Creating technological innovation via green supply chain management: An empirical analysis

This study sets out to empirically test the research framework and identify the relationship between green supply chain management (GSCM) practices and technological innovation (TI) in manufacturing firms. It is one of the first studies that experimentally validate the relationship between GSCM practices and TI from the perspective of a developing nation. In this study, 133 usable sets of data were collected from manufacturing firms in Malaysia. Results obtained from the partial least square-structural equation modeling (PLS-SEM) approach supported the significant positive relationship between three GSCM practices (i.e. internal environmental management, eco-design and investment recovery) and TI, but the study found that green purchasing and cooperation with customers do not have a significant positive correlation with TI. The importance of GSCM practices has been proven to enhance firms’ TI, in addition to improving the environment, bringing about a positive impact on the manufacturing establishment. Therefore, this study has relevance to all manufactures seeking to enhance their TI through the effective use of GSCM practices.     

Impact of Radio Frequency Identification Technology on Environmental Sustainability

This study is the first empirical investigation of the impact of Radio Frequency Identification (RFID) technology utilization on a manufacturing organization’s ability to implement environmental sustainability practices and the organization’s level of environmental performance. The purpose of the study is to investigate the relationships among RFID technology utilization, environmental sustainability practices, and environmental performance. A structural model depicting the impact (direct and indirect through green supply chain management practices) on environmental performance is theorized. The efficacy of the model is assessed using a Partial-Least-Squares structural equation modeling methodology based on data from a sample of manufacturing managers. The results suggest that RFID technology utilization is positively associated with green supply chain management practices and environmental performance. This study contributes to the understanding of the impact of a specific technology, RFID, on environmental sustainability. RFID technology utilization is established as a viable component of a manufacturing organization’s environmental sustainability strategy.     

A novel hybrid MCDM approach based on fuzzy DEMATEL, fuzzy ANP and fuzzy TOPSIS to evaluate green suppliers

It is well known that “green” principles and strategies have become vital for companies as the public awareness increased against their environmental impacts. A company’s environmental performance is not only related to the company’s inner environmental efforts, but also it is affected by the suppliers’ environmental performance and image. For industries, environmentally responsible manufacturing, return flows, and related processes require green supply chain (GSC) and accompanying suppliers with environmental/green competencies. During recent years, how to determine suitable and green suppliers in the supply chain has become a key strategic consideration. Therefore this paper examines GSC management (GSCM) and GSCM capability dimensions to propose an evaluation framework for green suppliers. However, the nature of supplier selection is a complex multi-criteria problem including both quantitative and qualitative factors which may be in conflict and may also be uncertain. The identified components are integrated into a novel hybrid fuzzy multiple criteria decision making (MCDM) model combines the fuzzy Decision Making Trial and Evaluation Laboratory Model (DEMATEL), the Analytical Network Process (ANP), and Technique for Order Performance by Similarity to Ideal Solution (TOPSIS) in a fuzzy context. A case study is proposed for green supplier evaluation in a specific company, namely Ford Otosan.     

Peas and carrots just because they are green? Operational fit between green supply chain management and green information system

Green supply chain management (GSCM) and green information system (GIS) are two strategic endeavors of external and internal orientations for the sustainable development of an organization. This study identifies the common dimensions between the two IT-enabled innovations in terms of environment protection, process control and organization support, and conceptualizes their operational fit. Compared with the commonly used perceived fit to measure how well IT infrastructure supports business activities, the operationalization of GSCM-GIS fit is based on both fit-as-profile-deviation and fit-as-moderation approaches to capture the synergy of GSCM and GIS practices along their common dimensions. Empirical evidence supports that operational fit as the result of functional deployment has expected long-term implications on environmental and social performances; whereas the implementation of both GSCM and GIS as the result of strategic planning has relatively short-term impacts on operational and economic performances.     

Do green supply chain management initiatives impact stock prices of firms?

Although firms have been taking green supply chain management (GSCM) initiatives, it is not known whether they create value for firms. We analyze 104 announcements related to GSCM using an event study, and determine what causes statistically significant gain in stock prices for these firms. Manufacturing firms, firms with high R&D expenses, and early adopters show a strong increase in stock prices on the day of the announcement. At the same time, small firms, firms not well-known for taking green initiatives, as well as firms that are low in growth potential considerably surprise the market when they make such announcements.     

An expert fuzzy rule-based system for closed-loop supply chain performance assessment in the automotive industry

Closed-loop supply chain management has been identified as an efficient, effective and economical strategy towards environmental sustainable practices in manufacturing companies. Without a formidable closed-loop supply chain to complement green supply chain management, most of the goals will not be achieved. A performance evaluation system is crucial for achieving a successful closed-loop supply chain in the automotive industry. Hence, a suitable expert fuzzy rule-based system for evaluation was developed in this study using Visual Basic.Net. The fuzzy rules and arithmetic used were described. The resulting performance measurement system was evaluated using a case study company from the automotive industry. The study culminated with recommendations and proposal of directions for future studies.     

锂离子电池剩余寿命预测方法研究综述

电池故障预测和健康管理(Prediction and Health Management, PHM)评价的主要方法是确定电池的健康状态和剩余使用寿命(Remaining Useful Life, RUL),以此保证锂离子电池安全可靠地工作和实现寿命优化。锂电池RUL预测不仅是PHM中的热点问题和挑战问题,其预测方法的准确性也会直接影响电池管理系统(Battery Management System, BMS)的整体性能。介绍了单体电芯测评标准,对影响锂电池循环寿命的主要因素进行详细分析。简述电池日历寿命和循环寿命。概括和总结了近几年锂离子电池剩余寿命预测方法,比较不同方法的优缺点。提出了当前实际应用中预测锂电池RUL仍存在的关键问题并进行探讨。     

Logistics supply chain information collaboration based on FPGA and internet of things system

The contribution of logistics in the supply chain and, at the same time, researchers and practitioners have recognized a new trend of supply chain integration and collaboration over the past two decades. This philosophy is known as supply chain management and has attracted extensive attention in logistics Development. In the existing method Deep Learning and Neural network for Logistics Supply Chain Information Collaboration. In the existing method large complexity of structure and Hard to maintain version control. So in the proposed method FPGA (Field-Programmable Gate Array) and IOT (Internet of Things) for Logistics Supply Chain Information Collaboration. The logistics Cooperation based on supply chain management reduces overall costs while improving services to end customers in the supply chain. Global progress, rapid innovation and growing regional influence have made the Supply Chain (SC) an indispensable part. Competition is now changing from the company level to the industry level. The data not only destroys the organization, but it also affects the industry as a whole supply unit. The industrial sector supports more than half of the population, and the automotive sector is the fastest-growing sector. Supply chain cooperation reduces the performance of different industries and different regions.     

Eco-friendly additive manufacturing of metals: Energy efficiency and life cycle analysis

Additive manufacturing (AM) of metal materials has attracted widespread attention and is shifting the conventional manufacturing landscape toward free-form processes. With increasing concerns about global sustainability, eco-consideration is highly encouraged to be integrated into AM processes. This review provides a comprehensive and timely discussion on the life cycle of metal parts fabricated through AM. The energy consumption required for raw metal material extraction and subsequent AM processes is analyzed. The eco-design and energy efficiency of metal AM are evaluated to reveal the role of manufacturing methods, machine subsystems, and post-processing modes in the eco-integration. AM-induced supply chain management, utilization, and recycling of the printed metal structure are also analyzed. Finally, a comprehensive life cycle assessment regarding the environmental, social, and economic impacts of metal AM is also addressed. Future directions of AM are also briefly discussed to provide insight and vision on the emerging field of additive eco-manufacturing.     

Close-loop or open hierarchical structures in green supply chain management under uncertainty

This study aims to explore the differences between close-loop and open hierarchical structures, which are used in the analytical network process (ANP) analysis of green supply chain management (GSCM) under uncertainty. Specifically, this study examines the interdependence among the proposed aspects and criteria used to assess GSCM in two hierarchical structures and compares these results to those of a real situation. Additionally, the aspects and criteria involve qualitative preferences in GSCM evaluation. Hence, this study proposes to use both hybrid fuzzy set theory and ANP methods. Examining two types of hierarchical structure provides the ability to examine study problems that have similar aspects and criteria with respect to situations that occur in GSCM. This study argues that while many of the commonly employed close-loop and open hierarchical structures display numerous worthwhile operational processes, further refinement of the criteria and methods are needed to improve the field. The results indicate that the close-loop hierarchical structure more closely resembles existing applications. The managerial implications of this result are discussed, and concluding remarks are provided.     

A cooperative advertising collaboration policy in supply chain management under uncertain conditions

Many industries are facing big challenges to design supply chains in a way to maximize the profit and meet the heightened expectations of the customer. This new era entirely relies on the dynamic advantages of competition and the role played by the collaboration policy. A global economy and increasing demand have put a huge pressure on supply chain partners to build a collaboration policy based on price, order quantity, and advertising. Companies are adopting the idea of ”shaking hands” to obtain more profit instead of taking risks through competition. Cooperative (co-op) advertising is a significant policy of centralized supply chain management (SCM) to boost the revenues generated by the supplier, manufacturer, and retailers. The uncertain costs associated with the supply chain management also create obstacles in economic analysis and feasibility. These uncertainties are associated with the basic costs of all supply chain partners, which are represented using a signed distance formula. This paper develops the concept of co-op advertising among the supplier, manufacturer, and retailers with a variable demand driven by selling price and advertising costs, where all basic costs are considered as fuzzy. The profit is optimized by considering variable cycle time, shipments, pricing and advertising costs for the decision support system of the supply chain management. The optimal results of the co-op advertisement ensured an increase in the revenue of whole supply chain.     

食品分销网络弹性设计与公平关切行为研究

研究了竞争型供应链弹性网络设计中的行为运作问题,首先建立了集产品制造成本/仓库运营成本/易腐品配送成本/网络节点选择/零售商公平厌恶成本于一体的整体配送框架。利用供应链背景下的一般运作模型,建立了弹性管理下的竞争型多源网络。考虑多源弹性供应网络下各级分销商失效的潜在风险,并分析了零售商公平厌恶下的消极影响。最后考察了一定水平的期望容忍条件、全球供应链和公平关切对于目标函数、正向架构的弹性运作和供应链成员的影响。     

The construction of a collaborative framework in support of low carbon product design

Ideally, carbon information could be disclosed and reduced through the supply chain if a life cycle inventory is well conducted. However, in practice, it has been found through the observation of the past carbon footprint inventories of enterprises that owing to the limited cost and resources, most of these investigations were seldom comprehensively conducted and were not integrated with the existing internal management systems or information systems of the enterprises, but instead were conducted as a special project for target products. Also, most enterprises thought it was time-consuming to conduct these inventories (raw material suppliers, manufacturers, transporters, retailers, customers, and waste processors, numerous suppliers). The main purpose of this study is to construct a collaborative design framework to help enterprises collect and calculate products' carbon footprints in a readily and timely manner throughout the entire supply chain. In this research, a computer aided tool was used to integrate enterprises' internal systems with life cycle inventory database and to establish enterprises' GHGs bills of material system. These enterprises were provided with standard data collection forms and a search engine system based on life cycle assessment approaches. A case study on the implementation of the system is also illustrated.     

Towards Long Lifetime Battery: AI-Based Manufacturing and Management

Technologies that accelerate the delivery of reliable battery-based energy storage will not only contribute to decarbonization such as transportation electrification, smart grid, but also strengthen the battery supply chain. As battery inevitably ages with time, losing its capacity to store charge and deliver it efficiently. This directly affects battery safety and efficiency, making related health management necessary. Recent advancements in automation science and engineering raised interest in AI-based solutions to prolong battery lifetime from both manufacturing and management perspectives. This paper aims at presenting a critical review of the state-of-the-art AI-based manufacturing and management strategies towards long lifetime battery. First, AI-based battery manufacturing and smart battery to benefit battery health are showcased. Then the most adopted AI solutions for battery life diagnostic including state-of-health estimation and ageing prediction are reviewed with a discussion of their advantages and drawbacks. Efforts through designing suitable AI solutions to enhance battery longevity are also presented. Finally, the main challenges involved and potential strategies in this field are suggested. This work will inform insights into the feasible, advanced AI for the health-conscious manufacturing, control and optimization of battery on different technology readiness levels.      

面向全生命周期的项目管理系统分析与设计

针对传统项目管理以规划执行为中心而忽视投标和客户反馈的问题,引入了全生命周期的概念,形成了基于Web的项目管理系统。提出了组织和过程分离的工作模式,为人员／企业的灵活组织提供了支持,从而为面向动态联盟的虚拟企业供应链的组织奠定了基础。针对项目中的文档管理问题,提出了基于权限管理的解决方案。面向全生命周期的项目管理系统包括了投标、执行和客户反馈等内容,具有良好的柔性和可扩展性。     

A roadmap for a methodology to assess,improve and sustain intra‐ and inter‐enterprise system performance with respect to technology‐product life cycle in small and medium manufacturers

Increased manufacturing costs are forcing U.S. manufacturing firms to send their operations off shore. Such business practices are greatly impacting the vitality of small and medium manufacturers (SMMs) in the U.S. economy. This article intends to advance the notion of the need for a methodology for assessment, improvement, and sustainability of intra‐ and inter‐enterprise system performance along the technology–product development life cycle. The aims of this article are to: (1) provide an overview of the technology–product development process; (2) document the different states of manufacturing technology readiness levels; (3) present an overview of prior methodologies reported on the subject in the published literature; and (4) establish a road map for assessment, improvement, and sustainability of intra‐ and inter‐enterprise system performance along the path of the technology–product development life cycle. A notion is advanced about the readiness of SMMs with respect to assessment, improvement, and sustainability of intra‐ and inter‐enterprise system performance. A road map is outlined for the deployment of a methodology to address the issues across the supply chain. © 2007 Wiley Periodicals, Inc.     

闭环供应链混合切换库存控制模型研究

针对一类具有回收、再制造、再分销的闭环供应链系统,以再制造产品的补货能力为切换信号设计了基于再制造优先的混合切换库存控制策略,使得市场需求优先由再制造产品满足,并应用切换控制理论研究混合切换库存控制策略的性能特征,分析系统参数对闭环供应链系统的关键性能指标的影响。仿真分析表明,合理的切换控制策略可以有效抑制闭环供应链运作过程的波动,保证系统具有良好的“牛鞭效应”特征、平稳的库存管理成本以及较高的顾客服务水平。     

供应链间竞争下绿色广告决策研究

通过构建两条供应链中的零售商横向竞争和制造商横向竞争模型研究分散和集中两种决策下的绿色广告决策问题,分析绿色广告成本系数和绿色广告敏感系数对绿色广告效应以及供应链成员利润的影响。研究结果表明：集中式供应链绿色广告效应更大;绿色广告成本系数较小时会对供应链成员利润产生显著影响且微小变动会引起需求市场剧烈变动;集中式决策下绿色产品供应链优势明显,而普通产品供应链的决策方式受绿色广告效应敏感系数的影响。     

A closed-loop logistic model with a spanning-tree based genetic algorithm

Due to the problem of global warming, the green supply chain management, in particular, closed-loop logistics, has drawn the attention of researchers. Although there were logistics models that were examined in the literatures, most of them were case based and not in a closed-loop. Therefore, they lacked generality and could not serve the purposes of recycling, reuse and recovery required in a green supply chain. In this study, the integration of forward and reverse logistics was investigated, and a generalized closed-loop model for the logistics planning was proposed by formulating a cyclic logistics network problem into an integer linear programming model. Moreover, the decisions for selecting the places of manufactories, distribution centers, and dismantlers with the respective operation units were supported with the minimum cost. A revised spanning-tree based genetic algorithm was also developed by using determinant encoding representation for solving this NP model. Numerical experiments were presented, and the results showed that the proposed model and algorithms were able to support the logistic decisions in a closed-loop supply chain efficiently and accurately.

Statement of scope and purposes

This study concerns with operations of 3R in the green supply chain logistics and the location selection optimization. Based on ‘cradle to cradle’ principle of a green product, a “closed-loop” structure of a network was proposed in order to integrate the environmental issues into a traditional logistic system. Due to NP-hard nature of the model, a Genetic Algorithm, which is based on spanning tree structure was developed. Test problems from the small size for accuracy to the large scale for efficiency have been demonstrated with comparison. The promising results have shown the applicability of the proposed model with the solution procedure.     

Application of an artificial immune system-based fuzzy neural network to a RFID-based positioning system

Due to the rapid development of globalization, which makes supply chain management more complicated, more companies are applying radio frequency identification (RFID), in warehouse management. The obvious advantages of RFID are its ability to scan at high-speed, its penetration and memory. In addition to recycling, use of a RFID system can also reduce business costs, by indentifying the position of goods and picking carts. This study proposes an artificial immune system (AIS)-based fuzzy neural network (FNN), to learn the relationship between the RFID signals and the picking cart’s position. Since the proposed network has the merits of both AIS and FNN, it is able to avoid falling into the local optimum and possesses a learning capability. The results of the evaluation of the model show that the proposed AIS-based FNN really can predict the picking cart position more precisely than conventional FNN and, unlike an artificial neural network, it is much easier to interpret the training results, since they are in the form of fuzzy IF–THEN rules.