Maintenance supplier selection considering life cycle costs and risks: a fuzzy goal programming approach

In this study, we address a new variant of supplier selection problem named maintenance supplier selection problem faced by a manufacturer. The production system consists of different multi-component equipments whose maintenance activities require several components (parts) each of which could be provided by multiple suppliers. A multi-objective mathematical model is developed to decide about the supply base of each part as well as the purchasing quantity of each part from each selected supplier. The model accounts for the total life cycle costs of purchased parts and various risks threatening the candidate suppliers. A fuzzy/soft lexicographic goal programming approach with soft priorities between objectives is proposed to enable the decision-maker to make preferred trade-offs between objectives by which the effects of various risks in each phase of life cycle of procured parts are investigated. The capability and effectiveness of the proposed model is validated through a case study. Some sensitivity analyses are also carried out for investigating the impact of cost, risk and objectives’ priorities on the final preferred compromise solution. Finally, some managerial insights and concluding remarks are provided.     

A new data envelopment analysis (DEA) model to select eco-efficient technologies in the presence of undesirable outputs

Recent global attention to the challenges of environmental protection is forcing firms and governments to evaluate, rank, and select eco-efficient technologies. Technologies may consume inputs to produce both desirable and undesirable outputs. It seems that the data envelopment analysis (DEA) is a proper method to evaluate eco-efficient technologies. There are some DEA extensions for dealing with undesirable output, and sometimes it is difficult to choose a suitable model to evaluate the technologies. The challenge becomes much more complex when the outcomes of models are not similar. In such a condition, subjective selection of alternative DEA models may lead to deviation from an optimal decision. Accordingly, the objective of this paper is to develop a combined model to include all characters of the previous DEA techniques in a flexible model to select optimum eco-efficient technology in the presence of undesirable outputs. A case study demonstrates the application of proposed procedure.     

A cash-constrained stochastic inventory model with consumer loans and supplier credits: the case of nanostores in emerging markets

We consider a small traditional retailer that is managing its inventory under strict cash constraints, mainly because typically informal loans are offered to customers. These stores are widely present in emerging markets, and we refer to them as nanostores (also called ‘mom-and-pop stores’). As the suppliers require immediate payments for goods delivered, a nanostore can only replenish products to the level for which it has on-hand cash available. To improve delivery efficiency, a supplier might offer a nanostore credit for its replenishments. However, currently, suppliers are often reluctant to do so as these nanostores quickly go bankrupt or disappear, hence defaulting on all outstanding credits. The objective of this paper is to determine when it is beneficial to offer supplier credits. We propose a multi-period, stochastic inventory model, and numerically compare scenarios with and without supplier credits. Our study shows that even in the presence of this risk, suppliers often have good incentives to provide these credits, even if interest is not incurred. For this to hold, the operations of the retailer should be (a little) profitable in the first place, for which we provide analytical conditions.     

Inventory decision-making models for a closed-loop supply chain system

In this paper, we investigate how buyers’ and suppliers’ distinct perceptions of technology uncertainty affect the relationship between communication frequency and supplier performance. Information processing theory suggests that a fit is desirable between perceived environmental uncertainty and the communication processes between organisations. However, if partners in a buyer-supplier relationship do not concur on the high level of technology uncertainty, it is highly questionable whether increased communication will be effective in increasing supplier performance. Using dyadic data from 86 buyer-supplier relationships, involving 388 respondents, we found that communication frequency was positively related to supplier performance only when both suppliers and buyers perceived high levels of technology uncertainty. When buyers perceived greater technology uncertainty than their suppliers, communication frequency was negatively related to supplier performance. The findings in this study show that it is important to take the distinct perceptions of buyers and suppliers of technology uncertainty into account when assessing the effects of communication frequency. It appears that increased communication is only effective when both parties acknowledge the need to communicate, and can be unfavourable when only one party sees the benefits of it.     

A basic model for co-ordinating a four-level supply chain of a product with a vendor,multiple buyers and tier-1 and tier-2 suppliers

This paper investigates the co-ordination of order quantities amongst the players in a four-level supply chain with a centralised decision process. The first level of the supply chain consists of multiple buyers, the second level of a vendor (manufacturer), the third level consists of multiple tier-1 suppliers, and the fourth level consists of multiple tier-2 suppliers. Each supplier supplies one or more items that are components of the product produced by the manufacturer. The model developed in this paper guarantees that the local costs for the players either remain the same as before co-ordination, or decrease as a result of co-ordination. A mathematical model is developed, with numerical examples presented and results discussed.     

Pre-selection of suppliers through an integrated fuzzy analytic hierarchy process and max-min methodology

There are a variety of analytical models for supplier selection ranging from simple weighted techniques to complex mathematical programming approaches. However, these models are specifically aimed at supporting a decision maker in a single phase, especially in the final selection phase and they have failed to consider the supplier selection process from a holistic point of view. Although the methodology presented in this paper primarily focused on the prequalification of potential suppliers, the outputs of the previous phases, namely problem definition and formulation of criteria, are used as inputs in this methodology. The methodology utilises a fuzzy analytic hierarchy process (AHP) method to determine the weights of the pre-selected decision criteria, a max-min approach to maximise and minimise the supplier performances against these weighted criteria, and a non-parametric statistical test to identify an effective supplier set. This information supports decision makers in making the final selection with effective alternative choices. Potential application of the proposed methodology is demonstrated in Audio Electronics in Turkey's electronics industry.     

Transmuting performance on manufacturing dimensions into business performance: An exploratory analysis of efficiency using DEA

This research examines efficiency in the transformation of performance on manufacturing competitive dimensions into business performance in the automotive supplier industry. Specifically, the study explores efficiency produced from data envelopment analysis (DEA) using cost, quality, time, flexibility and innovativeness performance as inputs and return on investment (ROI) and return on assets (ROA) as outputs. First tier suppliers to the 'Big 3' in North America were sampled. The 51 suppliers were categorized into three groups (high, medium and low) based on their efficiency. No significant group differences in quality, time, flexibility and innovativeness performance were found, but a significant difference does exist for cost. The results were further investigated by testing between-group differences for various cost reduction programmes, thereby identifying the levers and benchmarks for improving low efficiency firms.     

A review of mechanical drilling for composite laminates

Composite laminates (CFRP, GFRP, and fiber metal composite laminates) are attractive for many applications (such as aerospace and aircraft structural components) due to their superior properties. Usually, mechanical drilling operation is an important final machining process for components made of composite laminates. However, composite laminates are regarded as hard-to-machine materials, which results in low drilling efficiency and undesirable drilling-induced delamination. Therefore, it is desirable to improve the cost-effectiveness of currently-available drilling processes and to develop more advanced drilling processes for composite laminates. Such improvement and development will benefit from a comprehensive literature review on drilling of composite laminates. This review paper summarizes an up-to-date progress in mechanical drilling of composite laminates reported in the literature. It covers drilling operations (including conventional drilling, grinding drilling, vibration-assisted twist drilling, and high speed drilling), drill bit geometry and materials, drilling-induced delamination and its suppressing approaches, thrust force, and tool wear. It is intended to help readers to obtain a comprehensive view on mechanical drilling of composite laminates.     

Using integrated fuzzy DEMATEL and fuzzy C: means algorithm for supplier evaluation and selection

Decision-making techniques are used to help evaluate the current suppliers’ aim at classifying performance of individual suppliers against desired levels of performance, so as to design suitable plans to increase the performance and capabilities of suppliers. In this study, an integrated model is introduced and proposed for increasing the supplier selection and evaluation quality. The methodology is composed of two steps. The first stage is fuzzy decision-making trial and evaluation laboratory method in which the interactions between the evaluation criteria and the criteria weight have been computed. At the second stage, performances of suppliers are assessed using both the criteria weights obtained at the first stage and fuzzy c-means clustering algorithm by classifying the vendors according to their performances. Obtained results show that the proposed model is very well suited as a decision-making tool for supplier selection decisions.     

基于FMEA的军队第三方物流供应商选择

目的 针对军队第三方物流供应商的选择问题,从风险视角对供应商完成军事保障任务过程中可能存在的风险进行识别和评估,以降低军事物流外包风险,为军队第三方物流供应商决策提供方法和思路。方法 提出可将FMEA技术运用于军队第三方供应商选择中的操作性框架,按照框架流程确定评价标准、识别潜在失效模式、决策分析,可更加全面、科学地对军队第三方供应商做出选择。结果 在不考虑风险的情况下,5家候选供应商中E的原始评分最高,D排名居中,但经过FMEA分析后,由于E在单项评价指标上的风险比例太大,而D的各项指标风险比原始排名靠前的供应商小很多,因此D成为军队最终选择的供应商。结论 利用FMEA分析军队第三方物流供应商选择问题,可以起到事先识别可能出现的失效模式,分析产生原因和可能导致的后果以及现有措施的可控程度,从而评估每位候选供应商在确定的评价标准中的风险大小,最后综合原始评分得出了供应商选择的结果。该方法操作简单、计算方便,能比较全面衡量军队第三方物流供应商的综合水平,有助于提高军队物资保障效率,降低物资保障风险。     

Development and evaluation of the interactive bidding strategies for a demander and its suppliers in supplier selection auction market

Supplier selection strategy is a critical issue in a supply chain management (SCM) system. Selecting the correct suppliers can have a significant impact on the competitiveness of firms. This research is concerned with the development of the interactive bidding strategies for a demander and its multiple suppliers in a supplier selection auction market (SSAM). The objective of this paper is to investigate the negotiation efficiency for the various bidding strategies the demander employed in different order conditions. The negotiation efficiency is assumed as the required negotiation times to achieve an agreement, agreed price and the procurement costs. Further, this paper runs the experiments of SSAM and provides a bidding strategy guideline for a demander to achieve its goals of supplier selection in varying order conditions. To this end, the negotiation efficiency of this proposed bidding strategy model is compared with other research.     

Supply chain network design with unreliable suppliers: a Lagrangian relaxation-based approach

This paper deals with the integrated facility location and supplier selection decisions for the design of supply chain network with reliable and unreliable suppliers. Two problems are addressed: (1) facility location/supplier selection; and (2) facility location/supplier reliability. We first consider the facility location and supplier selections problem where all the suppliers are reliable. The decisions concern the selection of suppliers, the location of distribution centres (DCs), the allocation of suppliers to DCs and the allocation of retailers to DCs. The objective is to minimise fixed DCs location costs, inventory and safety stock costs at the DCs and ordering costs and transportation costs across the network. The introduction of inventory costs and safety stock costs leads to a non-linear NP-hard optimisation problem. To solve this problem, a Lagrangian relaxation-based approach is developed. For the second problem, a two-period decision model is proposed in which selected suppliers are reliable in the first period and can fail in the second period. The corresponding facility location/supplier reliability problem is formulated as a non-linear stochastic programming problem. A Monte Carlo optimisation approach combining the sample average approximation scheme and the Lagrangian relaxation-based approach is proposed. Computational results are presented to evaluate the efficiency of the proposed approaches.     

Channel coordination in an assembly system facing uncertain demand with synchronized processing time and delivery quantity

Supply chains need to be synchronized to increase system efficiency. With increasing globalization, an assembly or a manufacturing firm may receive supplies from all over the world. Synchronization of such a system becomes difficult for two reasons: first, each supplier has certain capacity and can supply materials with a fixed but different order processing time; second, each supplier has a different cost structure and, therefore, production quantities differ due to incentives conflicts, which leads to local optimization of profits by the suppliers. In the existing literature, this problem is generally tackled by focusing either on the synchronization of order processing time or on order quantity determination. However, when system coordination is of the essence, simultaneous consideration of both becomes imperative. A model to synchronize the assembly process is proposed and the optimal order quantities in a two-echelon assembly system with one assembler (facing a stochastic demand) and multiple suppliers with deterministic order processing times is determined. A numerical study conducted shows that risk sharing and proper safety stock placement lead to better system coordination and improve system performance.     

Developing environmental and social performance: the role of suppliers’ sustainability and buyer–supplier trust

We explore how environmental and social performance of manufacturing firms can be improved as sustainable supply chain management (SSCM) develops and evolves within a firm from internal to external practices. Importantly, this study considers how key suppliers’ sustainability performance and buyer–supplier trust mediate and moderate such a development. A conceptual framework is developed which relies on resource-based theories and emerging empirical evidence. Then, partial least square methodology is applied on survey data from a sample of Italian manufacturing firms. Results show that manufacturing firms’ sustainability performance improves as SSCM develops; however, while internal practices have a direct impact on performance, the effect of external practices on a manufacturing firm’s sustainability performance is fully mediated by key suppliers’ sustainability performance. Yet, buyer–supplier trust significantly influences the scope of such gains. Since evidence suggests that manufacturing firms are still struggling with how to leverage supply chain innovation potential for sustainable development, this study provides a timely and valuable contribution.     

Ripple effect modelling of supplier disruption: integrated Markov chain and dynamic Bayesian network approach

The ripple effect can occur when a supplier base disruption cannot be localised and consequently propagates downstream the supply chain (SC), adversely affecting performance. While stress-testing of SC designs and assessment of their vulnerability to disruptions in a single-echelon-single-event setting is desirable and indeed critical for some firms, modelling the ripple effect impact in multi-echelon-correlated-events systems is becoming increasingly important. Notably, ripple effect assessment in multi-stage SCs is particularly challenged by the need to consider both vulnerability and recoverability capabilities at individual firms in the network. We construct a new model based on integration of Discrete-Time Markov Chain (DTMC) and a Dynamic Bayesian Network (DBN) to quantify the ripple effect. We use the DTMC to model the recovery and vulnerability of suppliers. The proposed DTMC model is then equalised with a DBN model in order to simulate the propagation behaviour of supplier disruption in the SC. Finally, we propose a metric that quantifies the ripple effect of supplier disruption on manufacturers in terms of total expected utility and service level. This ripple effect metric is applied to two case studies and analysed. The findings suggest that our model can be of value in uncovering latent high-risk paths in the SC, analysing the performance impact of both a disruption and its propagation, and prioritising contingency and recovery policies.     

A hybrid multi-agent negotiation protocol supporting supplier selection for multiple products with synergy effect

Supplier selection is an important problem in supply chain management. In practice, it is common for a purchasing company to procure a bundle of products simultaneously. In this regard, synergy effect could exist between products and hence affect the final choice of suppliers. It is therefore necessary to incorporate the synergy effect between products in supplier selection process. Agent-based negotiation models are applied to automate supplier selection process. Negotiation protocol is an essential component should be considered when building an effective agent negotiation model. The objective of this research is to propose a negotiation protocol special for multi-product supplier selection problem. The negotiation protocol is a hybrid multi-agent protocol of combinatorial procurement auction protocol and multi-bilateral bargaining protocol. The negotiation protocol is able to support the purchasing company and suppliers negotiate on the concrete commitments of multiple products simultaneously, and select suppliers for multiple products. In addition, both the purchasing company and suppliers can express their preferences on the synergy effect between products in negotiation process by adopting the negotiation protocol. Simulation is conducted to demonstrate the effectiveness and efficiency of the negotiation protocol.     

Horizontal cooperation and information sharing between suppliers in the manufacturer–supplier triad

In this paper, we analyse a collusion and information-sharing problem between two suppliers in a manufacturer–supplier triad. The manufacturer treats one supplier as a strategic supplier and the other as a backup. While the strategic supplier offers modules of good quality but longer lead times, the backup supplier offers modules with inferior quality but shorter lead times. If there are urgent orders, the manufacturer must turn to the backup supplier. However, it is difficult for the manufacturer to estimate whether the urgent supplier has put extra effort into their production. We formulate this problem by assuming that the urgent supplier has either low or high production costs. To take advantage of the competition between two suppliers, the manufacturer can design a contract menu that defines total payment and lead times, under which both suppliers may be worse off. Meanwhile, it is possible for the suppliers to tacitly form a coalition, and to even share the private cost information. We study this problem by formulating it as a three-stage game. Furthermore, we investigate the variation of profits for each part of the supply chain. We find that the manufacturer is worse off when suppliers cooperate or share private information. Both suppliers, however, can benefit from cooperation and information sharing.     

Proactive and reactive purchasing planning under dependent demand,price, and yield risks

The trend of globalization and outsourcing makes supply unreliable and companies begin to have supplier diversity embedded into their procurement departments. Traditionally, contract suppliers are a major supply channel for many companies, while the effectiveness of reactive supply sources, such as spot markets, is often ignored. Spot markets have negligible lead times and higher average prices comparing with contract suppliers. In our research, procurement utilizes the combinatorial benefits of proactive supply (a contract supplier) and reactive supply (a spot market). The uncertainties of yields, spot prices, and demand, and the correlations among them are also taken into consideration when designing procurement plans. The objectives of this paper were to evaluate the effectiveness of dealing with uncertain supply using the spot market along with the contract supplier and to model the dependences among all the potential uncertainties. This research also seeks high expected profits without overlooking the associated variances. The analytical expression to determine the optimal order quantity is obtained under the most general situations where commodities can be both bought and sold via the spot market. Some properties are derived to provide useful managerial insights. In addition, reference scenarios, such as pure contract sourcing and the spot market restricted for buying or selling only, are included for comparison purposes.     

A supplier pre-selection model for multiple products with synergy effect

In practice, it is common for companies to purchase multiple products simultaneously. For the multiple required products, a large number of interested suppliers are involved. It is necessary for the purchasing company to shortlist a small number of qualified and competitive potential suppliers prior to finalising the suppliers for order fulfilment. In addition, synergy effect which is an effect arising between two or more products that produce an effect greater than the sum of their individual effects, could exist in the multi-product supplier selection environment. Since synergy effect between products can affect the choice of suppliers, it is also necessary to incorporate the synergy effect between products in the supplier selection for multiple products. However, few research efforts have been focused on the supplier pre-selection problem, let alone explicitly for multiple products with synergy effect. This paper presents a supplier pre-selection model for multiple products with synergy effect. The model is able to evaluate interested suppliers on the multiple pre-selection criteria, by the fuzzy Technique for Order Preference by Similarity to Ideal Solution (TOPSIS)-based supplier pre-selection algorithm, and shortlist a small number of potential suppliers. Illustrative examples are conducted to demonstrate the function and application of the supplier pre-selection model for multiple products with synergy effect.