Digital Society Ecosystem Impact on Creative Industry

Industry 4.0 phenomenon has emerged since many technological breakthroughs developed in the past decades. Human well-being behavior are basically influenced by the digital technology. The current customers incline the need for customized products. This situation drive the production paradigm shift from the mass production to the individual production. This paradigm shift force companies to own more resources. Companies’ collaboration is a way to win the competition. Industrial revolution era bring the fact that dominant economic activity is coming from a strong business ecosystem. The major impact of digitalization is faced by the creative industries, an industry priority and a \u27laboratory\u27 for studying economic transformation and modern society. This paper will review the digitalization in industry 4.0 era, business ecosystem and society shift, and the digitalization impact on creative industry. Keywords Industry 4.0; business ecosystem; society shift; creative industr

Understanding Digital Technology’s Evolution and the Path of Measured Productivity Growth: Present and Future in the Mirror of the Past

Three styles of explanation have been advanced by economists seeking to account for the so-called 'productivity paradox'. The coincidence of a persisting slowdown in the growth of measured total factor productivity (TFP) in the US, since the mid-1970's, with the wave of information technology (It) innovations, is said by some to be an illusion due to the mismeasurement of real output growth; by others to expose the mistaken expectations about the benefits of computerization; and by still others to reflect the amount of time, and the volume of intangible investments in 'learning', and the time required for ancillary innovations that allow the new digital technologies to be applied in ways that are reflected in measured productivity growth. This paper shows that rather than viewing these as competing hypotheses, the dynamics of the transition to a new technological and economic regime based upon a general purpose technology (GPT) should be understood to be likely to give rise to all three 'effects.' It more fully articulates and supports this thesis, which was first advanced in the 'computer and dynamo' papers by David (1990, 1991). The relevance of that historical experience is re-asserted and supported by further evidence rebutting skeptics who have argued that the diffusion of electrification and computerization have little in common. New evidence is produced about the links between IT use, mass customization, and the upward bias of output price deflators arising from the method used to 'chain in' new products prices. The measurement bias due to the exclusion of intangible investments from the scope of the official national product accounts also is examined. Further, it is argued that the development of the general-purpose PC delayed the re-organization of businesses along lines that would have more directly raised task productivity, even though the technologies yielded positive 'revenue productivity' gains for large companies. The paper concludes by indicating the emerging technical and organizational developments that are likely to deliver a sustained surge of measured TFP growth during the decades that lie immediately ahead.

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

General Purpose Technologies and Productivity Surges: Historical Reflections on the Future of the ICT Revolution

Presented to the International Symposium on ECONOMIC CHALLENGES OF THE 21ST CENTURY IN HISTORICAL PERSPECTIVE, Oxford, England, 2nd-4th July, 1999 Celebrating the Scholarly Career of Charles H. Feinstein, FBA. Re- examination of early twentieth century American productivity growth experience sheds light on the general phenomenon of recurring prolonged swings in total factor productivity (TFP) growth rate experienced in the advanced industrial economies. After a “productivity slowdown” lasting more than a quarter of a century (during which TFP for in the manufacturing sector grew at less than 1 percent per annum, industrial TFP surged to average 6 percent per annum during 1919-29. This contributed substantially to the absolute and relative rise of the US domestic economy’s TFP residual, and in many respects it may be seen as the opening of the high-growth era that persisted into the 1970s. The productivity surge marked the culminating phase in the diffusion of “the dynamo” as a general purpose technology (GPT); that saw a shift in the underlying technological regime brought about by the implementation of critical engineering and organizational advances originating in some two decades earlier. Closer analysis reveals the significant concurrence of the factory electrification movement in this period with important structural changes that were taking place in US labor markets; in addition, there were significant complementarities between managerial and organizational innovations and the new dynamo-based factory technology, on the one hand, and, and the reinforcement of both kinds of innovation by the macroeconomic conditions of the 1920s. This more complicated, historical view of the dynamics of GPT diffusion is supported by comparisons of the US experience of factory electrification with the developments taking place in Japanese industry during the 1920’s, and in the UK manufacturing sector during the 1930’s. Concluding sections of the paper reflect on the analogies and contrasts between the historical case of a socio-economic regime transition involving the electric dynamo and the modern experience of the information and communications technology (ICT) revolution. Our formulation the GPT concept in explicitly historical terms contributes to explaining the paradoxical phenomenon of the late twentieth century productivity slowdown in the US. It also points to some contemporary portents of a future phase of more rapid ICT-based growth in total factor productivity.

Towards Developing a Digital Twin Implementation Framework for Manufacturing Systems

This research studies the implementation of digital twins in manufacturing systems. Digital transformation is relevant due to changing manufacturing techniques and user demands. It brings new business opportunities, changes organizations, and allows factories to compete in the digital era. Nevertheless, digital transformation presents many uncertainties that could bring problems to a manufacturing system. Some potential problems are loss of data, cybersecurity threats, unpredictable behavior, and so on. For instance, there are doubts about how to integrate the physical and virtual spaces. Digital twin (DT) is a modern technology that can enable the digital transformation of manufacturing companies. DT works by collecting real-time data of machines, products, and processes. DT monitors and controls operations in real-time helping in the identification of problems. It performs simulations to improve manufacturing processes and end-products. DT presents several benefits for manufacturing systems. It gives feedback to the physical system, increases the system’s reliability and availability, reduces operational risks, helps to achieve organizational goals, reduces operations and maintenance costs, predicts machine failures, etc. DT presents all these benefits without affecting the system’s operation. xv This dissertation analyzes the implementation of digital twins in manufacturing systems. It uses systems thinking methods and tools to study the problem space and define the solution space. Some of these methods are the conceptagon, systemigram, and the theory of inventive problem solving (TRIZ in Russian acronym). It also uses systems thinking tools such as the CATWOE, the 9-windows tool, and the ideal final result (IFR). This analysis gives some insights into the digital twin implementation issues and potential solutions. One of these solutions is to build a digital twin implementation framework Next, this study proposes the development of a small-scale digital twin implementation framework. This framework could help users to create digital twins in manufacturing systems. The method to build this framework uses a Model-Based Systems Engineering approach and the systems engineering “Vee” model. This framework encompasses many concepts from the digital twin literature. The framework divides these concepts along three spaces: physical, virtual, and information. It also includes other concepts such as digital thread, data, ontology, and enabling technologies. Finally, this dissertation verifies the correctness of the proposed framework. The verification process shows that the proposed framework can develop digital twins for manufacturing systems. For that purpose, this study creates a process digital twin simulation using the proposed framework. This study presents a mapping and a workflow diagram to help users use the proposed framework. Then, it compares the digital twin simulation with the digital twin user and system requirements. The comparison finds that the proposed framework was built right

Exploring the Synergy between Industry 4.0, Quality 4.0, and Lean Production for Improved Quality in Manufacturing

The manufacturing industry has experienced significant changes with the advent of technological advancements. Industry 4.0 and Quality 4.0 have emerged as new paradigms focusing on the use of digital technologies to enhance efficiency and quality in manufacturing. Additionally, the long-established lean approach aims to minimize waste and improve overall quality. Integrating these approaches with Industry 4.0 and Quality 4.0 has the potential to transform the industry by optimizing quality, efficiency, and profitability. Therefore, this study aims to explore the interconnections between lean, Industry 4.0, and Quality 4.0, and their impact on quality in manufacturing. The research begins by providing the necessary background, starting with a comprehensive examination of the concept of quality. Subsequently, the study presents an overview of lean principles, followed by an analysis of the concepts of Industry 4.0 and Quality 4.0. The theoretical framework also explores the relationship between these concepts. Following the theoretical analysis, the empirical part of the study was conducted using a survey questionnaire. The survey was distributed to 190 medium-sized manufacturing companies in Finland, ultimately receiving responses from 44 organizations. This survey aimed to gather practical insights into the implementation of lean, Industry 4.0, and Quality 4.0 practices within the manufacturing context. Based on the findings derived from the survey data, lean tools have a broader adoption compared to Industry 4.0 and Quality 4.0 practices. Moreover, implementing these tools and practices has shown a positive impact on company performance, sparking a growing interest among companies to explore and implement additional tools. The survey also highlights a strong inclination among organizations to embrace Industry 4.0 and Quality 4.0 practices, showcasing their increasing recognition of the potential benefits and transformative capabilities of these innovative methodologies in driving organizational success

Design and Implementation of Hierarchical Digital Twins in Industrial Production Environments

The increasing requirements for industrial production environments due to customer expectations, the implementation of batch size 1, and further automation of production processes are confronting companies with new challenges. In particular, the emergence of cyber-physical systems is influencing and complicating manufacturing processes by capturing an increasing amount of information within production facilities. Digital twins are an interdisciplinary technology that may solve these issues because they serve to monitor, control, and optimize cyber-physical systems by creating a digital representation of real-world objects. Existing concepts for digital twins usually consider specific and independent objects. This is of limited use for production environments due to a multitude of different machines and associated sensor types. Therefore, we propose a requirements catalog, concept, and prototypical implementation for the hierarchical structuring of digital twins in this paper