Assembly line rebalancing is a problem companies are frequently confronted with as continuous changes in product features and volume demand caused by the volatility of modern markets result in re-definition of assembly tasks and line cycle time fluctuations. Consequently, managers are forced to adjust the balancing of their lines in order to adapt to the new conditions while trying to minimise both increases in completion costs and costs related to changes in task assignment. In particular, when modifications are made to line balancing, costs are incurred for operator training, equipment switching and moving, and quality assurance. The stochastic assembly line rebalancing problem is essentially composed of a multi-objective problem in which two joint objectives, total expected completion cost of the new line and similarity between the new and the existing line, must be optimised. Consequently, this paper presents a multiple single-pass heuristic algorithm developed for the purpose of finding the most complete set of dominant solutions representing the Pareto front of the problem. The operative parameters of the heuristic are set as a result of a great deal of experimentation. Moreover, a multi-objective genetic algorithm is developed and then compared with the proposed heuristic in order to demonstrate its effectiveness. Finally, an illustrative case study is presented.
The global demand for electrical and electronic equipment has undergone continuous growth in recent years due to the effect of industrialization and technological development. This indicates substantial quantities of e-waste that need to be managed properly to reduce their environmental impact and to avoid inappropriate forms of disposal. The purpose of this paper is to review the most popular multi-criteria decision-making approaches applied to the management of waste electrical and electronic equipment, analyzing how they are used to contribute to the improvement of management strategies along the entire supply chain. For this purpose, a methodological protocol for the collection, selection, and analysis of the scientific literature was applied, identifying 44 papers on which to conduct this study. The results showed that numerous authors have developed multi-criteria approaches, with particular attention to recycling phase. The analytic hierarchy process is the most widespread multi-criteria approach, often coupled with VIKOR, DELPHI, and TOPSIS methods. The numerous decision making criteria adopted cover different reference dimensions: environmental, economic, social, technical, and legal. Considering environmental aspects also in decision making processes means enhancing the relevance of this dimension, as well as encouraging practices that reduce the impact of toxic substances on the environment and living organisms.
4 November 2024 in Journal of Manufacturing Systems
Plastic materials account for about 20% of waste electrical and electronic equipment (WEEE). The recycling of this plastic fraction is a complex issue, heavily conditioned by the content of harmful additives, such as brominated flame retardants. Thus, the management and reprocessing of WEEE plastics pose environmental and human health concerns, mainly in developing countries, where informal recycling and disposal are practiced. The objective of this study was twofold. Firstly, it aimed to investigate some of the available options described in the literature for the re-use of WEEE plastic scraps in construction materials, a promising recycling route in the developing countries. Moreover, it presents an evaluation of the impact of these available end-of-life scenarios on the environment by means of the life cycle assessment (LCA) approach. In order to consider worker health and human and ecological risks, the LCA analysis focuses on ecotoxicity more than on climate change. The LCA evaluation confirmed that the plastic re-use in the construction sector has a lower toxicity impact on the environment and human health than common landfilling and incineration practices. It also shows that the unregulated handling and dismantling activities, as well as the re-use practices, contribute significantly to the impact of WEEE plastic treatments.
The textile manufacturing industry is energy- and water-intensive, and has a great impact on the environment. Sustainability-oriented innovation can support the transition of the textile sector towards a circular economy. This review investigates how the textile manufacturing chain can benefit from sustainability-driven innovation strategies to achieve the main circular economy goals. The review was conducted using the Scopus and Web of Science scientific databases, and it addresses material, process, and organizational innovations and covers the 2015–2024 time window. Five main areas of innovation emerged from the retrieved papers, including digitalization, the need for innovative product and process design and sustainable raw materials, the use of textile waste as new raw material outside the textile value chain, waste recovery within the value chain and environmental remediation, and organizational innovation. The innovative solutions analyzed improve the sustainability of the textile manufacturing industry and enable the achievement of circular economy goals. Finally, we discuss some concerns about the introduction of the suggested innovations, including the need to apply design principles for recyclability and durability while studying the feasibility of adopting novel materials.
The COVID-19 health emergency has imposed the need to limit and/or stop non-essential economic and commercial activities and movement of people. The objective of this work is to report an assessment of the change in vehicle flows and in air quality of a specific study area in the north of Italy, comparing the periods February–May 2020 and February–May 2019. Circulating vehicles have been measured at nine characteristic points of the local road network of the city of Reggio Emilia (Italy), while atmospheric pollutant concentrations have been analysed using data extracted from the regional air quality monitoring network. The results highlight a rapid decline in the number of vehicles circulating in 2020 (with values of up to −82%). This has contributed to a reduction in air concentrations of pollutants, in particular for NO2 and CO (over 30% and over 22%, respectively). On the other hand, O3 has increased (by about +13%), but this is expected. Finally, the particulate matter grew (about 30%), with a behaviour similar to the whole regional territory. The empirical findings of this study provide some indications and useful information to assist in understanding the effects of traffic blocking in urban areas on air quality.