Advancing Smart Manufacturing in Europe: Experiences from Two Decades of Research and Innovation Projects

In the past two decades, a large amount of attention has been devoted to the introduction of smart manufacturing concepts and technologies into industrial practice. In Europe, these efforts have been supported by European research and innovation programs, bringing together research and application parties. In this paper, we provide an overview of a series of four content-wise connected projects on the European scale that are aimed at advancing smart manufacturing, with a focus on connecting processes on smart factory shop floors to manufacturing equipment on the one hand and enterprise-level business processes on the other hand. These projects cover several tens of application cases across Europe. We present our experiences in the form of a single, informal longitudinal case study, highlighting both the major advances and the current limitations of developments. To organize these experiences, we place them in the context of the well-known RAMI4.0 reference framework for Industry 4.0 (covering the ISA-95 standard). Then, we analyze the experiences, both the positive ones and those including problems, and draw our learnings from these. In doing so, we do not present novel technological developments in this paper—these are presented in the papers we refer to—but concentrate on the main issues we have observed to guide future developments in research efforts and industrial innovation in the smart industry domain.

An Investigation to the Industry 4.0 Readiness of Manufacturing Enterprises

The visions of what constitutes the Industry 4.0 is an industry based on gains in efficiency and productivity enhancements supported by integrated, smart information systems. This has caused information systems strategic misalignment that present a severe barrier to National and organizational aspirations. This paper studies the readiness of manufacturing companies for the Industry 4.0, by using a case study of Chinese multinational enterprise in the aluminum production sector. The research design follows a rigorous grounded theory approach, which consisted of 41 semi-structured interviews in 7 different company branches. Based on this case study, the paper proposes an IS strategic misalignment model that identifies three levels of misalignment that need to be resolved before the vision of the smart industry can be realized. Six main categories of causes and five main categories of consequences of IS strategic misalignment are presented. This study contributes to the IS alignment literature and provides important implications for the achievement of Industry 4.0 in practice.

Research on the Value Chain as a Strategic Management Tool for the Digital Enterprise

The scientific paper summarizes the definition and structures of main and secondary activities, the value chain, the means of carrying out the cooperation of the economic environment with research as a necessity for increasing innovation in digital enterprises in Romania and the research results and contributions on mechatronic and cyber-mixmechatronic systems, technological platforms - cobotic platforms, platform networks and networks of technology and cobotic platform networks for the digital enterprise and for the smart industry as a whole (4.0). These concepts and constructive robots that have emerged as results of the research efforts in INCDMTM are presented concretely, as an important part in the realization of some of the parts of the digital enterprise and of the intelligent industry.

THE FUTURE OF SMART INDUSTRY: TECHNOLOGIES, MACRO-TRENDS AND APPLICATION AREAS

The Smart Industry has been developing has been developing at an accelerated pace since the beginning of the last decade, driven by of the last decade, driven by the by the emergence of technologies such as the Internet of Things, Compute of Things, Cloud Computing and Big Data Cloud Computing and Big Data technologies, as well as their connection and Big Data technologies, as well as their connection with machine learning algorithms for predictive data analysis [1] of data [1].

Changeability and agility enablers in one-of-a-kind product development and design processes

The smart factories that are already beginning to appear employ a completely new approach to product creation. Smart products are uniquely identifiable and know both their current status and alternative routes to achieving their target state. Smart factories allow individual customer requirements to be met, meaning that even one-off items can be manufactured profitably. In smart industry, dynamic business and engineering processes enable last-minute changes to design and production, delivering the ability to respond flexibly to disruptions and failures on behalf of suppliers. This paper presents a case study of product development and design process renovation according to changeability paradigm in one-of-a-kind industrial environment. It demonstrates how integration of changeability with agile design strategies crucially contribute to improve the operations of a highly individualized product development business. Successful management of ‘never-ending’ engineering changes appears to be the most important aspect in this field. Contribution of the presented work is a generalized framework that demonstrates how companies in such specific environments can improve competitiveness through the utilization of changeability concepts. The included case study validated the proposed changeability model and offers valuable insights into how to implement this in practice.

Smart Industry Monitoring and Controlling System Using IoT

Air pollution in an ecosystem has proliferated industrial automation. This dissertation concentrates more on industrial automation and has design an embedded device with sensors to monitor and control the toxic gases in industries. This entire prototype is an excellent result for observing the toxic gases in industry and generates information by using data acquisition and transmission of data. “Internet of Things (IoT)” is a important technology behind this and it provide platform to bring together all the devices in the world to the internet. In this dissertation, the parameters monitored are temperature, humidity and gas leakages in industries. The sensor senses the parameters and uploads these data to the cloud with the help of NodeMCU. If observed gas level is above the threshold which is the safety limit of operation, the first alert is intimated from the Google cloud and the controlling action carried out (ie) automatically close gas leakage valves and then industry will take immediate step to control pollution. Or else, the second alert message is sent through Electronic mail (e-mail) to restore the safe limit, as government play role to power outage in the industries. Cloud is used to store the sensed data, which is then transmitted and processed.

EXCURSION TO THE SMART DIMENSION THROUGH MATHEMATICS: SIGNIFICANCE OF OUTCOME-BASED EDUCATION

The advancement of a smart society depends to a large extent on the standard of the higher education system. The fourth Industrial Revolution (FIR), or smart industry, is the trend related to artificial intelligence, changing various aspects of life, especially the education system. The flow of the smart industry, spurring Bangladesh to accept the technologies of the FIR. The drift of FIR will drop a strong impact on our graduates. The smart industry needs the efficiency of Science, Technology, Engineering, and Mathematics (STEM). Mathematics is a scaffold to the next industrial revolution. So, our university education system should be convenient to set up our graduates all around the smart world and overcome the industrial requirements; it is compulsory to adopt Outcome-Based Education (OBE). OBE templates were approved at the 157th meeting of the University Grants Commission of Bangladesh (UGC) on 06 February 2020. Recently, UGC has requested that all universities modify their undergrad educational plans depending on the Outcome-Based Education (OBE) layout. The purpose of this article is to look at the significance of skilled Mathematics alumni for the smart world, and we also examine the challenges of actualizing Outcome-Based Education (OBE).