A two-way approach to supply chain partner selection

All organisations face partner selection. It is the first step in establishing partnership. Over recent decades, a one-way selection approach has been dominant in the literature. It is assumed that a buyer searches for one or more suppliers from a set of suppliers. Once the best supplier is found and selected, a partnership is formed. However, in reality, not only is the selection not a one-way process as the relationship itself is bilateral, but the existence of other buyers and suppliers also needs to be taken into account. In this study, a two-way partner selection approach is proposed, where not only the buyers evaluate suppliers, but also the suppliers have the opportunity to evaluate buyers. Considering a marketplace where there are several buyers and suppliers, an integrative model is proposed in the form of an assignment model to optimally match all the buyers and suppliers. A generalised model is also formulated to take the suppliers’ capacity and buyers’ demand into account. The proposed models are illustrated using some numerical examples. Finally, conclusions and recommendations for future research are provided.     

Co-procurement: making the most of collaborative procurement

While the procurement decision is generally made by individual buyers, this study investigates how a group of buyers can make a shared decision. We call this collaborative approach, co-procurement. A mathematical model is formulated for the decision of procurement from multiple suppliers. The model is solved for individual buyers. The outcome shows the optimal number of items a buyer should buy from different suppliers such that the total cost is minimised for that buyer. Next, it is investigated how a group of buyers could make this decision together. The proposed model takes into account transaction costs of collaboration, to determine the optimal size of the collaboration and the involved parties. The idea is new in the old direction of procurement and it introduces the concept of transaction costs in this area and analyses its impact on the optimal collaboration size and mix. A case study from Dutch Food Valley is provided to investigate the benefits of co-procurement and validate the developed structure. The results indicate that co-procurement can bring considerable cost-savings through consolidation of orders and more efficient transportation schedules. A sensitivity analysis is conducted to determine the impact of changes in the transaction cost in favour of the co-procurement.     

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.     

Bootstrap approach for supplier selection based on production yield

Current manufacturing industries have increased their level of out-sourcing and relied more heavily on their supply chain as a source of competitive advantage. Supplier selection decisions have become an important component of production management. Those decisions have a significant impact on a firm's marketing competition, and suppliers may account for a large portion of the production cost. Production quality is one of the key factors in supplier evaluation. The manual of supplier certification includes a discussion of process capability analysis, which recommends a procedure for evaluating the most prevalent process capability index C _pk. However, the recommended procedure is applicable only when evaluating an individual supplier's performance. In this paper, we apply the bootstrap method to the supplier selection problem. We construct lower confidence intervals for the capability difference and ratio between two given suppliers. Performance comparisons are made among various bootstrap methods in terms of error probability and selection power. For convenience of applications, the sample sizes required for various designated selection power are also tabulated.     

A branch-and-bound algorithm for the concave cost supply problem

Effective supplier selection and allocation of order quantity among multiple suppliers are indispensable to the success of a manufacturing company. While companies have begun to turn into a comprehensive multi-criteria approach, most buyers still consider purchasing cost to be their primary concern in selecting their suppliers. In this paper, we consider the concave cost supply problem where a manufacturer seeks to select the suppliers and simultaneously procure the quantity of material/component required for production at the minimum total cost during a standard production period. We provide and validate an effective and efficient branch-and-bound algorithm that is finite and that finds the global optimal solution of the problem without any restrictions on the cost functions or on the set of input parameters used in the problem. Numerical experiments are conducted to evaluate the performance of the proposed algorithm.     

The use of rush deliveries in periodic review assemble-to-order systems

We calculate optimal safety stock in a periodic review (T,S) assemble-to-order system having multiple components and multiple finished goods (FGs). Customer orders for FGs arrive according to independent Poisson processes, and cannot be neither backlogged nor lost. In case of potential component stock-out, the studied system uses rush deliveries from suppliers. For this setting, approximate expressions of the optimal safety stock that minimise the sum of inventory holding and rush ordering costs are developed. Exact optimal safety stocks are calculated using Discrete Event Simulation, and compared numerically to the approximate expressions. The model is applied to a first-tier automotive supplier and yields to a significant reduction in terms of inventory holding and rush ordering costs. A sensitivity analysis on relevant system parameters such as components demand, assembly coefficients and unit rush ordering cost is conducted.     

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.     

Procedure for supplier selection based on Cpm applied to super twisted nematic liquid crystal display processes

The loss-based process capability index C _pm , sometimes called the Taguchi index, has been proposed to the manufacturing industry as a method to measure process performance. The index C _pm takes into account the targeting degree of the process, which essentially measures process performance based on average process loss. Based on the C _pm index, a mathematically complicated approximation method was developed previously for selecting a subset of processes containing the best supplier from a given set of processes. The present paper implements this method and develops a practical step-by-step procedure to aid supplier selection decisions. The accuracy of the selection method is investigated using a simulation technique. The accuracy study provides useful information about the sample size required for a designated selection power. A two-phase selection procedure is developed to select a better supplier and to examine the magnitude of the difference between the two suppliers. Also investigated is a real-world case on the super twisted nematic liquid crystal display manufacturing process, and it is applied to the selection procedure using actual data collected from the factories to reach a decision in supplier selection.     

Evaluating Six Sigma failure rate for inverse Gaussian cycle times

Six Sigma is a quality philosophy and methodology that aims to achieve operational excellence and delighted customers. The cost of poor quality depends on the sigma quality level and its corresponding failure rate. Six Sigma provides a well-defined target of 3.4 defects per million. This failure rate is commonly evaluated under the assumption that the process is normally distributed and its specifications are two-sided. However, these assumptions may lead to implementation of quality-improvement strategies that are based on inaccurate evaluations of quality costs and profits. This paper defines the relationship between failure rate and sigma quality level for inverse Gaussian processes. The inverse Gaussian distribution has considerable applications in describing cycle times, product life, employee service times, and so on. We show that for these processes attaining Six Sigma target failure rate requires higher quality efforts than for normal processes. A generic model is presented to characterise cycle times in manufacturing systems. In this model, the asymptotic production is described by a drifted Brownian motion, and the cycle time is evaluated by using the first passage time theory of a Wiener process to a boundary. The proposed method estimates the right efforts required to reach Six Sigma goals.     

Comparing the lens displacement profile data by using the sequential approach for selecting alternative suppliers

The lens module is a critical part of the camera module. The quality of the lens module significantly influences the auto-focus and image stability functions of the camera module. A new approach that uses sequential tests is proposed to select the alternative suppliers that provide the qualified parts as the current supplier under the linear profile data. Having several qualified alternative suppliers can reduce the dependency on one supplier, improve bargaining power, and reduce capacity risk. The lens displacement that has a linear relationship with current is the quality characteristic for evaluating the lens module suppliers. To select the qualified alternative suppliers, the proposed sequential approach tests the profile difference between the current supplier and the investigated suppliers. The simulation results show that the power of the sequential approach is higher than the simultaneous confidence bands method in differentiating profiles. Last, the proposed approach is effectively applied to select the qualified alternative lens module suppliers for the camera module manufacturer. Procuring the lens module from the selected suppliers can maintain production quality and flexibility for the camera module manufacturer in practice.     

Collaboration in humanitarian supply chains: an organisational culture framework

The purpose of this study was to determine the impact that institutional logics and, more specifically, organisational culture can have on humanitarian supply chain (HSC) collaboration. A framework was developed that explicates buyer–supplier collaboration in a humanitarian setting. Twenty-nine semi-structured interviews were conducted with buyers and suppliers. The data indicated that in a HSC, collaborative outcomes, such as new product development, inventory management, and product/service delivery, are influenced by the buyers’ and suppliers’ organisational cultures. Based on suppliers’ characteristics, they can be classified as humanitarian suppliers, commercial suppliers, and humanitarian and commercial suppliers. These groups have distinct organisational cultures. An unexpected finding is that suppliers that serve commercial buyers primarily claim to have encountered no issues in supply chain collaboration with humanitarian buyers, although they have different types of organisational cultures. The factors that lead to successful collaboration are identified as trust, commitment, information sharing and mutual respect. Simultaneously, dominant institutional logics are observed in the dyadic relationship.     

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.     

Sustainable Supplier Selection Model in Supply Chains During the COVID-19 Pandemic

As global supply chains become more developed and complicated, supplier quality has become increasingly influential on the competitiveness of businesses during the Covid-19 pandemic. Consequently, supplier selection is an increasingly important process for any business around the globe. Choosing a supplier is a complex decision that can result in lower procurement costs and increased profits without increasing the cost or lowering the quality of the product. However, these decision-making problems can be complicated in cases with multiple potential suppliers. Vietnam's textile and garment industry, for example, has made rapid progress in recent years but is still facing great difficulties as the supply of raw materials and machinery depends heavily on foreign countries. Therefore, it is extremely important for textile and garment manufacturing companies in Vietnam to implement an effective supplier evaluation and selection process. While multicriteria decision-making models are frequently employed to assist with supplier evaluation and selection problems, few of these models consider the problem under the condition of a fuzzy decision-making environment. The aim of this paper is to create a hybrid MCDM model using the Fuzzy Analytical Hierarchy Process (FAHP) model and the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) to assist the supplier selection process in the garment industry in a fuzzy decision-making environment. In this study, the FAHP method is used to evaluate the performance and the weight of each criterion. TOPSIS is then used to rank all potential suppliers. The proposed model is then applied to a real-world case study to demonstrate both the process of calculation as well as its real-world applicability. The results from the case study provide empirical evidence that the model is feasible. The proposed approach can also be used in combination with other MCDM models to better support decision makers and can be modified to be applied in similar supplier selection processes for different industries.     

Risk, risk aversion and the optimal time to produce

This paper studies the order-fulfillment process of a supplier producing a customized capital good. When they decide at what time to begin production, suppliers in these industries typically face the following dilemma. On the one hand, their customers expect them to be responsive and the time that they are prepared to wait for the product is much shorter than the time needed to produce and deliver it. On the other hand, it is risky for the suppliers to start production before the customers confirm their orders due to inventory holding costs and the possibility of order cancellation. We offer a model to help understand this dilemma and investigate the comparative statics effects of lead time, lead time uncertainty and the risk aversion of the supplier. Relative to existing work, our model has two novel components: demand distribution updating and the supplier's risk attitude. Previous empirical studies reveal that the supplier is very conservative when commencing the order fulfillment. The studies attribute this to high holding and cancellation costs relative to the delay cost. Our model provides two alternative explanations. First, other than costs, when the supplier starts to produce depends also on how the distribution of the demand arrival time is updated as time progresses. Second, although the effect of increasing risk aversion of the supplier on the optimal time to produce is ambiguous, we show that it plays a major role in the decision and thus it alone may have caused the supplier to be conservative.     

Supplier selection by testing the process incapability index

In the competitive global business environment of the 21st century, enterprises must respond effectively to customer demands. The selection of suppliers and the evaluation of their performance are becoming major challenges that face manufacturing managers. Assessing a group of suppliers and selecting one or more of them is a complex task because various criteria must be considered in the decision making process. Quality is an essential factor in qualifying a corporation to enter the marketplace. In fact, the quality of parts obtained from suppliers determines the quality of the finished product. Hence, quality is the fundamental factor for supplier evaluation among various criteria. This study applies the process incapability index C_pp to develop an evaluation model that assesses the quality performance of suppliers. The model simplifies the evaluation of suppliers, facilitates their effective selection, and provides insights into the process situation of suppliers who may enter into a long-term partnership with a company.     

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.     

Six Sigma in industry: some observations after twenty‐five years

Six Sigma has enjoyed considerable popularity in the industry for about a quarter of a century. While the standard contents of Six Sigma have been described and discussed widely, some little articulated aspects of Six Sigma implementation deserve the attention of serious practitioners. In this paper, a ‘5W+1H’ (What, Why, When Where, Who, How) format is used to elucidate the nature of Six Sigma in a non‐mathematical discussion, followed by observations peculiar to the usual mode of development of Six Sigma professionals. It is pointed out that Six Sigma has Statistical Thinking as its foundation; for Six Sigma and its associated frameworks such as Design for Six Sigma and Lean Six Sigma to continue to be effective, it is important that users have a clear understanding of the nature of Six Sigma and be able to address the related challenges in practice. Copyright © 2010 John Wiley & Sons, Ltd.     

Developing a resilient supply chain through supplier flexibility and reliability assessment

In this study, we examine the optimal allocation of demand across a set of suppliers in a supply chain that is exposed to supply risk and environmental risk. A two-stage mixed-integer programming model is used to develop a flexible sourcing strategy under disruptions. Our model integrates supplier selection and demand allocation with transportation channel selection and provides contingency plans to mitigate the negative impacts of disruptions and minimise total network costs. Finally, a numerical example is presented to illustrate the model and provide insights. The findings suggest that developing contingency plans using flexibility in suppliers’ production capacity is an effective strategy for firms to mitigate the severity of disruptions. We also show that flexibility and reliability of the suppliers and regions play a significant role in determining contingency plans for during disruption. Findings generally show that highly flexible suppliers receive less allocation, and their flexible capacity is reserved for disruptions. For firms that do not incorporate risk management into supplier selection and allocation, the recommendation is to source from fewer, more reliable suppliers with less risk of disruption. Our findings also emphasise that the type of disruption has important implications for supplier selection and demand allocation. This study highlights the supply chain risk management strategy of regionalising as a means for minimising the impact of environmental disruptions.     

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.     

The economic lot and delivery scheduling problem: models for nested schedules

We investigate the problem of simultaneously determining schedules for the production of several assembly components at a captive supplier and delivery of those components to the customer. We consider situations in which production economies of scale in the form of setup costs and/or setup times make it desirable for the supplier to produce in batches that are larger than the desired order quantity of the customer. The objective is to minimize the average cost per unit time of transportation, inventory at both the customer and the supplier, and, where applicable, setup costs.

We develop a heuristic solution procedure and a lower bounding approach for this problem. We also report experimental results that indicate that the heuristic provides solutions close to the lower bound in most instances. Our results provide a means to answer the often-asked question of whether just-in-time suppliers are (or should be) asked to hold inventory for their customers, and the question of how much setup costs and setup times need to be reduced so that the suppliers no longer need to hold that inventory.