Sustainable Operations and Computers最新文献

To assist enterprises in adapting to the challenges of the digital era during the product eco-design stage, based on the synergistic symbiosis theory and the eco-strategy wheel, combined with literature research and expert interviews, this study identifies 11 factors for enterprises to realize product eco-design under digital collaboration. In this study, the Decision-making Trial and Evaluation Laboratory (DEMATEL) method was used to aggregate the identified 11 factors into four factor sets: strong cause, weak cause, strong result, and weak result; and the Interpretive Structural Model (ISM) was used to create a multilevel recursive model of product eco-design for digital collaboration. The study's findings show that: digital collaborative product eco-design is a combination of intra-organizational, intra-organizational, and external organizational synergies; and digital collaboration improves the efficiency of eco-design technology acquisition. This research provides a scientific foundation for company managers to make product eco-design decisions in the context of the worldwide digitalization trend.

The plan of "transforming national high-tech zones into national innovation demonstration zones (hereinafter referred to as" NIDZ") launched in 2009 is an attempt to promote high-quality economic development in China. Based on the quasi-natural experiment of transforming national high-tech zones into NIDZ in 2009, this paper collected and sorted out the data of 51 cities where national high-tech zones were located in China from 2002 to 2018. Then we measured urban green total factor productivity by applying the SBM model and investigated the impact of transformation on urban green total factor productivity through the difference in difference (DID) method. The results show that: (1) Urban green total factor productivity has been improved by transforming into a NIDZ, and the results are relatively stable. (2) Mechanism analysis shows that the promotion of urban green total factor productivity by transformation is realized through green technology innovation and industrial agglomeration mechanism. (3)The heterogeneity analysis shows that the policy effects are better in the developed eastern regions and regions with lower levels of government efficiency, and have not been reflected in the less developed central and western regions and regions with higher levels of government efficiency.

The textile industry supply chains (SC) face numerous risks and disruptions due to the changing dynamics of high demand and limited resources. The impact of epidemics and regional conflicts further complicates global business operations, especially in emerging economies. In this context, the textile sector in these economies must prioritize Sustainable Supply Chain Management (SSCM) to achieve cost reduction, enhance productivity, and improve profitability to sustain their business. Although research has examined several SSCM viewpoints, the barriers that prevent emerging economies from adopting SSCM in the textile sector to meet the Sustainable Development Goals (SDGs) are not sufficiently highlighted in the empirical literature that has already been published. This study analyzes different barriers and investigates how they are interconnected. From the literature research, 17 main barriers were first identified in the process. The barriers were then prioritized in order of significance using a combination of fuzzy theory, Pareto analysis, and the Decision-Making Trial and Evaluation Laboratory (DEMATEL) framework. Finally, the cause-and-effect relationships among these barriers were established. A lack of commitment from the supplier's top management, insufficient financial incentives, and the absence of supportive government standards and regulations were identified as the three topmost significant barriers to SSCM adoption. For the textile sector, governments, and policymakers in emerging economies, the study's results are helpful since they will assist them create mitigation strategies to get rid of these barriers and achieve long-term sustainability.

An increase in greenhouse gases emission from the transportation sector has led companies and the government to elevate and support the production of electric vehicles (EV). With recent developments in urbanization and e-commerce, transportation companies are replacing their conventional fleet with EVs to strengthen the efforts for sustainable and environment-friendly operations. However, deploying a fleet of EVs asks for efficient routing and recharging strategies to alleviate their limited range and mitigate the battery degradation rate. In this work, a fleet of electric vehicles is considered for transportation and logistic capabilities with limited battery capacity and scarce charging station availability. We introduce a min-max electric vehicle routing problem (MEVRP) where the maximum distance traveled by any EV is minimized while considering charging stations for recharging. We propose an efficient branch and cut framework and a three-phase hybrid heuristic algorithm that can efficiently solve a variety of instances. Extensive computational results and sensitivity analyses are performed to corroborate the efficiency of the proposed approach, both quantitatively and qualitatively. Finally a data-driven simulation implemented with the robot operating system (ROS) middleware are performed to corroborate the efficiency of the proposed approach, both quantitatively and qualitatively.

Fused Deposition Modeling (FDM) 3D printing is an advanced Additive Manufacturing (AM) method for developing thermoplastic-based parts. Researchers studied FDM-based 3D printing of PLA with whole biomass and biomass resources such as lignin, hemicellulose, and cellulose. These composites are environmentally friendly, sustainable and have wide applications in healthcare. There is scope for developing the 3D printing of biocomposite with medical surgical cotton fabric, where PLA is unique for such manufacturing. The development and characterisation of FDM 3D printed medical surgical cotton fabric- PLA biocomposite is the primary objective of this work. Experimental methods used for the development of biocomposites involve the use of three types of cotton fabric of pore sizes 0.6 mm x 0.6 mm, 0.8 mm x 0.8 mm, and 1.0 mm x 1.0 mm with three different 3D printing pore sizes 0.5 mm x 0.5 mm, 1.0 mm x 1.0 and 1.5 mm x 1.5 mm. The development of biocomposites is found feasible. Breaking strength, percentage extension, and water absorption capacity increased in 3D printing pore sizes and pore wall width for each fabric. The maximum 235.40 N and minimum 123.20 N breaking strength, maximum 2.288 % and minimum 1.506 % extension, and maximum 7.63 % and minimum 3.57 % absorption capacity have been observed for the developed biocomposite. The behaviours of these biocomposites are adequate for healthcare applications and may be used as a bandage in wound healing. The present work is limited to the feasibility study of the unique biocomposite. Analysis of other properties and testing of biocomposite on animals and humans may be carried out in future work.

Management 4.0 assists businesses in evolving, surviving and performing in the competitive and dynamic world. This fourth revolution uses advanced technologies like Artificial Intelligence (AI), Virtual Reality (VR), Internet of Things (IoT), Robotics, Holography, Additive Manufacturing etc., for the proper management systems. These technologies facilitate working personnel and make it more appealing to complete their duties efficiently and accurately. The main aim of this paper is to understand the concept of Management 4.0, its technologies and applications for proper management systems. As Management 4.0 enhances process control, the chance of human error is reduced, leading to increased efficiency. It enables rapid and intelligent decision-making, reduces costs, accelerates growth, and raises profitability. Management 4.0 technologies and advanced data analytics are helpful to make smart supply chain management well suited to fulfil industry 4.0. Thus, to overcome various obstacles and effectively deploy Management 4.0 technologies in manufacturing industries, top management must establish a clear asset performance management plan with the help of process engineers familiar with industrial system failure occurrences and what operators need to improve. Management 4.0 involves advanced technologies, system connectivity, data collection & analysis at the organisation level. Management 4.0 is expected to be a critical component in the long-term survival of any business, either manufacturing or service-providing organisations. This paper explores the development of Management 4.0 and its dimensions and transformations through Management 4.0 perspectives. Finally, the significant role of Management 4.0 for appropriate private management system in manufacturing industries are identified. Organisations require a system that seamlessly meets the company's expectations, consumers, investors, and other stakeholders to remain competitive, and Management 4.0 will enable this. Many businesses strive to integrate technologies and upskill their personnel to adapt to the new job duties and attract more workers with the necessary abilities.

In today's power systems, performing demand response (DR) programs is considered a solution for sustainable operation, carbon reduction, and facilitating renewable energy integration. Currently in Iran, several DR programs are available to industrial customers. Moreover, the design of a market-based DR has recently been considered by the power system operator. In DR programs, customer baseline load (CBL) is used to determine the level of customers’ demand reduction and is key to the billing process; thus, the CBL calculation methodology can directly affect the efficiency of these programs. This paper investigates the current CBL calculation method in Iran's power system and, as its main contribution, proposes some effective methods to reduce the probable incentives for CBL manipulation. In order to show the effectiveness of the methods, a real study case is considered based on the historical load data of the industries in the Khorasan region.

The frequent occurrence of natural disasters caused by human activities and environmental pollution has forced people to pay attention to environmental protection. Of course, emergency rescue after natural disasters is also a great component of research. Emergency rescue often generates a large number of emergency evacuation and rescue traffic needs. In the face of scarce road resources, how to allocate limited road resources for emergency traffic needs reasonably to improve the efficiency of emergency rescue has important practical significance. This paper studies the emergency traffic distribution method and the traffic organization method of the emergency traffic network. First, on the basis of the existing traffic distribution method based on Logit model, combined with the characteristics of emergency traffic flow, an emergency multi-path traffic distributed method based on the second modified Logit model is proposed. As well as the emergency lane reversal implementation strategy is proposed according to the actual situation. Finally, an example is proposed to comprehensively verify the emergency traffic distribution method and emergency lane reversal strategy proposed in this paper. The experimental results show that the proposed method can cope with the complex scenarios of multiple emergency traffic flows and is helpful to improve the overall efficiency of emergency traffic flow.