Industry 4.0 is changing the industrial environment. Particularly, the emerging Industry 4.0 technologies can improve the agri-food supply chain throughout all its stages. This study aims to highlight the benefits of implementing Industry 4.0 in the agri-food supply chain. First, it presents how technologies enhance the agri-food supply chain development. Then, it identifies and highlights the most common challenges that Industry 4.0 implementation faces in agri-food’s environment. After that, it proposes key performance indicators to measure the advantages of this implementation. To achieve this, a systematic literature review was conducted. It combined conceptual and bibliometric analyses of 78 papers. As a result, the most suitable technologies were identified, e.g., Internet of Things, Big Data, blockchain and cyber physical systems. The most used indicators are proposed and the challenges of implementation were detected and classified in three groups, i.e., technical, educational and governmental. This paper highlights and exemplifies the benefits of implementing Industry 4.0 facing the lack of knowledge that exists nowadays. Moreover, it fulfils the gaps in literature, i.e., the lack of information about the implementation of technologies 4.0 or the description of the most relevant indicators for Industry 4.0 implementation.

This work investigates Industry 4.0 technologies by developing a new key performance indicator that can determine the energy consumption of machine tools for a more sustainable supply chain. To achieve this, we integrated the machine tool indicator into a cyber–physical system for easy and real-time capturing of data. We also developed software that can turn these data into relevant information (using Python): Using this software, we were able to view machine tool activities and energy consumption in real time, which allowed us to determine the activities with greater energy burdens. As such, we were able to improve the application of Industry 4.0 in machine tools by allowing informed real-time decisions that can reduce energy consumption. In this research, a new Key Performance Indicator (KPI) was been developed and calculated in real time. This KPI can be monitored, can measure the sustainability of machining processes in a green supply chain (GSC) using Nakajima’s six big losses from the perspective of energy consumption, and is able to detect what the biggest energy loss is. This research was implemented in a cyber–physical system typical of Industry 4.0 to demonstrate its applicability in real processes. Other productivity KPIs were implemented in order to compare efficiency and sustainability, highlighting the importance of paying attention to both terms at the same time, given that the improvement of one does not imply the improvement of the other, as our results show.

Climate change, resource scarcity, and a growing world population are some of the problems facing traditional agriculture. For this reason, new cultivation systems are emerging, such as vertical farming. This is based on indoor cultivation, which is not affected by climatic conditions. However, vertical farming requires higher consumption of water and light, since in traditional agriculture those resources are free. Vertical cultivation requires the use of new technologies and sensors to reduce water and energy consumption and increase its efficiency. The sensorization of these systems makes it possible to monitor and evaluate their performance in real time. In addition, vertical farming faces economic uncertainty since its profitability has not been studied in depth. This article studies the most important variables when monitoring a vertical farming system and proposes the sensors to be used in the data acquisition system. In addition, this study presents a cost model for the installation of this type of system. This cost model is applied to a case study to evaluate the profitability of installing this type of infrastructure. The results obtained suggest that the investment made in VF installations could be profitable in a period of three to five years.

The purpose of this paper is to build up and implement a framework of a lean performance indicator with collaborative participation. A new indicator derived from OEE is presented, overall process effectiveness (OPE), which measures the effectiveness of an operation process. The action research (AR) methodology was used; collaborative work was done between researchers and management team participation. The framework was developed with the researchers’ and practitioners’ experiences, and the data was collected and analyzed; some improvements were applied and finally, a critical reflection of the process was done. This new metric contributes to measuring the unloading process, identifying losses, and generating continuous improvement plans tailored to organizational needs, increasing their market competitiveness and reducing the non-value-add activities. The OEE framework is implemented in a new domain, opening a new line of research applied to logistic process performance. This framework contributes to recording and measuring the data of one unloading area and could be extrapolated to other domains for lean performance. It was possible to generate and validate knowledge applied in the field. This study makes collaborative participation providing an effectiveness indicator that helps the managerial team to make better decisions through AR methodology.

This study aims to review the literature published in the last 15 years (2007–2022) that relates to Industry 4.0 and the green supply chain (GSC). This review identifies the enabling technologies for Industry 4.0 that are being applied to improve GSC practices and establishes the points of its future research agenda. A systematic literature review (SLR) of this topic was conducted using Web of Science and Scopus as databases. Our study combined descriptive and conceptual analysis, guided by three review questions. These questions were proposed to identify how Industry 4.0 technologies can enhance the development of GSCs. After refinement, 75 papers were analyzed. This research underlines what technologies of Industry 4.0 are being implemented to improve GSC aspects. In addition, it shows in which GSC practices the application of these technologies is being considered and what challenges of implementing Industry 4.0 in GSCs have been identified in the literature. Finally, all these findings enhance establishing a future research agenda. Current studies have focused on analyzing the benefits of implementing Industry 4.0 in GSCs. However, this paper delves into enabling technologies for Industry 4.0 and GSC practices and does not only discuss them in general terms.

Among the new trends in technology that have emerged through the Industry 4.0, Cyber Physical Systems (CPS) and Internet of Things (IoT) are crucial for the real-time data acquisition. This data acquisition, together with its transformation in valuable information, are indispensable for the development of real-time indicators. Moreover, real-time indicators provide companies with a competitive advantage over the competition since they enhance the calculus and speed up the decision-making and failure detection. Our research highlights the advantages of real-time data acquisition for supply chains, developing indicators that would be impossible to achieve with traditional systems, improving the accuracy of the existing ones and enhancing the real-time decision-making. Moreover, it brings out the importance of integrating technologies 4.0 in industry, in this case, CPS and IoT, and establishes the main points for a future research agenda of this topic.