Industry 4.0 technologies enable manufacturing companies to efficiently utilise their assets and reach a competitive advantage. These technologies provide new methods of generating revenue from data-driven services and facilitate predictive maintenance through the use of real-time data analytics. Even after more than a decade from the start of the fourth industrial revolution, manufacturing industry still struggles to upgrade to Industry 4.0-compliant technologies and standards. Currently, the barriers and enablers facing manufacturing companies to adopt new technology are not well understood, and there is a significant gap in the available literature. The authors of this paper review the challenges, opportunities, and applications facing manufacturers from an academic and industrial perspective. In order to identify these factors, a literature review and a survey were chosen. Based on the results of this study, the main challenges identified are financial constraints, a lack of knowledge, and the complexity of new technologies. The research also identified opportunities for manufacturing firms, such as improving efficiency, reducing costs, and improving quality. Potential applications for manufacturers include sharing machine status, predictive maintenance and controlling machines remotely. In the current work, these factors have been ranked from an industrial perspective.

Industry 4.0 technologies and digitalised processes are essential for implementing smart manufacturing within vertically and horizontally integrated production environments. These technologies offer new ways to generate revenue from data-driven services and enable predictive maintenance based on real-time data analytics. They also provide autonomous manufacturing scheduling and resource allocation facilitated by cloud computing technologies and the industrial Internet of Things (IoT). Although the fourth industrial revolution has been underway for more than a decade, the manufacturing sector is still grappling with the process of upgrading manufacturing systems and processes to Industry 4.0-conforming technologies and standards. Small and medium enterprises (SMEs) in particular, cannot always afford to replace their legacy systems with state-of-the-art machines but must look for financially viable alternatives. One such alternative is retrofitting, whereby old manufacturing systems are upgraded with sensors and IoT components to integrate them into a digital workflows across an enterprise. Unfortunately, to date, the scope and systematic process of legacy system retrofitting, and integration are not well understood and currently represent a large gap in the literature. In this article, the authors present an in-depth systematic review of case studies and available literature on legacy system retrofitting. A total of 32 papers met the selection criteria and were particularly relevant to the topic. Three digital retrofitting approaches are identified and compared. The results include insights common technologies used in retrofitting, hardware and software components typically required, and suitable communication protocols for establishing interoperability across the enterprise. These form an initial basis for a theoretical decision-making framework and associated retrofitting guide tool to be developed.

Industry 4.0 technologies and digitalised processes are essential for implementing smart manufacturing within vertically and horizontally integrated industries. These technologies offer new ways to generate revenue from data-driven services and enable predictive maintenance based on real-time data analytics. Although the fourth industrial revolution has been underway for more than a decade, the manufacturing sector is still grappling with the process of upgrading manufacturing systems and processes to Industry 4.0-conforming technologies and standards. Small and medium enterprises (SMEs) cannot always afford to replace their legacy systems with state-of-the-art machines. One option available in such cases is known as retrofitting, in which manufacturing systems of past generations are upgraded with sensors and IoT components to integrate them into a digital workflow across the enterprise. Unfortunately, the scope and systematic process of legacy system retrofitting and integration are not yet well understood and currently represent a large gap in the literature. In this article, the authors present an in-depth systematic review of case studies and available literature on legacy system retrofitting. A total of 32 papers met our selection criteria and were particularly relevant to our topic. The results identify three digital retrofitting solutions.