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.     

Inventory policies analysis under demand patterns and lead times constraints in a real supply chain

This paper reports a study on a real three-echelon supply chain operating in the beverage sector. The authors, starting from the actual supply chain configuration, propose a detailed study of the inventory systems. The test of a comprehensive set of different operative scenarios, in terms of customers’ demand intensity, customers’ demand variability and lead times, becomes a powerful tool for inventory systems analysis along the supply chain. The main objective is the comparison of the actual supply chain configuration with optimistic and pessimistic scenarios for studying the behaviour of different inventory control policies and optimizing the inventory system of each supply chain node. Due to the dynamically changing and stochastic behaviour of the supply chain variables as well as the complex interactions among its actors, the authors have been pushed to implement an advanced simulation model supported by a ‘well-planned’ experimental design. In addition the paper aims to underline the research effort for conceptualizing, modelling, validating and simulating a real stochastic supply chain.     

Inventory performance of some supply chain inventory policies under impulse demands

This paper attempts to study the impact of impulsive demand disturbances on the inventory-based performance of some inventory control policies. The supply chain is modelled as a network of autonomous supply chain nodes. The customer places a constant demand except for a brief period of sudden and steep change in demand (called demand impulse). Under this setting, the behaviour of each inventory policy is analysed for inventory performance of each node. It is found that the independent decision-making by each node leads to a bullwhip effect in the supply chain whereby demand information is amplified and distorted. However, under a scenario where the retailer places a constant order irrespective of the end customer demand, the inventory variance was actually found to decrease along the supply chain. The variance of the inventory remained constant along the chain when only the actual demands are transmitted by each node. The results also showed that the inventory policy which is best for one supply chain node is generally less efficient from a supply chain perspective. Moreover, the policy which performs poorly for one node can be most efficient for the supply chain. In a way, our results also provide a case for coordinated inventory management in the supply chain where all members prepare a joint inventory management policy that is beneficial for all the supply chain nodes. The results have significant industrial implications.     

Investigating the implications of extending synchronized sequencing in automotive supply chains: the case of suppliers in the European automotive sector

In recent years automakers have paid considerable attention to synchronizing supply chain material flow. Potential benefits associated with synchronization include stability in both demand and supply patterns, inventory reduction, elimination of demand amplification and better long-term planning. In major European production sites, the geographic proximity of suppliers to the vehicle assembly plants provided the motivation for examining the feasibility of extending the synchronized sequenced delivery of components upstream in the vehicle supply chain. The value stream used in the research concerned the seating systems at two major European production sites. The results of extending synchronized sequencing from the first to the second tier showed a reduction in demand amplification to negligible levels, achieved overall synchronization levels of 99–100% and considerably reduced overall pipeline inventory between the vehicle assembly plant and the second tier component supplier. The findings suggest how the geographic proximity of suppliers can be used to implement multi tier synchronized sequencing of components to improve supply chain performance. Based on the results of the study a series of recommendations are provided concerning the supply chain implications of multi tier synchronized sequencing.     

考虑缺货成本的VMI利益分配

考虑缺货成本,从库存成本角度开展研究,通过对比实施VMI前后供应链库存成本模型,指出VMI短期内供应链收益来源于库存成本变化,且存在责任利益不一致的情况。针对供需双方不同地位,应用价格契约、斯坦科尔博格博弈模型与收益共享契约分别建立了零售商占优与供需双方地位平等情况下的利益分配模型,求解出零售商激励采购价格与收益共享系数的具体值,并采用算例进行分析。     

Exploring nonlinear supply chains: the dynamics of capacity constraints

While most supply chain models assume linearity, real production and distribution systems often operate in constrained contexts. This article aims to analyse the consequences of capacity limits in the order-up-to replenishment policy with minimum mean squared error forecasting under independently and identically distributed random demand. Our study shows that the impact of this nonlinearity is often significant and should not be ignored. In this regard, we introduce the concept of a settling capacity, which informs when our knowledge from a linear analysis is a reasonable approximation in a nonlinear context. If the available capacity is less than the settling capacity, the nonlinear effects can have a significant impact. We compare the Bullwhip Effect and Fill Rate in constrained contexts to well-established results for linear supply chains. We reveal the capacity limit acts as a production smoothing mechanism, at the expense of increasing inventory variability. We proceed to analyse the economic consequences of the capacity constraint and show that it can actually reduce costs. We provide an approximate solution for determining the optimal capacity depending on the demand, the unit costs and the lead time.     

Supply chain design and cost analysis through simulation

This paper is grounded on a discrete-event simulation model, reproducing a fast moving consumer goods (FMCG) supply chain, and aims at quantitatively assessing the effects of different supply configurations on the resulting total supply chain costs and bullwhip effect. Specifically, 30 supply chain configurations are examined, stemming from the combination of several supply chain design parameters, namely number of echelons (from 3 to 5), re-order and inventory management policies (EOQ vs. EOI), demand information sharing (absence vs. presence of information sharing mechanisms), demand value (absence vs. presence of demand ‘peak’), responsiveness of supply chain players. For each configuration, the total logistics costs and the resulting demand variance amplification are computed. A subsequent statistical analysis is performed on 20 representative supply chain configurations, with the aim to identify significant single and combined effects of the above parameters on the results observed. From effects analysis, bullwhip effect and costs outcomes, 11 key results are derived, which provide useful insights and suggestions to optimise supply chain design.     

VMI versus information sharing: an analysis under static uncertainty strategy with fill rate constraints

A vendor-managed inventory (VMI) relationship between a downstream retailer and an upstream vendor consists of two distinct components: (i) information sharing (IS) and (ii) a shift in decision-making responsibility. This study compares these two components of VMI in a two-stage serial supply chain based on the ‘static uncertainty’ strategy under dynamic and random demand with fill rate constraints. Numerical experiments are conducted using analytical models to identify the conditions where the incremental value of VMI over IS is significant. The results provide guidelines relevant to academia and supply chain practitioners in taking VMI adoption decision above and beyond IS according to their specific business environment.     

An EOQ model when production standards are assumed to be normally distributed

In this paper an EOQ model is developed especially for a production environment where the inventory to be controlled is raw material. The fundamental difference between this model and others is that a stochastic demand is placed upon the inventory in terms of the time for an individual to consume one unit of inventory rather than the number of units consumed in some time interval. A shortage cost for inventory is imposed via the idle machine (man) cost. The optimal re-order quantity is determined as a function of the stockout probability and the optimal stockout probability is obtained via a one-dimensional search, over some prescribed set of feasible stockout probabilities.     

Supply chain focus dependent sensitivity of the point of product differentiation

Customer preferences for variety in the product(s) with improved customer service and lower prices are forcing the supply chains to overhaul the current practices from design to operational level. Postponement or delayed differentiation of the products is one such strategy, primarily deployed in mass customisation settings. Life cycles are shrinking not only for individual products but for product families as well. In this context, supply chain responsiveness becomes one of the crucial factors that need to be effectively managed to succeed in the present day competitive markets. Our model, that considers inventory costs and the supply chain responsiveness costs would aid a supply chain manager to make informed decisions with regard to the ideal location for the point of differentiation (POD), while striking the right balance between holding costs and the supply chain responsiveness costs. We also make use of a dimensionless parameter called the ‘coefficient of inverse responsiveness’ that not only facilitates the introduction of responsiveness related costs into the model but also improves the scalability and simplifies the analysis and interpretation of the results. Based on the strategic model developed, we offer some context-specific counter-intuitive managerial insights with respect to the sensitivity of the location of the POD in a supply chain.     

双周期可变供货协议的运转优化模型:以漫友为例

关注一个双周期且存在单一供应商和多个经销商组成的供应链生产和库存的分配优化问题：第1个期间,供应商根据经销商的订单进行生产。从第2期间开始,通过引入一个双周期调整协议,供应商为经销商提供了一个可以在第2期间重新调整库存的机会,即每个经销商可以从供应商那里购买额外库存或销售回多余库存（转运实际发货、收货等交割可在经销商之间进行）。研究运用建立数学模型论证了双周期情况下一个供应商和多个经销商组成的纵向集中而横向分散型系统（半分散型系统）的生产、库存及价格最优均衡模型,接着通过实例数据分析,对完全集中型、半分散型和完全分散型系统转运优化效果进行比较,结果显示,完全集中型优化效果最好(最高13%),但实现难度大;而半分散型是否强于完全分散型系统,取决于调节协议中约定的批发价与生产成本之间的差距因素,差距越小,则半分散型系统的优化效果越强（最高3.39%）。     

Dynamic mutual adjustment search for supply chain operations planning co-ordination

Operational planning is an activity carried out by all manufacturing and logistical companies. Its co-ordination with supply chain partners aims at synchronising resources utilisation in order to minimise inefficiencies, such as unnecessary inventory holding, or in order to improve revenue through better resource utilisation. It is a rather complex process as partners have different objectives and information asymmetry is part of any effort to find good co-ordination solutions. Furthermore, because supply chains evolve in a dynamic and uncertain environment, once a co-ordination of operations plans is achieved, input data, such as forecasts or resources’ status, can change and affect on hand plans. These dynamic changes not only require updating the plan that is directly affected by the changes, but it also requires the adjustment of all plans that are part of the same co-ordination solution (Stadtler, H. 2009. A framework for collaborative planning and state-of-the-art. OR Spectrum, 31 (1), 5–30). Therefore, the development of a practical co-ordination approach should be capable of dealing with these dynamic changes. This paper proposes a dynamic mutual adjustment search heuristic, which can be used to co-ordinate the operations plans of two independent supply chain partners, linked by material and non-strategic information flows. Computational analysis shows that the proposed approach produces a win-win strategy in the context of two supply chain partners, and improves the results of upstream planning in each planning cycle, and also improves the fairness of revenue sharing when compared to optimal centralised planning.     

A fractal perspective-based methodological framework for supply chain modelling and distributed simulation with multi-agent system

With the development of global economy, supply chain, as a recognised complex system, is becoming more complex for analysis. In this context, it is worth introducing the perspective of complex system in perceiving and modelling of supply chain system to address its dynamic, stochastic and uncertain characteristics. Therefore, this paper proposes a methodological framework of supply chain modelling and simulation based on the fractal perspective, and presents an all-round and systematic exposition of concept modelling and distributed simulation by means of multi-agent technology. In this framework, different supply chain scenarios focusing on manufacturing, inventory and transportation can be easily modelled and simulated at different scales and levels. In addition, a prototype system which implements the methodological framework and the key implementation techniques are presented as well. Finally, a supply chain example, which supposes manufacturer as the core member, is modelled and simulated with the prototype system to illustrate the effectiveness of the proposed framework.     

The value of nonlinear control theory in investigating the underlying dynamics and resilience of a grocery supply chain

In an empirical context, a method to use nonlinear control theory in the dynamic analysis of supply chain resilience is developed and tested. The method utilises block diagram development, transfer function formulation, describing function representation of nonlinearities and simulation. Using both ‘shock’ or step response and ‘filter’ or frequency response lenses, a system dynamics model is created to analyse the resilience performance of a distribution centre replenishment system at a large grocery retailer. Potential risks for the retailer’s resilience performance include the possibility of a mismatch between supply and demand, as well as serving the store inefficiently and causing on-shelf stock-outs. Thus, resilience is determined by investigating the dynamic behaviour of stock and shipment responses. The method allows insights into the nonlinear system control structures that would not be evident using simulation alone, including a better understanding of the influence of control parameters on dynamic behaviour, the identification of inventory offsets potentially leading to ‘drift’, the impact of nonlinearities on supply chain performance and the minimisation of simulation experiments.     

On the Bullwhip Avoidance Phase: supply chain collaboration and order smoothing

This paper provides an assessment of the impact of collaboration and smoothing replenishment rules on supply chain operational performance and customer service level. Three supply chain configurations (i.e. Traditional, Information Exchange and Synchronised) in which orders are generated by smoothing (S, R) inventory control policies are studied for different proportional controllers. A supply chain stress test is performed through a sudden and intense change in demand. A structured and extended supply chain assessment framework is adopted. The main conclusions of this paper are the following. (i) The impact of Supply Chain Collaboration on overall supply chain performance is greater than that of order smoothing. Order smoothing mitigates the bullwhip effect, but it may have a negative impact on customer service. Supply Chain Collaboration mitigates the bullwhip effect, provides inventory stability, limits lumpy orders and enhances customer service level. (ii) The negative effect on customer service level of order smoothing is almost eliminated in synchronised supply chains.     

基于VMI的医院供应管理

医院大部分药品及相关用品属于易逝品,针对该类产品的特点,将VMI(Vender Managed Inventory)方法引入到医院供应管理研究中,通过建立两级供应链库存定量模型(即供应商-医院关系模型),比较实施VMI方法前后,医院、供应商以及供应链总库存成本的变化情况.通过定量比较证实,实施VMI方法可以有效降低医院及供应链总库存成本,供应商的库存成本虽有所升高,但是可以通过转移支付方法,使供应商与医院达到利益均衡点,从而降低供应链总库存成本,获得pareto均衡.     

Analysis of parts requirements variance for a JIT supply chain

Metrics used to assess level parts usage for some JIT supply chains are based on the product-unit by product-unit launch of products on the assembly line. However, many automobile assembly plants require parts suppliers to deliver parts to the assembly line by using a constant order cycle, non-constant order quantity framework. The paper proposes metrics that are suited to this parts delivery framework. Through extensive simulation over a wide range of assembly parameter values, it assesses the ability of supplier plants to match assembly requirements at each supply epoch. Among other things, the study finds that the conventional JIT scheduling framework also works well in general under this parts delivery arrangement, but acute parts stockout conditions could sometimes occur. Therefore, managers need to consider this in determining appropriate inventory levels for each part. This will prevent stockouts and reduce supply chain costs.     

Vendor-managed inventory and the effect of channel power

We analyze decentralized supply chains that follow general continuous review (Q, R) inventory policies subject to vendor-managed inventory agreements where the supplier chooses the order quantity Q, and the retailer chooses the reorder point R. Within the VMI scenario, we explore the effect of divisions of channel power on supply chain and individual agent performance by examining different game theoretic models. Optimal policies and analytical results, including existence and uniqueness proofs for equilibrium solutions under VMI, are derived. Numerical results are provided to compare the effectiveness of VMI and to analyze different channel power relationships under a variety of environmental conditions. We find that VMI can result in considerable supply chain savings over traditional relationships and that the relative division of channel power can significantly effect the performance of VMI. Interestingly, we find that the greatest system benefits from VMI arise in asymmetric channel power relationships, but that individual agents lack the incentive to assume a leadership role.     

The impact of quality considerations on material flow in two-stage inventory systems

Supply chain management literature calls for coordination between the different members of the chain. Inventory models achieve this coordination along a supply chain by making the lot size at an upstream entity an integer multiplier of the lot size at the adjacent downstream entity. Such models assume that all components produced are of acceptable quality and may cause suppliers to produce larger quantities than what is optimal. In this paper, we formulate and solve two-stage supply chain inventory models in which the proportion of defective products increases with increased production lot sizes. We show that quality considerations can lead to significant reduction in production lot sizes. In addition, the models show that most benefits to the supply chain are attained from the suppliers producing on a just-in-time basis rather than delivering to their customers just-in-time. We derive closed-form expressions for the optimal lot sizes for a two-stage supply chain under deterministic and then stochastic demand and illustrate the models with numerical examples.