Sustainability

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19 pages, 554 KiB

Open AccessArticle

Anti-Counterfeiting and Traceability Consensus Algorithm Based on Weightage to Contributors in a Food Supply Chain of Industry 4.0

by Ji Tan, S. B. Goyal, Anand Singh Rajawat, Tony Jan, Neda Azizi and Mukesh Prasad

Sustainability 2023, 15(10), 7855; https://doi.org/10.3390/su15107855 - 11 May 2023

Cited by 3 | Viewed by 2027

Abstract

Supply chain management can significantly benefit from contemporary technologies. Among these technologies, blockchain is considered suitable for anti-counterfeiting and traceability applications due to its openness, decentralization, anonymity, and other characteristics. This article introduces different types of blockchains and standard algorithms used in blockchain [...] Read more.

Supply chain management can significantly benefit from contemporary technologies. Among these technologies, blockchain is considered suitable for anti-counterfeiting and traceability applications due to its openness, decentralization, anonymity, and other characteristics. This article introduces different types of blockchains and standard algorithms used in blockchain technology and discusses their advantages and disadvantages. To improve the work efficiency of anti-counterfeiting traceability systems in supply chains and reduce their energy consumption, this paper proposes a model based on the practical Byzantine fault tolerance (PBFT) algorithm of alliance chains. This model uses a credit evaluation system to select the primary node and integrates the weightage to contributors (WtC) algorithm based on the consensus mechanism. This model can reduce the decline in the algorithm success rate while increasing the number of malicious transaction nodes, thereby reducing the computing cost. Additionally, the throughput of the algorithmic system increases rapidly, reaching approximately 680 transactions per second (TPS) in about 120 min after the malicious nodes are eliminated. The throughput rapidly increases as the blacklist mechanism reduces the number of malicious nodes, which improves the system’s fault tolerance. To validate the effectiveness of the proposed model, a case study was conducted using data from the anti-counterfeiting traceability system of the real-life supply chain of a food company. The analysis results show that after a period of stable operation of the WtCPBFT algorithm in the proposed model, the overall communication cost of the system was reduced, the throughput and stability were improved, and the fault-tolerant performance of the system was improved. In conclusion, this paper presents a novel model that utilizes the PBFT algorithm of alliance chains and the WtC algorithm to improve the efficiency and security of anti-counterfeiting traceability systems in supply chains. The results of the case study indicate that this model can effectively reduce communication costs, improve throughput and stability, and enhance the fault tolerance of the system. Full article

(This article belongs to the Special Issue Innovation and Sustainability in New Product Development and Supply Chain)

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18 pages, 629 KiB

Open AccessArticle

A Data-Driven Approach for Improving Sustainable Product Development

by Marcin Relich

Sustainability 2023, 15(8), 6736; https://doi.org/10.3390/su15086736 - 17 Apr 2023

Cited by 6 | Viewed by 2134

Abstract

A product’s impact on environmental issues in its complete life cycle is significantly determined by decisions taken during product development. Thus, it is of vital importance to integrate a sustainability perspective in methods and tools for product development. The paper aims at the [...] Read more.

A product’s impact on environmental issues in its complete life cycle is significantly determined by decisions taken during product development. Thus, it is of vital importance to integrate a sustainability perspective in methods and tools for product development. The paper aims at the development of a method based on a data-driven approach, which is dedicated to identifying opportunities for improving product sustainability at the design stage. The proposed method consists of two main parts: predictive analytics and simulations. Predictive analytics use parametric models to identify relationships within product sustainability. In turn, simulations are performed using a constraint programming technique, which enables the identification of all possible solutions (if there are any) to a constraint satisfaction problem. These solutions support R&D specialists in finding improvement opportunities for eco-design related to reducing harmful impacts on the environment in the manufacturing, product use, and post-use stages. The results indicate that constraint-satisfaction modeling is a pertinent framework for searching for admissible changes at the design stage to improve sustainable product development within the full scope of socio-ecological sustainability. The applicability of the proposed approach is verified through an illustrative example which refers to reducing the number of defective products and quantity of energy consumption. Full article

(This article belongs to the Special Issue Innovation and Sustainability in New Product Development and Supply Chain)

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20 pages, 5567 KiB

Open AccessArticle

An Energy-Saving Regulation Framework of Central Air Conditioning Based on Cloud–Edge–Device Architecture

by Guofu Luo, Tianxing Sun, Haoqi Wang, Hao Li, Jiaqi Wang, Zhuang Miao, Honglei Si, Fuliang Che and Gen Liu

Sustainability 2023, 15(3), 2554; https://doi.org/10.3390/su15032554 - 31 Jan 2023

Viewed by 1749

Abstract

As energy plays a fundamental role in our modern life and most of a building’s energy is used for air conditioning, understanding the sustainable regulation theory of central air conditioning remains a significant scientific issue. In view of three shortcomings of existing energy-saving [...] Read more.

As energy plays a fundamental role in our modern life and most of a building’s energy is used for air conditioning, understanding the sustainable regulation theory of central air conditioning remains a significant scientific issue. In view of three shortcomings of existing energy-saving regulation methods of central air conditioning: (1) few studies on low-latency, high-reliability, and safer energy-saving control operation modes, (2) lack of consideration for human comfort, and (3) insufficient analysis of the comprehensive impact of the human–machine–environment, this paper proposes an energy-saving control framework of central air conditioning based on cloud–edge–device architecture. The framework establishes a prediction model of human comfort based on recurrent neural network. An intelligent energy-saving control strategy is proposed to ensure indoor personnel’s thermal comfort, considering the human–machine–environment factors. This study provides a basis for better understanding the sustainable control theory of building central air conditioning. Finally, the experiment proves that the proposed method can effectively reduce the energy consumption of central air conditioning. Compared with traditional regulation approaches, the proposed real-time control strategy can save up to 91% of energy consumption, depending on the environment, and advance control strategies can save an average of 4%. Full article

(This article belongs to the Special Issue Innovation and Sustainability in New Product Development and Supply Chain)

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18 pages, 517 KiB

Open AccessArticle

The Impact of Supply Chain Integration on Operational Performance: An Empirical Study

by Ra’ed Masa’deh, Ismail Muheisen, Bader Obeidat and Ashraf Bany Mohammad

Sustainability 2022, 14(24), 16634; https://doi.org/10.3390/su142416634 - 12 Dec 2022

Cited by 2 | Viewed by 5024

Abstract

Manufacturing companies nowadays are under constant pressure to deliver high-quality products at the lowest possible prices within the shortest possible time even under the most unpredictable economic situations. Supply chain integration has a critical impact on operational performance. Nevertheless, this impact has not [...] Read more.

Manufacturing companies nowadays are under constant pressure to deliver high-quality products at the lowest possible prices within the shortest possible time even under the most unpredictable economic situations. Supply chain integration has a critical impact on operational performance. Nevertheless, this impact has not been consistent and showed mixed results throughout the literature. This study aimed to examine the impact of technology management in terms of supply chain integration on operational performance. The research model was empirically validated using 317 valid survey responses from the Jordanian food and beverage industry, which were subjected to quantitative research design and regression analysis. Results showed that supply chain integration had a direct significant impact on operational performance, and all three dimensions of the theoretical model contributed significantly to operational performance. This study suggests the critical need to create and implement proper supply chain integration strategies and technologies, both internally and externally, to enhance their performance and competitive advantage. Moreover, future research needs to extend this work to other industries, cultures, and nations, while investigating the moderating or mediating effects of other key variables along with using alternative sampling strategies. Full article

(This article belongs to the Special Issue Innovation and Sustainability in New Product Development and Supply Chain)

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19 pages, 1974 KiB

Open AccessArticle

Green Supply Chain Operations Decision and Government Subsidy Strategies under R & D Failure Risk

by Wenli Wang and Ruizhen Zhang

Sustainability 2022, 14(22), 15307; https://doi.org/10.3390/su142215307 - 17 Nov 2022

Cited by 3 | Viewed by 1254

Abstract

The behavior of enterprises upgrading green technology presents a certain risk of failure. In this paper, the probability of R & D failure that is not considered in most articles is introduced into the model, and the supply chain composed of green product [...] Read more.

The behavior of enterprises upgrading green technology presents a certain risk of failure. In this paper, the probability of R & D failure that is not considered in most articles is introduced into the model, and the supply chain composed of green product manufacturers and retailers is considered. The optimal operation decision of the green supply chain under the two modes of government subsidizing manufacturers’ R & D costs and subsidizing green product production costs is analyzed. Under the same subsidy expenditure, this study examines which subsidy method can maximize social welfare. The results show that, when the production cost of green products developed by manufacturers is high, if the government budget is low, the production cost of green products shall be subsidized; if the government budget is high, the manufacturer’s R & D cost should be judged. If the R & D cost is high, the production cost of green products should be subsidized to encourage retailers to order more green products. However, if the R & D cost is low, the R & D cost of green products should be subsidized to encourage manufacturers to invest the most in R & D. When the production cost of green products developed by manufacturers is low, the production cost of green products should be subsidized no matter the R & D cost of manufacturers. Additionally the conclusion has been verified by the actual case. Full article

(This article belongs to the Special Issue Innovation and Sustainability in New Product Development and Supply Chain)

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16 pages, 2763 KiB

Open AccessArticle

Assessing the Private Sector’s Efforts in Improving the Supply Chain of Hermetic Bags in East Africa

by Oluwatoba J. Omotilewa and Dieudonne Baributsa

Sustainability 2022, 14(19), 12579; https://doi.org/10.3390/su141912579 - 3 Oct 2022

Viewed by 1278

Abstract

Hermetic bags are effective at curbing grain losses due to insect pests, but their use remains low due to unavailability among smallholder farmers. This study used primary data from actors within the Purdue Improved Crop Storage (PICS) supply chain network, mostly the private [...] Read more.

Hermetic bags are effective at curbing grain losses due to insect pests, but their use remains low due to unavailability among smallholder farmers. This study used primary data from actors within the Purdue Improved Crop Storage (PICS) supply chain network, mostly the private sector, in Ethiopia, Tanzania, and Uganda, to understand the challenges and opportunities in improving the availability of hermetic bags in rural areas. It finds that supply-side distribution approaches played a critical role in improving PICS bag availability. Some of the supply-side constraints included poor inventory management, pricing, and limited access to capital. Inventory management can be improved through better forecasting using sales records and prediction of farmers’ harvests. Improved access to credit during peak season can improve the timely supply and reduce stockouts. Marketing inefficiency appears to be fueled by a high-profit margin at the distributor level. Using all available distribution channels in addition to ag-input dealers will enhance the availability of the bags in rural communities. Full article

(This article belongs to the Special Issue Innovation and Sustainability in New Product Development and Supply Chain)

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23 pages, 1159 KiB

Open AccessArticle

A Hesitant Fuzzy Method for Evaluating Risky Cold Chain Suppliers Based on an Improved TODIM

by Yongzheng Zhang, Chunming Ye and Xiuli Geng

Sustainability 2022, 14(16), 10152; https://doi.org/10.3390/su141610152 - 16 Aug 2022

Cited by 4 | Viewed by 1138

Abstract

Enterprises need sustainable development in order to reduce costs and increase income. The cold chain logistics industry needs to promote sustainable supply chains more. As the beginning of the supply chain, the choice of suppliers is particularly important. Considering the risky attitude of [...] Read more.

Enterprises need sustainable development in order to reduce costs and increase income. The cold chain logistics industry needs to promote sustainable supply chains more. As the beginning of the supply chain, the choice of suppliers is particularly important. Considering the risky attitude of decision-makers, an improved hesitant fuzzy TODIM approach is adopted to select suppliers. In order to calculate a more objective indicator weight, the generalized Shapley function of the hesitant fuzzy measure is adopted by analyzing the relationships among indicators. The uncertain supplier evaluation information given by decision-makers is obtained by using hesitant fuzzy information. The improved Interactive and Multi-criteria Decision-Making (TODIM) method based on hesitant fuzzy numbers is used to analyze the psychological behavior of decision-makers under different market prospects and comprehensively rank the candidate suppliers. Finally, a case study of selecting cold chain logistics suppliers is provided to verify the effectiveness and feasibility of the method in this paper. Full article

(This article belongs to the Special Issue Innovation and Sustainability in New Product Development and Supply Chain)

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21 pages, 3817 KiB

Open AccessArticle

A Novel Sustainable Processing Mode for Burr Classified Prediction of Weak Rigid Drilling Process Using a Fusion Modeling Method

by Siyi Ding, Xiaohu Zheng, Mingyu Wu and Qirui Yang

Sustainability 2022, 14(12), 7429; https://doi.org/10.3390/su14127429 - 17 Jun 2022

Cited by 4 | Viewed by 1605

Abstract

Weakly rigid drilling systems, such as the industrial robot, are widely used in aerospace, military, and other fields due to its good flexibility and large scope of operation. However, the weak rigidity can easily cause burrs, seriously affecting the precision of parts and [...] Read more.

Weakly rigid drilling systems, such as the industrial robot, are widely used in aerospace, military, and other fields due to its good flexibility and large scope of operation. However, the weak rigidity can easily cause burrs, seriously affecting the precision of parts and product performance. To reduce the heavy deburring process and to improve continuous production and sustainable processing capacity, accurate prediction of burr quality is a prerequisite. Traditional burr forming theory cannot accurately predict the drilling defects. Data-driven approaches can be independent of prior knowledge and discover relationships between process parameters and machining precision directly from the data structure itself. Therefore, to take advantage of both approaches, a fusion model was established for burr classified prediction. On the one hand, the drilling and burr forming process was firstly modeled, and preliminary classification results for burrs were calculated. On the other hand, according to the measured data, the errors between initial calculation results and actual classification results were obtained and selected as the tag values of dataset, which served as inputs for the error compensation model of burrs. Finally, by training the network of TCN–DNN using the drilling data, the burr classified prediction in a weak rigid hole-making system was realized. Experimental results showed that compared with traditional drilling theory, the prediction accuracy of the proposed model improved by 25%, reaching 91.67%. The results can provide a basis for judging the process of burr post-treatment, which has practical guiding significance. This method is beneficial to reduce the heavy deburring process and to improve sustainable processing capacity. Full article

(This article belongs to the Special Issue Innovation and Sustainability in New Product Development and Supply Chain)

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