Smart Education System Initiatives to Support Data Science and Industry 4.0

Introduction

In the last decades, technological advances in Information Technology (IT) have made computing devices more economical and widespread than ever. From households to industrial plants, a variety of devices allow a quick and effortless access to information. In an industrial environment a series of sensors gather process data which can be posterior analyzed with the main goal of productivity increase and preventive maintenance. To take advantage of the increasing role of IT on the factory floor, a set of design practices were identified and proposed under the common concept of a fourth industrial revolution. In Europe this concept is commonly designated as Industry 4.0(I4.0) after the German industrial development program with the same name. This new concept makes use of cyber-physical systems, the Cloud and the Internet of Things to aid in the management of the complete product life cycle (Pacheco & Reis, 2019). Industry 4.0 is a shift from the previous industry shape. Automation is as a result of technology involving electrical energy. Changes occur and lead to paperless and humanless, but these changes require preparation both in the industrial world and in other supporting worlds. Data is a different side of technology. Data involves many different concepts from the industrial world, even though either data of the industrial world involve the same technology. Specifically, data management is different than industry management. The realization of Industry 4.0 model requires theoretical knowledge and practical skills in industrial automation and networking (Yakimov & Iovey, 2019). Universities have a relevant and essential key role to ensure knowledge and development of competencies in the current fourth industrial revolution called Industry 4.0. The Industry 4.0 promotes a set of digital technologies to allow the convergence between the information technology and the operation technology towards smarter factories. Under such new framework, multiple initiatives are being carried out worldwide as response of such evolution, particularly, from the engineering education point of view (Prieto et al., 2019). One of the primary indices to determine the economic progress of a country is its gross domestic product (GDP). The higher the percentage of GDP, the better will be the country’s performance in terms of economic production and growth (Mian et al., 2020).

Figure 1.

Digital skills in education

Active Learning By Practical

Inter-disciplinarily and creativity are recognized by several institutions as two key skills that need to be enhanced in engineering courses in higher education. Current research concludes that future industrial engineering work will be characterized by increased networking, flexibility, and control over innovative technologies. The student team aims to cover the automation and digitization of industrial processes through his horizontal and vertical network of relevant OT and IT elements. Students thus lead to the development of features and services such as flexible automation, IIoT devices, development of CPS based on artificial intelligence, and augmented reality based on interfaces. All these elements interact to facilitate an enhanced, connected environment of human-machine collaboration. In this context, the proposed content for the promotion of Engineering 4.0 programs at the Bachelor and Masters level lies in the design of challenging environments in which students are involved in complete industrial processes as a real learning framework. This approach offers a combination of active learning techniques such as problem-based learning and problem-oriented learning, where the educational process is linked to experimental solutions to proposed tasks. In this way, students should experience participation in a collaborative laboratory where interdisciplinary projects are carried out in real industrial cells.

Figure 2.

Five stage teaching-learning model