Hybrid Petri-nets for modelling and performance evaluation of supply chains

Modelling and analysis of complex and co-ordinated supply chains is a crucial task due to its inherent complexity and uncertainty. Therefore, the current research direction is to devise an efficient modelling technique that maps the dynamics of a real life supply chain and assists industrial practitioners in evaluating and comparing their network with other competing networks. Here an effective modelling technique, the hybrid Petri-net, is proposed to efficiently handle the dynamic behaviour of the supply chain. This modelling methodology embeds two enticing features, i.e. cost and batch sizes, in deterministic and stochastic Petri-net for the modelling and performance evaluation of supply chain networks. The model is subsequently used for risk management to investigate the issues of supply chain vulnerability and risk that has become a major research subject in recent years. In the test bed, a simple productive supply chain and an industrial supply chain are modelled with fundamental inventory replenishment policy. Subsequently, its performance is evaluated along with the identification and assessment of risk factors using analytical and simulation techniques respectively. Thus, this paper presents a complete package for industrial practitioners to model, evaluate performance and manage risky events in a supply chain.     

Selection of risk mitigation strategy in electronic supply chains using grey theory and digraph-matrix approaches

Supply chains are becoming more lengthy and complex due to globalisation and vertical integrations. In this context, adopting proactive approaches is needed for dealing with changing risks and vulnerabilities for securing supply chain systems. Supply chain risks are interlinked and thus, one mitigation strategy can reduce many of other supply chain risks. For example, aggregate or pooling demand reduces forecast risks, capacity risks and inventory risks. Also, some of the risk mitigation strategies have negative influences over certain supply chain risks as adding capacity has a negative influence on capacity risks. Twelve major supply chain risk categories and 21 risk mitigation strategies with typical focus on electronics manufacturing supply chains have been identified. A combination of grey theory and digraph-matrix methodologies has been used for quantifying various supply chain risk mitigation strategies and this approach is not seen in literature till date. The proposed model was also tested taking a case study of an Indian electronics manufacturing company. Obtained results were also subject to sensitivity analysis. The net positive influence values of risk mitigation strategies proposed in this research could effectively be used by top management for ascertaining their risk mitigation strategies for better management of supply chains as a whole.     

Supply chain risk classification: discussion and proposal

The supply chain management philosophy has often been used by organisations to achieve a competitive advantage, but it increases the vulnerability of these supply chains (SC) to certain risks. This dialogue between competitive advantage and risk generation has increased the number of studies related to the topic of ‘supply chain risk management’. Aiming to contribute to this field of research, a literature survey was conducted on 16 risk classifications, which included 56 risk types. These risk types were sorted according to existing conceptual similarities and then related to the five management processes intrinsic in a functional SC (plan, source, make, deliver and return), which are mainly advocated by the supply chain operations reference model. This literature review also highlights the lack of consensus among the surveyed authors concerning the risk types that affect a SC, a gap which this paper seeks to close by proposing a supply chain risk classification.     

Sustainable supply chains for supply chain sustainability: impact of sustainability efforts on supply chain risk

Supply chain managers across the globe are finding it difficult to manage the increasingly complex supply chains despite adopting a variety of risk mitigation strategies. Firms on the other hand have also been adopting various kinds of environmental and social sustainability practices in recent times to reduce carbon footprint and improve their image on the social front. However, very few studies in the extant literature have examined the impact of sustainability practices on supply chain risk. We address this important gap in literature by empirically testing this relationship, using primary data from six manufacturing sectors and 21 different countries including developed as well as emerging markets across the globe. Our findings indicate that risk mitigation strategies do not always reduce the actual supply chain risk experienced by firms, whereas sustainability efforts help reduce supply chain risk, especially in emerging market contexts. In addition, we find that, while reactive risk mitigation strategies on their own fail to reduce supply chain risk, they are effective when used in conjunction with sustainability efforts. We also find that preventive risk mitigation efforts are only effective in mature supply chains such as the OECD countries.     

Development of a hybrid fresh food supply chain risk assessment model

Supply chain managers and scholars recognise the importance of managing supply chain risk, especially in fresh food supply chain due to the perishable nature and short life cycle of products. Supply chain risk management consists of supply chain risk assessment, risk evaluation and formulation and implementation of effective risk response strategies. The commonly adopted qualitative methods such as risk assessment matrix to determine the level of risk have limitations. This paper proposes a hybrid model comprising both fuzzy logic (FL) and hierarchical holographic modelling (HHM) techniques where risk is first identified by the HHM method and then assessed using both qualitative risk assessment model (named risk filtering, ranking and management Framework) and fuzzy-based risk assessment method (named FL approach). The risk assessment results by the two different approaches are compared, and the overall risk level of each risk is calculated using the Root Mean Square calculation before identifying response strategies. This novel approach takes advantage of the benefits of both techniques and offsets their drawbacks in certain aspects. A case study in a fresh food supply chain company has been conducted in order to validate the proposed integrated approach on the feasibility of its functionality in a real environment.     

Effect of firm characteristics,supplier relationships and techniques used on Supply Chain Risk Management (SCRM): an empirical investigation on French industrial firms

Recent years have witnessed a focus on managing risks in supply chains. On the one hand, there are many cases where events like natural disasters, strikes and terrorism have significantly influenced the performance of organisational supply chains and in turn their competitiveness. And on the other hand, operational activities and strategic decisions of the firms (concerning, for e.g. supply, procurement, production, delivery, commercialisation, demand management, planning, etc.) can be different than expected and so create uncertainties. Uncertainties, whether they are external or internal, impact organisations leading to increased supply chain risk. Realising the potential implications of these situations on supply chain competitiveness, an attempt has been made to define risks and their sources and to identify the management that can help reduce the negative impact of risks on supply chains. In this paper, a framework for supply chain risk management (SCRM) is proposed and is applied using the data collected from 164 French companies, in manufacturing sector. The literature review, theoretical framework and empirical research undertaken in this work have led to identifying critical success management for SCRM. The focus of this paper is the inter-organisational management of supply chain risk: the collaborative relationship (with industrial and supply partners) can be considered as an efficient way to make SCRM. The paper finishes with a summary of the findings and conclusions, along with suggestions for future research projects.     

Literature review on disruption recovery in the supply chain*

Recent research underlines the crucial role of disruption events and recovery policies in supply chains. Despite a wealth of literature on supply chain design with disruption considerations, to the best of our knowledge there is no survey on supply chain with disruptions and recovery considerations. We analyse state-of-the-art research streams on supply chain design and planning with both disruptions and recovery considerations with the aim of relating the existing quantitative methods to empirical research. The paper structures and classifies existing research streams and application areas of different quantitative methods subject to different disruption risks and recovery measures. We identify gaps in current research and delineate future research avenues. The results of this study are twofold: operations and supply chain managers can observe which quantitative tools are available for different application areas; on the other hand, limitations and future research needs for decision-support methods in supply chain risk management domains can be identified.     

基于直觉模糊关系的供应链风险评估

针对供应链风险评判过程中的复杂模糊关系,借助直觉模糊理论,将犹豫度引入到具体的风险评判过程中,构建基于直觉模糊关系的供应链风险评判决策模型,并详细阐述了该方法的算法步骤,最后通过具体算例对该模型的实际应用进行了一定的分析.结果表明,该模型有望在实际中得到更加广泛的应用.     

Quantifying risks in a supply chain through integration of fuzzy AHP and fuzzy TOPSIS

Risk is inherent in almost every activity of supply chain management. With the ever-increasing push for efficiency, supply chains today are getting more and more risky. Adding to the difficulty of dealing with these risks is the amount of subjectivity and uncertainty involved. This makes analytical examination of the situation very difficult, especially as the amount of information available at a particular time is not sufficient for such an analysis. Thus a supply chain risk index, which captures the level of risk faced by a supply chain in a given situation, is the need of the hour. This study is an effort towards quantifying the risks in a supply chain and then consolidating the values into a comprehensive risk index. An integrated approach, with a fuzzy analytical hierarchy process (AHP) and a fuzzy technique for order preference by similarity to the ideal solution (TOPSIS) as its important elements, has been used for this purpose. Fuzzy values in this study help in capturing the subjectivity of the situation with a final conversion to a crisp value which is much more comprehensible. A case study is used to illustrate the proposed methodology.     

Evaluation mechanism for structural robustness of supply chain considering disruption propagation

This paper aims to develop a novel evaluation mechanism for assessing the structural robustness of a supply chain considering disruption propagation. Disruption propagation means that the impact of risks propagates to the whole supply chain along the connected structure. Based on the propagation model, a structural robustness evaluation mechanism is devised by integrating two quantitative metrics, average path length and in degree-out degree. To validate the proposed mechanism, the result of the quantitative assessment of the structural robustness on random networks is compared with the probability of network disruption due to the random risk. From the results of the statistical verifications and sensitivity analysis, it can be said that the proposed mechanism is better at explaining the robustness of a supply chain. In other words, all components of a network, such as nodes and arcs, and their relationships should be considered altogether, in order to more accurately measure the robustness. It may be possible to apply the proposed mechanism to the very first step of designing the supply chain. Especially, in the case of it being hard to redesign a supply chain structure after practically launching and operating the designed network, the proposed mechanism may be utilised to verify whether the planned supply chain is robust to risks or not.     

Supply chain risk modelling and mitigation

In today’s global competitive environment, supply chains are more susceptible to vulnerability due to the increasing occurrence of internal and external risk events. In addition, the trend associated with lean management, which involves reducing inventory, leads to more dependency of supply chain partners on each other which exacerbates risk exposure of companies in the supply chain. This creates the need for more effective management of supply chain risks. In this research, a methodology based on Bow-Tie analysis and optimisation techniques is proposed to quantify and mitigate supply chain risks. The proposed methodology takes into consideration risk interconnections, and it identifies the best combination of mitigation strategies under budget constraints. A real case study from a high-end server manufacturing environment is presented. Results from the case study showed that the proposed methodology for risk modelling and mitigation can effectively be used to quantify the risks and achieve the required risk reduction at minimum cost while considering risk correlations.     

再利用市场中三方关联供应链的决策与协调

提出了在生产废弃物再利用过程中,将横向供应链和纵向供应链相结合的三方关联供应链（TSC）模型。分析了由于多产品多市场供需不确定导致的多重供需关系不匹配的情况下, TSC集中决策时的最优模型和分散决策下的双重主从最优决策模型。通过对传统两条供应链模型、TISC模型中分散决策模型和集中决策模型的收益进行对比,充分证明了跨链间TSC模型的可行性及集中决策的优越性。通过契约先使得整体经济效益和环境效益的最大化,然后运用收入-费用分享机制在TSC之间进行了收益共享。结果表明,与传统方式不同,在生产废弃物再利用的TSC模型中,负价格定价机制的运用同样能实现效益的增长。     

A comparison of supply chain vulnerability indices for different categories of firms

Given the high vulnerability of today's supply chains to disruptions, measuring and managing supply chain vulnerability has become critical. In the attempt to support practice in reducing supply chain vulnerability, we (1) discuss and define the concept of supply chain vulnerability and (2) measure and compare supply chain vulnerability for various categories of firms. Normal Accident Theory and High Reliability Theory provide the theoretical foundations for the empirical study, and graph modelling is the method used to construct a measure for supply chain vulnerability. The empirical data largely confirm that there is a negative relationship between supply chain vulnerability and supply chain performance, a positive relationship between structural categories (firm size and production type) and supply chain vulnerability, and a positive relationship between supply chain vulnerability and managerial categories (logistics importance, supply chain risk planning, and supply chain risk management).     

Bayesian network modelling for supply chain risk propagation

Supply chain risk propagation is a cascading effect of risks on global supply chain networks. The paper attempts to measure the behaviour of risks following the assessment of supply chain risk propagation. Bayesian network theory is used to analyse the multi-echelon network faced with simultaneous disruptions. The ripple effect of node disruption is evaluated using metrics like fragility, service level, inventory cost and lost sales. Developed risk exposure and resilience indices support in assessing the vulnerability and adaptability of each node in the supply chain network. The research provides a holistic measurement approach for predicting the complex behaviour of risk propagation for improved supply chain risk management.     

分布式多级供应链整合建模及仿真

针对4级供应链结构,构造了多产品、多级结构的采购-生产-分销供应链整合模型。该模型面向供应链各级结构的物流优化,以供应链总成本最小并满足一定容量柔性为目标,确定供应商、工厂、配送中心的最优数目及其选择,以及配送中心和客户区之间的最优配置关系。在此基础上利用LINGO进行仿真求解,对不同场景下的供应链总成本进行了估算,并对容量柔性进行权衡,证明了模型的可行性和有效性。     

Risks and performance in supply chain: the push effect

A risk, when it occurs, causes negative effects on outputs. Typically risks are not independent, as multiple risks occur simultaneously. These risks have links, creating a ‘push’ effect, thus increasing the severity of each and all risk(s) on outputs. This paper aims to verify the mechanism of the push effect that is a new approach in the supply chain risk management literature. In this study, two models were compared: (1) only exists in direct effects of risks on supply chain performance, i.e. the competitive model. The other, (2), contains relationships among risks that show the mechanism of the push effect, i.e. the hypothesised model. Empirical evidence found in the Vietnam construction sector proved that the hypothesised model is better suited and has greater effect on supply chain performance in terms of each and all risk(s). Comparing 55% variance of the competitive model, the hypothesised one can explain up to 73% variance of supply chain performance. These results confirm our hypotheses of the push effect. Furthermore, findings achieved from this research can be used as ‘a guideline’ for reducing the impact of this mechanism.     

Bottleneck identification in supply chain networks

In supply chain risk management, it is essential to identify firms that induce high losses due to supply chain disruptions in a focal firm or the supply chain network as a whole (bottlenecks). In this article, we describe supply chain networks as complex systems of firms and their suppliers. We revisit some established network measures and compare their predictions with a new methodology for detecting bottlenecks. In this bottom-up approach, production disruptions on the firm level are modelled with stochastic point processes, and a mechanism for the propagation of losses through the network is defined. The individual firms' emerging loss contributions to the total losses of the focal firm provide, then, an alternative risk-adjusted measure. Our methodology and findings enable more informed and transparent decisions to be made for optimal supply chain network design.     

Product complexity and supply chain design

To assemble a product, each and every part is required. Hence, the more parts in the product, the greater the risk of disruption. Compared with retailers or assemblers of simple products, manufacturers of complex products are much more sensitive to supply chain delays. This heightened vulnerability to supply chain disruptions should lead complex product assemblers to design less risky supply chains. Supply chain design should depend on the complexity of the product assembled or manufactured. This paper models how product complexity drives the likelihood of disruption for given component supply chain reliabilities. The paper provides insights for supply chain design that comprehends the impact of product complexity.     

Reliable design of a closed loop supply chain network under uncertainty: An interval fuzzy possibilistic chance-constrained model

This article seeks to offer a systematic approach to establishing a reliable network of facilities in closed loop supply chains (CLSCs) under uncertainties. Facilities that are located in this article concurrently satisfy both traditional objective functions and reliability considerations in CLSC network designs. To attack this problem, a novel mathematical model is developed that integrates the network design decisions in both forward and reverse supply chain networks. The model also utilizes an effective reliability approach to find a robust network design. In order to make the results of this article more realistic, a CLSC for a case study in the iron and steel industry has been explored. The considered CLSC is multi-echelon, multi-facility, multi-product and multi-supplier. Furthermore, multiple facilities exist in the reverse logistics network leading to high complexities. Since the collection centres play an important role in this network, the reliability concept of these facilities is taken into consideration. To solve the proposed model, a novel interactive hybrid solution methodology is developed by combining a number of efficient solution approaches from the recent literature. The proposed solution methodology is a bi-objective interval fuzzy possibilistic chance-constraint mixed integer linear programming (BOIFPCCMILP). Finally, computational experiments are provided to demonstrate the applicability and suitability of the proposed model in a supply chain environment and to help decision makers facilitate their analyses.     

Supplier selection based on supply chain ecosystem,performance and risk criteria

A supply chain ecosystem consists of the elements of the supply chain and the entities that influence the goods, information and financial flows through the supply chain. These influences come through government regulations, human, financial and natural resources, logistics infrastructure and management, etc., and thus affect the supply chain performance. Similarly, all the ecosystem elements also contribute to the risk. The aim of this paper is to identify both performances-based and risk-based decision criteria, which are important and critical to the supply chain. A two step approach using fuzzy AHP and fuzzy technique for order of preference by similarity to ideal solution has been proposed for multi-criteria decision-making and illustrated using a numerical example. The first step does the selection without considering risks and then in the next step suppliers are ranked according to their risk profiles. Later, the two ranks are consolidated into one. In subsequent section, the method is also extended for multi-tier supplier selection. In short, we are presenting a method for the design of a resilient supply chain, in this paper.