This paper reports a case study using a standardization process for increasing efficiency and a better optimization of resources in a printing company with 150 operators having manual and mechanical tasks in the box assembly department along with four production lines. The current capacity is 350 boxes per day, while the demand is 650 units, where the company is expected to pay large sums for overtime. Using work standardization, studying worker movements, timing, and workstations redesign, the main goal was to increase the efficiency and productivity indexes. After applying those tools, the inefficient movements in operators decreased from 230 to 78, eliminating 66% of the unnecessary movements, as well as the standard time in a workstation decreased from 244 to 199 s (18.44%) per each assembled box, and the production rate increased by 63.2%, that is, 229 units per assembly line a day, where overtime was reduced to zero.

Total quality management (TQM) is a lean manufacturing tool that focuses on ensuring the production of goods that meet design specifications and give customer satisfaction, both attractive benefits highly appreciated by managers. However, there are several factors involved in the success of TQM programs, many of which are cultural aspects associated with human resources (HR). This article presents a structural equation model that integrates three latent variables related to internal HR: “managerial commitment,” “employee integration,” and “training and education,” which are linked to the operational benefits of a manufacturing system. The variables are connected through six hypotheses that have been validated with information obtained from 398 responses of a questionnaire applied to manufacturing industry professionals. In addition, a sensitivity analysis was carried out to describe the probabilities of occurrence for the variables at low and high levels. The hypotheses were statistically validated with the partial least squared technique, where the results showed that human factors play an essential role in the success of TQM, since the direct, indirect, and total effects of managerial commitment, employee integration and training, and education processes on the benefits obtained from the implementation of TQM were statistically significant at 95% confidence.

This research explores the prospective implementations of artificial intelligence (AI) algorithms within the agrifood sector, focusing on the Spanish context. AI methodologies, encompassing machine learning, deep learning, and neural networks, are increasingly integrated into various agrifood sectors, including precision farming, crop yield forecasting, disease diagnosis, and resource management. Utilizing a comprehensive bibliometric analysis of scientific literature from 2020 to 2024, this research outlines the increasing incorporation of AI in Spain and identifies the prevailing trends and obstacles associated with it in the agrifood industry. The findings underscore the extensive application of AI in remote sensing, water management, and environmental sustainability. These areas are particularly pertinent to Spain’s diverse agricultural landscapes. Additionally, the study conducts a comparative analysis between Spain and global research outputs, highlighting its distinctive contributions and the unique challenges encountered within its agricultural sector. Despite the considerable opportunities presented by these technologies, the research identifies key limitations, including the need for enhanced digital infrastructure, improved data integration, and increased accessibility for smaller agricultural enterprises. The paper also outlines future research pathways aimed at facilitating the integration of AI in Spain’s agriculture. It addresses cost-effective solutions, data-sharing frameworks, and the ethical and societal implications inherent to AI deployment.

Producing quality wines is the primary objective of wine-making companies. Aging plays a fundamental role in the vinification process involved in the production of quality wines. This paper presents a gate-to-gate life cycle analysis (LCA) of all the productive processes involved in aging one liter of wine in Quercus alba/petrea oak barrels for six months. The research was undertaken using 225-L, 300-L, and 500-L barrels. In the category Global Warming, aging in 225-L barrels has an environmental impact of 3.27 kg CO2 eq./liter of wine for every liter aged for six months in Quercus alba and 3.18 E-02 kg CO2 eq./liter of wine for Quercus petraea. The same aging in 300-L and 500-L barrels has environmental impacts of 2.21 kg CO2 eq./liter of wine and 1.58E-02 kg CO2 eq./liter of wine respectively for Quercus alba. These last values are reduced to 2.18 E-02 kg CO2 eq./liter of wine and 1.53 E-02 kg CO2 eq./liter of wine for Quercus petraea specie.