An integrated modelling approach for raw material management in a steel mill

An integrated modelling approach combining optimisation models with simulation is proposed for coordinated raw material management at steel works throughout the whole supply chain management process. The integrated model is composed of three components: ship scheduling, yard operation simulation and material blending models. The ship scheduling model determines which brands, how much and when they should be arrived, and the problem is modelled as mixed integer linear programming. The simulation model is used to simulate the whole processes from ships’ arrivals to the retrieval of the materials through the berthing and unloading the raw materials. Finally, the raw material blending model is developed for determining the brand and quantity of raw materials to be used. The proposed integrated modelling approach for raw material management has been successfully implemented and applied at steelwork to provide shipping schedules and predict future inventory levels at stock yards. By coordinating all the activities throughout the entire raw material supply chain management process, this article proposes an integrated approach to the problem and suggests a guideline by the appropriate simplification. The quantitative nature of the optimisation model and simulation facilitates an assessment of the risk factors in the supply chain, leading to an evaluation of a wide variety of scenarios and the development of multiple contingency plans. Further research is expected to supplement the ship scheduling models with heuristics for the idiosyncratic constraints of maritime transportation.     

Literature review: Strategic network optimization models in waste reverse supply chains

In scientific literature two large, partly overlapping areas regarding the environmental and economical attractive removal of waste coexist: reverse logistics and waste management. Both fields study, among other topics, the flows of discarded products leaving the end consumer. This review takes an integrated point of view on reverse logistics and waste management and aims at a better integration. More specifically, it gives a concise but complete overview of the efforts already performed in the area of strategic network design in waste reverse supply chains by means of combinatorial optimization models. Its purpose is to guide interested readers and researchers directly to publications of their interest, and let them identify courses other than the well-worn paths. Among others, we explicitly refer to (1) the importance of environmental, social and performance indicators in multi-objective models, (2) the potential of incorporating the different waste reverse supply chain stakeholders into the network design model, (3) the consideration of future waste reverse supply chain developments like extended producer responsibility schemes and the circular economy and their challenges, and (4) better heuristics to deal with the increasingly complex strategic network design models.     

A PRACTICAL SETTING FOR EXPERIENTIAL LEARNING ABOUT SUPPLY CHAINS: SIEMENS BRIEF CASE GAME SUPPLY CHAIN SIMULATOR

Siemens Brief Case Game Supply Chain Simulator provides a practical setting for experiential learning exercises about supply chains. The game, drawing upon an actual situation, models the jobs of nine supply chain activities required to transform an order placed by the customer into a delivered product. Using the detail and complexity of the game, instructors can develop learning exercises that focus on a wide range of supply chain management issues. This paper describes two learning exercises with different objectives and for different audiences that we successfully delivered using the Brief Case Game. One exercise provides a concrete example of typical activities in a supply chain and their interactions. The other exercise leads students to discover what creates a need for coordination, what activities in a supply chain require coordination, and what methods work well. These exercises are suited for small upper level undergraduate and graduate courses in logistics and supply chain management. While significant resources were used to develop exercises and deliver the game, students were enthusiastic about the approach and demonstrated that they learned about the complexity inherent in managing supply chains.     

Decision knowledge sharing: flexible supply chains in KM context

Supply chain excellence has a real impact on business strategy. Building supply chains as flexible systems represents one of the most exciting opportunities to create value and one of the most challenging tasks for the policy makers. It requires integrated decision making amongst autonomous chain partners with effective decision knowledge sharing between them. The key to success lies in knowing which decision has more impact on the overall performance and this can be achieved by appropriate knowledge sharing. In this context, knowledge management (KM) can be used as an effective approach to achieve knowledge sharing and decision synchronisation in supply chains. Flexible supply chains (FSC_s) are more complex and involve multiple autonomous players with varying technical cultures (affects knowledge mindsets), managerial background (affects decision knowledge) and supply chain management (SCM) exposures (affects knowledge sharing attitudes). Thus there is a need to develop demo models that can encourage chain managers towards collaborative knowledge sharing in the supply chains. This paper presents the application of one such model based on decision knowledge sharing (DKS) for improved supply chain management. A simulation model of a flexible supply chain based on DKS framework is developed for demo purposes. The key results are highlighted along with industry implications. The cost based performance of DKS at different levels of flexibility is studied. Thus a careful analysis of the chain with a focus on collaborative decisions is useful to ensure success. This paper addresses this interesting and challenging domain.     

Scrutinising the interplay between governance and resilience in supply chain management: A systems thinking framework

Supply chain disruptions recurrently challenge end-to-end operations owing to the ambiguous understanding of the role of governance in impacting supply network resilience. This paper scrutinises the relevant literature to understand the plethora of interpretations in supply chain governance and resilience while further providing a new perspective on the representation of the interplay between governance and resilience in supply chains. In this regard, the Systems Thinking lens is adopted to pull together the typologies and constructs of supply chain governance and resilience from the literature. Methodologically, System Dynamics modelling principles are leveraged to capture the underpinning structural interdependencies in a causal loop diagram. The study reveals that endogenous and exogenous supply chain governance processes and mechanisms support the intrinsic and extrinsic resilience in networks. Overall, this research contributes to the supply chain risk management domain by synthesising the interplay between governance and resilience, identifying pertinent typologies, and articulating research propositions that can inform decision-making at policy and management levels.     

Partner selection in agile supply chains: a fuzzy intelligent approach

Partner selection is a fundamental issue in supply chain management as it contributes significantly to overall supply chain performance. However, such decision-making is problematic due to the need to consider both tangible and intangible factors, which cause vagueness, ambiguity and complexity. This paper proposes a new fuzzy intelligent approach for partner selection in agile supply chains by using fuzzy set theory in combination with radial basis function artificial neural network. Using these two approaches in combination enables the model to classify potential partners in the qualification phase of partner selection efficiently and effectively using very large amounts of both qualitative and quantitative data. The paper includes a worked empirical application of the model with data from 84 representative companies within the Chinese electrical components and equipment industry, to demonstrate its suitability for helping organisational decision-makers in partner selection.     

A hybrid approach to the study of CPFR implementation enablers

Collaborative planning, forecasting and replenishment (CPFR) is one of the most important but also one of the most difficult collaborative strategies in supply chain management. CPFR has been well documented in past research as providing significant benefit to those that implement it well. It has also been noted that CPFR uptake has been significantly lower than initially expected. The main reason for this slow uptake is the general recognition that successful implementation of CPFR is not a trivial task and the fact that it inflicts dramatic changes to the ‘usual’ way of doing business. Based on the premise that CPFR has significant positive potential for supply chain collaboration, the motivation of this paper is to review CPFR enablers and to develop a model which addresses the most significant ones. To complete this task, a hybrid modelling approach integrating fuzzy extended analytical hierarchy process and interpretive structural modelling is proposed. The model developed is based on an identified gap by the automotive sector and embeds expert opinion, from two separate industrial groups in the automotive sector through the use of workshops. Although potential success factors for CPFR implementation can vary across somewhat between differing supply chains, the results maintain wider general applicability due to the many common issues across sectors. The paper highlights the need for decision-makers to be aware of the most influential enablers prior to a CPFR implementation project and to understand the relationships between these enablers.     

A knowledge chain management framework to support integrated decisions in global supply chains

Knowledge management has been identified as a key enabler to achieve organisation’s value chain competitiveness. It, however, has been facing fresh challenges in a global supply chain setting. This paper proposes a global knowledge chain management (GKCM) framework that identifies and prioritises critical knowledge that a global supply chain can focus on to support integrated decisions. The framework explores three types of global context knowledge, namely global market knowledge, global capacity knowledge and global supply network configuration knowledge. Empirical study has been undertaken within the manufacturing industry to evaluate the GKCM framework. Analytic network process has been explored as a key method to assess the importance of the global knowledge constructs from supply chain managers’ perspectives. A key contribution of the paper is that it advances existing knowledge chain management approaches within one organisation and its local supply chain to include the global context knowledge applicable to global manufacturing settings, and highlights how the GKCM framework can support global supply chain integrated decisions.     

Managing channel profits of different cooperative models in closed-loop supply chains

The importance of closed-loop supply chains has been widely recognized in literature and in practice. The paper investigates interactions among the different parties in a three-echelon closed-loop supply chain consisting of a single manufacturer, a single retailer and two recyclers and focuses on how cooperative strategies affect closed-loop supply chain decision-making. Various cooperative models are considered by observing recent research and current cases, and the optimal decisions and supply chain profits of these models are discussed. By comparing various coalition structures, we discover that cooperative strategies can lead to win–win outcomes and increase an alliance׳s profit and can be effective ways of achieving greater efficiency from the point of view of the overall supply chain. Finally, the paper presents a detailed comparative analysis of these models and provides insights into the management of closed-loop supply chains.     

An integrated model of supply chain performance evaluation and decision-making using structural equation modelling and fuzzy AHP

This paper aims to propose a comprehensive evaluation tool and decision model, which can help the practitioners to gauge their supply chain performance and guide them in decision-making for further improvements. The model provides a salient notion of integrated supply chain performance evaluation approach distilled from the literature. The five important performance evaluation criteria (supply chain planning performance, supply chain partnership performance, production performance, delivery and logistic performance and customer service and satisfaction performance) and corresponding 19 sub-criteria have been identified. An integrated methodology of structural equation modelling (SEM) and fuzzy analytic hierarchy process (FAHP) have been applied to the proposed model to a real case study of Indian textile–apparel–retail supply chain network.     

Operations Risk Management: Overview of Paul Kleindorfer's Contributions

This paper reviews Paul Kleindorfer's contributions to Operations Management (OM), with a special focus on his research on risk management. An annotated bibliography of selected other contributions reviews the breadth of topics that have occupied Kleindorfer's research attention over his now 45 + years of research. These include optimal control theory, scheduling theory, decision sciences, investment planning and peak load pricing, plus a number of important applications in network industries and insurance. In the area of operations risk management, we review recent work that Kleindorfer and his colleagues in the Wharton Risk Center have undertaken on environmental management and operations, focusing on process safety and environmental risks in the chemical industry. This work is directly related to Kleindorfer's work in the broader area of “sustainable operations”, which he, Kal Singhal and Luk Van Wassenhove recently surveyed as part of the new initiative at POMS to encompass sustainable management practices within the POMS community. Continuing in the area of supply chain risks, the paper reviews Kleindorfer's contributions to the development of an integrated framework for contracting and risk hedging for supply management. The emphasis on alignment of pricing, performance and risk management in this framework is presaged in the work undertaken by Kleindorfer and his co‐authors in the 1980s on after‐sales support services for high‐technology products. This work on supply chain risk, and its successors, is reviewed here in light of its growing importance in managing the unbundled and global supply chains characteristic of the new economy.     

Honoring complexity in sustainable supply chain research: a rough set theoretic approach (SI:ResMeth)

Abstract

Sustainable supply chain management (SSCM) faces greater complexity because it considers additional stakeholder requirements, broader sustainable performance objectives, increased sustainable business practices and technologies, and relationships among those entities. These additional complexities make SSCM more difficult to manage and operate than traditional supply chains. Complex systems require new methods for research especially given reductionist research paradigms of modern science. Rough set theory (RST) can be a valuable tool that will help address complexity in SSCM research and practice. To exemplify RST usefulness and applicability, an illustrative application using sustainable supply chain practices (SSCP), and environmental and economic performance outcomes is introduced. The conceptual case provides nuanced insights for researchers and practitioners in mitigating and evaluating various SSCM complexities. RST limitations and extensions are introduced.     

Supply chain optimisation and protocol environment (SCOPE) for rapid prototyping and analysis of complex supply chains

There is a strong need for modelling tools that allow decision makers to rapidly develop aggregate models of supply chains, including both material and information flow, that they can use to gain insights and assess alternative configurations. We present a prototype implementation of such a system and apply it to a simple supply chain for validation purposes, and to a real world case study from the consumer packaged goods industry.     

基于经典扎根理论的虚拟企业供应链形成机理研究

管理学术界对实体企业的供应链研究已形成较系统的知识体系,而与虚拟企业有关的供应链研究才刚刚起步。企业间动态联合后会对供应链产生不同于企业单兵作战时的影响,这种影响广泛存在于企业实践中却较少被理论界所研究。因此,本文选择典型的虚拟企业为案例,运用经典扎根理论研究方法并采用认知地图工具,对虚拟企业供应链的动态变化进行了深入研究。研究发现,处于不同发展阶段的虚拟企业供应链形成过程有明显不同,该过程具有阶段性特征,并共同呈现虚拟企业供应链形成的内在机理。另外,在品牌影响力和供应链控制力的作用下,虚拟企业供应链的形式会产生由简入繁的变化,同时,其整体构型也出现了从“积木”组件向“积木”模型的蜕变,本文构建的“积木”模型形象地表达了上述机理。本文还发现,实体企业演化为虚拟企业的速度是影响虚拟企业供应链结构复杂程度的关键因素,两者呈现出相互关联的特性,可通过函数图形来表征。本文的研究弥补了虚拟企业供应链研究的不足,为更加深入研究相关问题奠定了理论基础。     

Supply‐Chain Research Opportunities with the Poor as Suppliers or Distributors in Developing Countries

Many social enterprises and some companies have developed supply chains with the poor as suppliers or distributors to alleviate poverty and to create revenues for themselves. Such supply chains have created new research opportunities because they raise issues fundamentally different from those examined in the existing operations management literature. We report this phenomenon of supply chains with the poor as suppliers or distributors in developing countries and identify operations management (OM) research opportunities. We also provide some stylized models to serve as potential seeds for modeling‐based research in this area.     

复杂供应链网络视域下关系资本对供应链融资作用机制研究--有调节的多重中介效应模型构建与检验

从复杂供应链网络的视角出发,以供应链网络内各节点中小企业为研究对象,依照"资源-结构-行为-绩效"的思路,揭示供应链网络内中小企业积累的关系资本对提升其供应链融资获取频率的作用机制,并通过构建多群组SEM模型,验证供应链复杂性的潜在调节效应。结果显示:(1)中小企业积累的关系资本对供应链融资频率的提升有显著的促进作用;(2)对比"关系资本-供应链设计-供应链融资"与"关系资本-供应链整合-供应链融资"的拟合结果发现,两个特定变量的中介效应具有显著差异,且以供应链设计、整合为连续中介变量的多重链式中介效应模型成立;(3)供应链复杂性显著调节中小企业关系资本对供应链融资的转化机制链条,供应链复杂性越高,节点中小企业获取供应链融资更依赖"关系资本-供应链设计-供应链整合-供应链融资"的多重链式传导机制传导。这意味着,在复杂供应链网络当中,中小企业一方面需要提升自身关系资本积累,另一方面更要加强其在网络当中的位置优化,提升供应链整合水平,为获取更多供应链融资打下坚实基础。     

Supply Network Structure,Visibility, and Risk Diffusion: A Computational Approach

Understanding and managing supply chain risks is a critical functional competency for today's global enterprises. A lack of this competency can have significant negative outcomes, including costly production and delivery delays, loss of future sales, and a tarnished corporate image. The ability to identify and mitigate risks, however, is complicated as supply chains are becoming increasingly global, complex, and interconnected. Drawing on the complex systems and epidemiology literature, and using a computational modeling and network analysis approach, we examine the impact of global supply network structure on risk diffusion and supply network health and demonstrate the importance of supply network visibility. Our results show a significant association between network structure and both risk diffusion and supply network health. In particular, our results indicate that small‐world supply network topologies consistently outperform supply networks with scale‐free characteristics. Theoretically, our study contributes to our understanding of risk management and supply networks as complex networked systems using a computational approach. Managerially, our study illustrates how decision makers can benefit from a network analytic approach to develop a more holistic understanding of system‐wide risk diffusion and to guide network governance policies for more favorable health level outcomes. The article concludes by highlighting the main findings and discussing possibilities of future research directions.     

Quality Management in Multi‐Level Supply Chains with Outsourced Manufacturing

Outsourcing stretches supply chains longer with added contract manufacturers responsible for the manufacturing of parts and final products. Should a firm change its quality management approach as its supply chain becomes longer with outsourced manufacturing? This paper studies a brand owner's optimal choice between two commonly used quality management approaches: an inspection‐based approach and an external failure‐based approach, in two supply chains – a dyadic supply chain and a multi‐level supply chain where the brand owner outsources manufacturing to an independent contract manufacturer. Our study finds that the brand owner's optimal choice between the two quality management approaches could be opposite in the two supply chains. Specifically, we show that if agency costs exist between the contract manufacturer and the brand owner, the brand owner may prefer an inspection‐based approach in the multi‐level supply chain in contrast to preferring an external failure‐based approach in the dyadic supply chain. In particular, inspections can be effective for the brand owner to limit the manufacturer's profit by excluding defective finished products and components, which in turn reduce agency costs in the multi‐level supply chain. Hence, the efficiency of an inspection‐based approach relative to an external failure‐based approach can be higher in the multi‐level supply chain as compared to the dyadic one. Our findings suggest that firms should adjust to changes in supply chain structures and re‐evaluate the efficiencies of different quality management approaches accordingly.     

社会责任环境下供应链的协作与利润分享策略研究

在企业社会责任环境下,研究了由一个供应商和一个制造商组成的两层供应链的协作、定价及其利润分享问题.分别研究了Nash均衡、Stackelberg均衡和合作博弈情况下,制造商与供应商的均衡结果和系统利润,并设计一简单的收入分享契约,该利润分享契约可以实现供应链的帕雷托改进,甚至达到集中式供应链的情形.最后给出了算例分析.     

Supply chain reconfiguration opportunities arising from additive manufacturing technologies in the digital era

Abstract

The aim of this study is to explore the impact of additive manufacturing (AM) technologies on the configuration opportunities of supply chains (SCs) within the digital manufacturing era. To this effect, we first conduct a critical taxonomy of existing research efforts and then propose an integrated decision-making process for the design and management of SCs defined by digital manufacturing technologies. Following, we provide an integrated framework for future SC reconfiguration opportunities arising from the adoption of AM on a supply network setting. Our analysis demonstrates the significant ramifications of AM techniques on SC configuration and sustainability performance as opposed to conventional value networks; however, existing research is evidently limited due to scope related challenges and the inherent complexity at the manufacturing echelon of the respective supply networks.