Optimal service parts contract with multiple response times and on-site spare parts

This study examines user outsourcing of spare parts management to vendors through a service contract. The user’s selection of a fixed-price service parts contract is formulated as a stochastic integer programming model that decides multiple response times and on-site spare parts, while considering component breakdown with uncertain failure rates. We analytically derive the optimality conditions for the continuous case and subsequently design an efficient algorithm. Numerical illustrations and analyses are conducted to evaluate decisions under various scenarios. Our analysis shows that when both failure rate and expedited contract cost are high, coupled with low part cost, users would prefer the purchase of spare parts for all components to expedited contracts. A fixed-price expedited contract has a lower marginal cost with respect to failure rate than a fixed-price next day contract and a usage-based contract. We also examine inventory behaviour for a single part, multiple types of parts, and multiple groups of parts. It is shown that there is a cost-saving pooling effect in spare parts for identical items, which significantly raises the likelihood of having on-site stored parts. The problem becomes more complex for multiple items, reflecting bundling effects between items for a given contract.     

Additive manufacturing technology in spare parts supply chain: a comparative study

Additive Manufacturing (AM) technology has the potential to significantly improve supply chain dynamics. The purpose of this paper is to investigate the impact of AM on spare parts supply chain. Three supply chain scenarios are investigated in this paper, namely conventional supply chain, centralised AM-based supply chain and distributed AM-based supply chain. Based on system dynamics simulations, this paper specifically compares three supply chain scenarios, in terms of total variable cost and carbon emission. The results show the spare part supply chain utilising AM is indeed superior to the traditional one in sustainable performance. It is also expected that AM can facilitate the spare parts supply chain to achieve more economic benefits along with its development. To our knowledge, this paper is one of the early studies that explores the impact of AM on supply chain performance and quantitatively examines the superiority of utilising AM in spare parts supply chain. Some suggestions are also provided to help managers adopting AM in their spare parts supply chains.     

Two-echelon multi-item spare parts systems with emergency supply flexibility and waiting time constraints

We consider a two-echelon multi-item spare parts inventory system in which supply flexibility through both lateral transshipments and direct deliveries are used in response to stock-outs. We develop a simple heuristic to determine the stocking levels for each type of spare part at the central warehouse and local warehouses minimizing the expected total system cost subject to a target level for the average waiting time across items at each local warehouse. Numerical comparisons between the heuristic's objective function values and lower bounds obtained by applying Lagrangian relaxation techniques show that the heuristic performs well. A study to evaluate the relative merits of a two-echelon system as opposed to a single-echelon system is also presented. We find that the presence of lateral transhipment improves the performance of the single-echelon system considerably. A two-echelon system is only worth implementing when lateral transhipments are not possible.     

Modelling and solving spare parts supply chain network design problems

Spare parts are key operational assets in order to minimise unexpected equipment downtimes that may significantly impact a company’s results. The spare parts supply chain network supports the entire spare parts operations management and it is essential to achieve the planned goals. However, most of the traditional literature on spare parts management has not focused on the underlying supply chain network. Thus, this paper studies the integration of supply chain network design and control with traditional spare parts management. In particular, a generic network optimisation modelling structure is proposed, with simultaneous optimisation of warehouse locations and inventory control decisions, allowing minimising the total costs associated with the spare parts supply chain network. The generic model is specified based on three inventory control policies widely employed in the industry, which are suitable for managing a great variety of spare parts, i.e. (s, Q), (R, s, S) and (S-1, S). Furthermore, a solution approach is proposed based on Generalised Benders Decomposition. Finally, numerical results from a real-world application case in the process industry are shown and discussed.     

Benefits of considering inventory in service parts logistics network design problems with time-based service constraints

We study the integrated logistics network design and inventory stocking problem as characterized by the interdependency of the design and stocking decisions in service parts logistics. These two sets of decisions are usually considered sequentially in practice, and the associated problems are tackled separately in the research literature. The overall problem is typically further complicated due to time-based service constraints that provide lower limits on the percentage of demand satisfied within specified time windows. We introduce an optimization model that explicitly captures the interdependency between network design (location of facilities, and allocation of demands to facilities) and inventory stocking decisions (stock levels and their corresponding stochastic fill rates), and present computational results from our extensive experiments that investigate the effects of several factors including demand levels, time-based service levels and costs. We show that the integrated approach can provide significant cost savings over the decoupled approach (solving the network design first and inventory stocking next), shifting the whole efficient frontier curve between cost and service level to superior regions. We also show that the decoupled and integrated approaches may generate totally different solutions, even in the number of located facilities and in their locations, magnifying the importance of considering inventory as part of the network design models.     

Strategies for warranty service in a dual-channel supply chain with value-added service competition

This paper studies a dual-channel supply chain composed of a manufacturer and a retailer. The manufacturer and the retailer sell homogeneous durable goods bundled with warranty service that is provided by the manufacturer, and they compete for customers by offering free value-added service. Both the warranty and value-added services can affect the purchasing behaviour of customers. We examine the warranty service decision of the manufacturer and the value-added service competition between the manufacturer and the retailer. Three types of warranty service strategies that can affect the value-added service competition are proposed. By analysing the equilibriums of the value-added service level decisions of the manufacturer and the retailer, we find that when the manufacturer increases its warranty service level, the value-added service competition will be weakened, and when the warranty service level is high enough, there is no value-added service competition. In addition, we examine the optimal warranty service strategy and warranty service level of the manufacturer under different conditions, and we find that the stronger the manufacturer’s bargaining power is, or the stronger the value-added service competition intensity is, the more motivation the manufacturer has to provide a high warranty service level. Numerical examples reveal that differentiation strategy in value-added service may hurt the profits of the manufacturer, the retailer and the entire supply chain.     

Impact of an emergency order opportunity on supply chain coordination

We consider a manufacturer-retailer supply chain in the pre-selling and selling seasons, whereby the manufacturer can offer the retailer an emergency order opportunity with a limited commitment quantity in addition to the regular order from the retailer before the selling season. Due to the short lead time for the emergency order, the manufacturer needs to prepare for it in the pre-selling season by producing more than the regular order or reserving its capacity for the responsive production. Through mathematically modelling and analyzing the supply chain, we found that, when the emergency order opportunity is provided, the manufacturer might be worse off, although the retailer is always better off. We derive the conditions whereby both the manufacturer and retailer can benefit from the emergency order, and the supply chain profit can be maximised. Further, we show that the supply chain can be coordinated by setting only the unit price and maximum commitment quantity for the emergency order. We also prove that Pareto improvement can be always achieved by setting the unit price for the regular order in addition to the unit price and maximum commitment quantity for the emergency order.     

The impact of supply chain disruption on the closed-loop supply chain configuration profit: a study of sourcing policies

A closed-loop supply chain configuration (CLSCC) encompasses the decisions related to the optimal selection of options at each stage of a closed-loop supply chain (CLSC) for the introduction and reconstruction of new products. The extant literature ignores the impact of supply chain disruptions on CLSCC. An attempt is made to fill this gap in this study. Thus, an integrated multi-sourcing CLSCC optimisation model for new and reconstructed products is developed. The optimisation model presented is a mixed-integer nonlinear programming (MINLP) model. Based on a real-world case study of an auto-parts manufacturer in India presented, a comprehensive set of computational experiments, scenario analyses are conducted. The key finding/observation that resulted from our computational experiments is that multi-sourcing generates higher net present value of total profit compared to single sourcing under the risk of supply chain disruption. Several other observations and managerial insights are drawn from computational experiments, and scenario analyses. Firms interested in configuring their CLSC under the risk of supply chain disruption may use the study's outcomes to understand the profit impact of various CLSCC parameters, individually and in combination.     

New flexibility drivers for manufacturing,supply chain and service operations

Increasing product proliferation, customisation, competition and customer expectations, as well as supply side disruptions, pose significant challenges to firm operations. Such challenges require improved efficiency and resilience in manufacturing, service and supply chain systems. New and innovative flexibility concepts and models offer a prospective route to such operational improvements. Several emerging issues in flexibility, such as risk and uncertainty management, environmental sustainability, optimal strategies under competition, optimal operations with strategic consumer behaviours are being examined in this regard. This overview provides a concise review of these critical research issues, and discusses related papers featured in this special issue. Four major flexibility drivers are classified: disruption risks, resilience and the ripple effect in the supply chain; digitalisation, smart operations and e-supply chains; sustainability and closed-loop supply chains; and supplier integration and behavioural flexibility.     

Inventory management in a lateral collaborative manufacturing supply chain: a simulation study

Due to global competition, firms are seeking more effective supply chain (SC) collaboration in order to provide quality products with less cost, at the right time and in the right quantity. The present study examines manufacturing SC collaboration on the basis of holding cost, backorder cost and ordering cost. The types of collaboration examined are vertical, horizontal and lateral collaboration. This research emphasises lateral collaboration by determining the impact of inventory policies ((s, S) and (s, Q) inventory policies) on SC performance. For better understanding, a conceptual model is provided that is supported by a numerical example. As the study of SCs is complex in nature, a simulation approach has been employed to show the impact of lateral collaboration on performance measures such as the total cost, which is the sum of several cost components: inventory holding cost, backorder cost and ordering cost. The research is based on two manufacturing SCs where the manufacturer is taken as the collaborative node. To allow more clarity, a separate study on each cost component has been conducted. The laterally collaborative SC was simulated on ARENA 9.0, a simulation package. The results show that the efficacy of lateral collaboration outperforms horizontal collaboration due to having the individual SC members at more liberty to make decisions.     

On the risk-averse optimization of service level in a supply chain under disruption risks

The worst-case optimization of service level in the presence of supply chain disruption risks is considered for the two different service levels measures: the expected worst-case demand fulfillment rate and the expected worst-case order fulfillment rate. The optimization problem is formulated as a joint selection of suppliers and stochastic scheduling of customer orders under random disruptions of supplies. The suppliers are located in different geographic regions and the supplies are subject to random local and regional disruptions. The obtained combinatorial stochastic optimization problem is formulated as a mixed integer program with conditional service-at-risk as a worst-case service level measure. The risk-averse solutions that optimize the worst-case performance of a supply chain are compared for the two service level measures. In addition, to demonstrate the impact on the cost in the process of optimizing the worst-case service level, a joint optimization of expected cost and conditional service-at-risk using a weighted-sum approach is considered and illustrated with numerical examples. The findings indicate that the worst-case order fulfillment rate shows a higher service performance than the worst-case demand fulfillment rate. Maximization of the expected worst-case fraction of fulfilled customer orders better mitigates the impact of disruption risks. The supply portfolio is more diversified and the expected worst-case fraction of fulfilled orders is greater for most confidence levels. Finally, the results clearly show that worst-case service level is in opposition to cost.     

Involvement in emergency supply chain for disaster management: a cognitive dissonance perspective

An integrated process, interlinked operation and interoperable communication network amongst operating agencies are critical for developing an effective disaster management supply chain. The traditional managerial problems observed across disaster management operations are: non-cooperation among members, disrupted chain of commands, misuse of relief items, lack of information sharing, mistrust and lack of coordination. This study aims to understand the issues affiliated with negative attitude towards disaster management operations using theory of cognitive dissonance. A qualitative investigation was undertaken across 64 districts in Bangladesh. Five constructs were examined for their influences on attitude and behavioural intention of members participating in government emergency supply chain for disaster management. The results indicate that administrative conflict, political biasness and professional growth have significant effects on attitude. Impact of insecurity is non-significant on attitude. This research offers substantial theoretical contribution to the cognitive dissonance theory in the context of disaster management supply chain.     

The bullwhip effect in hybrid supply chain

As the service is becoming the strategic preference in the manufacturing industry, more and more manufacturing companies provide customers with total solutions by integrating services into their core product offerings, which is usually implemented in so-called hybrid supply chain (HSC). The HSC is formed as a chain by a group of manufacturers and service providers who work together to offer total solutions to customers. In HSC, customers’ responses to variable service levels and the interaction between inventory strategy and service capacity strategy have a great impact on supply chain instability, which represents an important concern in supply chain research. To tackle this problem, we establish a system dynamics model, by taking the HSC for an elevator company in China as an example. Firstly, we analyzed the oscillation characteristics of service flow and product flow. Then, we proposed the performance metrics of bullwhip effect in HSC. Finally, based on the model, we find that the bullwhip effect of HSC could be smoothened by incorporating service capacity adjustment strategy into the inventory replenishment policy.     

A constrained EPSAC approach to inventory control for a benchmark supply chain system

The design of an appropriate inventory control policy for a supply chain (SC) plays an essential role in tempering inventory instability and bullwhip effect. Several constraints are commonly encountered in actual operations so managers are required to take these physical restrictions into account when designing the inventory control policy. Model predictive control (MPC) appears as a promising solution to this issue, due to its capability of finding optimal control actions for a constrained SC system. Therefore, the inventory control problem for a benchmark SC is solved using the extended prediction self-adaptive control approach to MPC. To extend methodologies in our previous work, the control framework relies on generic process model and incorporates the physical constraints arising from practical operations to form the general constrained optimisation problems. The managers can choose from decentralised and centralised control structures according to specific informational and organisational factors of their SCs. The proposed control schemes in this study may be appropriate for industrial practice because the designed policy can bring a reduction of over 30% in operating cost and a significant increase of customer satisfaction level compared with that of the conventional policy.     

Flexibility dimensions to control the bullwhip effect in a supply chain

In this paper, we analyse the consequences of two flexibility dimensions proposed in a previous approach—adjustment capability and responsiveness—on the bullwhip effect in a supply-chain model when a stochastic AR(1) demand process is considered. First modelling the manager's belief on forecasting in pull, push and hybrid ordering methods, it is revealed that high adjustment capability induces a robust reduction of the bullwhip effect. Secondly, it is found that maximal responsiveness is not always a necessary management strategy. Indeed, we show that these dimensions may be organised in a trade-off, always keeping amplification to acceptable values in the whole supply chain.     

Stockout propagation and amplification in supply chain inventory systems

We investigate the existence and magnitude of stockout propagation and stockout amplification in the context of supply chain inventory systems. Stockout amplification is a stage-to-stage increase in overall stockout rates. Stockout propagation is the tendency for stockout at one node to instigate a stockout at a neighbouring node and is conceptually related to the idea of cascading failures in physical systems, such as electrical power grids. We study these concepts in both upstream (‘supply side’) and downstream (‘demand side’) directions in the context of normal operating conditions for an adaptive R, S (periodic, order-up-to) inventory policy. We build a simulation model of a 5-stage serial supply chain that experiences normally distributed customer demands and gamma distributed lead times. We find that stockout propagation exists, but contrary to conventional wisdom, it occurs in the upstream direction. There is little indication that stockout propagation is occurring to any significant degree in the downstream direction. We also find stockout amplification occurring in the upstream direction in scenarios where more aggressively adaptive inventory parameter updating is performed. We discuss implications of this work in the areas of supply chain inventory modelling, ordering decisions, safety stock determination, and the use of adaptive inventory policies.     

Service capability procurement decision in logistics service supply chain: a research under demand updating and quality guarantee

Though existing researches have already studied on service quality guarantee and demand updating in a supply chain respectively, there is little attention paid to integrated research on service quality guarantee problem with demand updating. This paper aims to investigate the impacts of demand uncertainty revelation and quality guarantee change cost (GCC) on the optimal decisions of logistics service integrator (LSI) and functional logistics service provider (FLSP) in a logistics service supply chain. At the beginning of the first period, the FLSP first guarantees an initial quality level and the LSI procures service capacity from the FLSP based on the demand prediction. Then the demand information is updated after the first-period demand being satisfied, and the LSI and the FLSP make their optimal decisions based on the renewed demand in the next period. Before the second period, uncertainty complete revelation/uncertainty incomplete revelation (UCR/UIR) and GCC/no guarantee change cost (NGCC) may take place, which will affect the decisions the LSI and the FLSP make. Consequently, four situations are considered: (1) UCR and GCC; (2) UIR and GCC; (3) UCR and NGCC; and (4) UIR and NGCC. In each situation, we derive the optimal decisions of the FLSP and the LSI, and a comparison between the first- and second-period decisions in each situation is conducted. Several managerial insights are concluded, and the most important one is that the LSI is supposed to reduce the procurement quantity and the FLSP is supposed to promise a higher quality defect rate in the case of UIR and NGCC. Furthermore, in case of UIR and GCC, we specify a critical condition in which the LSI and the FLSP insist on the initial decisions of the first period. At last, we conducted numerical analysis and gave a practical example of China Yuantong Express Company to support our conclusions.     

The influence of additive manufacturing on the configuration of make-to-order spare parts supply chain under heterogeneous demand

Additive manufacturing (AM), alongside technological developments, has been used in the production of spare parts with positive results for spare parts supply chains. In this study, we investigate spare parts supply chains serving heterogeneous demands from multiple service locations under the mode of make-to-order. We aim to compare different configurations (i.e. centralised and distributed) of spare parts supply chains in terms of their performance (e.g. sojourn time and cost) and to further propose suggestions to better configure AM-based spare parts supply chains by effectively allocating AM machines at service locations (SLs) or regional distribution centres (RDCs). In order to realise these research objectives, the simulation approach is used as the main research method. Different from the existing perception, our results illustrate that the distributed deployment of AM machines does not always guarantee a quick response, and that centralised configuration is desirable when the demand rate is relatively high due to the pooling effect. The distributed configuration, however, can still be suitable, considering the development of AM technology. Our results also indicate the possibility of a mixed configuration of AM-based supply chains with the potential for outperforming the purely centralised/distributed configuration. The criteria to design such a mixed configuration are also offered.     

Relational benefits and manufacturer satisfaction: an empirical study of logistics service in supply chain

Using data collected from US manufacturing firms, this research evaluates logistics service from the eyes of manufacturers. The study leads to a close look at how manufacturers view third party logistics services to provide important strategic and operational values to manufacturers. The results indicate that the building of a long-term relationship is mediated by trust and commitment from manufacturers. When manufacturers believe that the logistics service provider is honest and passionate, and care about their business, they will make a commitment toward a long-term business relationship.     

Random yield and coordination mechanisms of a supply chain with emergency backup sourcing

This paper considers a supply chain in which a buyer purchases finished items from a contracting supplier to satisfy a stochastic market demand, where the supplier’s production is subject to random yield. We assume that the buyer can make up the shortage by sourcing from an emergency backup supplier. We develop two Stackelberg game models, i.e. buyer-Stackelberg (BS) model and supplier-Stackelberg (SS) model, and find that the decentralised BS model results in a higher stocking factor of supplier’s input than the decentralised SS model. Compared with BS model, the buyer in SS model performs more explicit order plan, and we find that only when the actual yield of the supplier is insufficient, the buyer would use emergency backup sourcing to make up the shortage. When the manufacturing operation of the supplier is in the good state, the buyer only orders a certain amount and has some leftover. When the actual yield of the supplier is moderate, the buyer uses up every item produced from the supplier regardless of the yield rate. Comparing both channel structures, SS operation is a more effective way of controlling both inventory cost and backup sourcing cost, and it can be beneficial for each player as well as for the whole channel. Finally, we develop the coordination mechanism for each channel to investigate the issues of risk handling and risk sharing for uncertain demand and uncertain yield.