant potential to drive economic impact and disruption, implications and challenges for business leaders in this new technological and business landscape.2019-2

Literature search of key factors for the development of generic and specific maturity models for industry 4.0

The adequacy of business models to Industry 4.0 (I4.0) is an urgent requirement and a clear concern. Ways to recognize the relative position of a company and ways to evolve towards this new paradigm are an important step both for researchers and professionals. In general, most small and medium enterprises (SME) do not have their own resources or do not have the means to be fully supported by consultancies, to develop a specific model, and they do not recognize themselves as ready to initiate any action to adapt to this new paradigm. Based on the idea of identification of directions and opportunities of research about the conditions for the adoption of approaches involving readiness assessment, implementation framework, roadmap and maturity model, the main objective of this article is the identification of factors for the development of specific maturity models, oriented towards unique conditions, located in specific contexts, and that can cover both the need for self-diagnosis of the level of preparation, as well as the actions that aim to achieve a progressive reconfiguration and guided by continuous improvement towards Industry 4.0. A Systematic Literature Review (SLR) of 67 articles was conducted and resulted in the identification of two approaches to address maturity models, which are the application of existing generic models and the process of building specific ones focused on the peculiarities of certain contexts. Moreover, this work points out five factors for development of a specific maturity model: context characterization, conceptual characterization, interaction with practitioners and experts, development of surveys, and qualitative research. Additionally, this work identified the need for development of methodologies that can be applied in a more autonomous way for the development of specific maturity models.This work has been supported by FCT—Fundação para a Ciência e Tecnologia within the R&D UnitsProject Scope UIDB/00319/2020

The environmental impact of advanced manufacturing technologies

The purpose of the paper is to demonstrate the beneficial impact of advanced manufacturing technologies (AMT) on firms’ environmental performance. Drawing on interviews conducted with 16 Hungarian manufacturing subsidiaries on their experience with AMT, we find three functional areas, where industry 4.0 solutions can not only enhance operational excellence and cost-efficiency, but they can also improve eco-efficiency, but they can also improve eco-efficiency, namely in the field of quality management (through smart production control, data analytics and predictive modelling solutions); process optimization (through capacity planning and production scheduling solutions); and product and process engineering (through advanced virtual technologies). We also find that AMT adoption facilitated subsidiary upgrading along various dimensions. The main managerial implication is that subsidiaries need to be proactive, and emphasize also the benefits stemming from energy and resource efficiency improvement when lobbying for investment in AMT

A categorical framework of manufacturing for industry 4.0 and beyond

AbstractWith rapid advancements in industry, technology and applications, many concepts have emerged in manufacturing. It is generally known that the far-sighted term ‘Industry 4.0’ was published to highlight a new industrial revolution. Many manufacturing organizations and companies are researching this topic. However, the achievement criteria of Industry 4.0 are as yet uncertain. In addition, the technology roadmap of accomplishing Industry 4.0 is still not clear in industry nor in academia to date. This paper focuses on the fundamental conception of Industry 4.0 and the state of current manufacturing systems. It also identifies the research gaps between current manufacturing systems and Industry 4.0 requirements. The major contribution is an implementation structure of Industry 4.0, consisting of a multi-layered framework is described, and is shown how it can assist people in understanding and achieving the requirements of Industry 4.0

A review of the meanings and the implications of the Industry 4.0 concept

The global industrial landscape has changed deeply in the last few years due to successive technological developments and innovations in manufacturing processes. The Industry 4.0 concept has emerged and the academic literature has paid an increased attention to this topic, which remains non-consensual or ill defined. In this research, a literature review is made to understand this concept in its technological dimension, and to comprehend its impacts. This new industrial paradigm brings together the digital and physical worlds through the Cyber-Physical Systems enhanced by Internet of Things and it is expected that this novel has consequences on industry, markets and economy, improving production processes and increasing productivity, affecting the whole product lifecycle, creating new business models, changing the work environment and restructuring the labor market. Therefore, this paper focuses on Industry 4.0 concept and contributes for its clarification and further understanding about the importance and implications of this complex technological system.This work has been supported by COMPETE: POCI-01-0145-FEDER-007043 and FCT – Fundação para a Ciência e Tecnologia within the Project Scope: UID/CEC/00319/2013.info:eu-repo/semantics/publishedVersio

Organisational sustainability modelling - An emerging service and analytics model for evaluating Cloud Computing adoption with two case studies

© 2015 Elsevier Ltd. Cloud Computing is an emerging technology which promises to bring with it great benefits to all types of computing activities including business support. However, the full commitment to Cloud Computing necessary to gain the full benefit is a major project for any organisation, since it necessitates adoption of new business processes and attitudes to computing services in addition to the immediately obvious systems changes. Hence the evaluation of a Cloud Computing project needs to consider the balance of benefits and risks to the organisation in the full context of the environment in which it operates; it is not sufficient or appropriate to examine technical considerations alone.In this paper, we consider the application of CAPM, a well established approach used for the analysis of risks and benefits of commercial projects to Cloud adoption projects and propose a revised and improved technique, OSM. To support the validity of OSM, two full case studies are presented. In the first, we describe an application of the approach to the iSolutions Group at University of Southampton, which focuses on evaluations of Cloud Computing service improvement. We then illustrate the use of OSM for measuring learning satisfaction of two cohort groups at the University of Greenwich. The results confirm the advantages of using OSM. We conclude that OSM can analyse the risk and return status of Cloud Computing services and help organisations that adopt Cloud Computing to evaluate and review their Cloud Computing projects and services. OSM is an emerging service and analytics model supported by several case studies

At the edge of the Fourth Industrial Revolution: Employees’ perceptions of employment equity from a CIBART perspective

Abstract: Orientation: In accordance with global trends, South Africa is striving for the Fourth Industrial Revolution (4IR). Discourses of employees’ employment equity (EE) perceptions within the 4IR context are studied 25 years after apartheid. Research purpose: The purpose of the study was to understand the systems psychodynamics underneath the surface of employees’ perceptions of EE in South Africa within the context of the 4IR. Motivation for the study: South African workplaces are debated nationally and urged to compete with 4IR changes on a global level. This research focuses on employees’ perceptions of EE underneath the surface and aims at understanding employees’ perceptions through the conflict, identity, boundaries, authority, roles, task (CIBART) model..

Supply chain hybrid simulation: From Big Data to distributions and approaches comparison

The uncertainty and variability of Supply Chains paves the way for simulation to be employed to mitigate such risks. Due to the amounts of data generated by the systems used to manage relevant Supply Chain processes, it is widely recognized that Big Data technologies may bring benefits to Supply Chain simulation models. Nevertheless, a simulation model should also consider statistical distributions, which allow it to be used for purposes such as testing risk scenarios or for prediction. However, when Supply Chains are complex and of huge-scale, performing distribution fitting may not be feasible, which often results in users focusing on subsets of problems or selecting samples of elements, such as suppliers or materials. This paper proposed a hybrid simulation model that runs using data stored in a Big Data Warehouse, statistical distributions or a combination of both approaches. The results show that the former approach brings benefits to the simulations and is essential when setting the model to run based on statistical distributions. Furthermore, this paper also compared these approaches, emphasizing the pros and cons of each, as well as their differences in computational requirements, hence establishing a milestone for future researches in this domain.This work has been supported by national funds through FCT -Fundacao para a Ciencia e Tecnologia within the Project Scope: UID/CEC/00319/2019 and by the Doctoral scholarship PDE/BDE/114566/2016 funded by FCT, the Portuguese Ministry of Science, Technology and Higher Education, through national funds, and co-financed by the European Social Fund (ESF) through the Operational Programme for Human Capital (POCH)