Fuzzy QFD for supply chain management with reliability consideration

Although many products are made through several tiers of supply chains, a systematic way of handling reliability issues in a various product planning stage has drawn attention, only recently, in the context of supply chain management (SCM). The main objective of this paper is to develop a fuzzy quality function deployment (QFD) model in order to convey fuzzy relationship between customers needs and design specification for reliability in the context of SCM. A fuzzy multi criteria decision-making procedure is proposed and is applied to find a set of optimal solution with respect to the performance of the reliability test needed in CRT design. It is expected that the proposed approach can make significant contributions on the following areas: effectively communicating with technical personnel and users; developing relatively error-free reliability review system; and creating consistent and complete documentation for design for reliability.     

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.     

Algorithm for constructing a delivery-sequencing/inventory-allocation plan for supply chain control in the operational planning level

This paper aims to propose an algorithm to construct a delivery-sequencing/inventory-allocation plan used to control a supply chain in the operational planning level. The algorithm which is mainly based on the improving search technique begins by determining a suitable initial sequence of customer orders, allocating available inventory and determining inventory replenishment plan according to the sequence, calculating the interesting goals, and finally searching the appropriate sequence of customer orders using a proposed pairwise interchange technique. The sequence of the customer order is considered appropriate if it can simultaneously give most preferable two goals: minimizing the total penalties paid by the supply chain, and minimizing the average cost of fulfilling each product unit transferred to customers. The efficiency of the proposed algorithm is tested by the numerical experiments based on real data from a selected supply chain in Thailand, namely the food-ingredient industry. Statistical results show that the proposed algorithm significantly outperforms the current planning heuristics used in the industry and some other well-known heuristics.     

On measuring company performance within a supply chain

Emerging research strengthens the connection between supply chain performance and a company's financial performance (D’Avanzo, R., Von Lewinski, H. and Van Wassenhove, L. N., 2003. The link between supply chain and financial performance. Supply Chain Management Review, November/December, 40–47). The focus on integrating functional internal processes has expanded to include the need for integrating these with external processes of business partners (Edwards, P., Peters, M. and Sharman, G., 2001. The effectiveness of information systems in supporting the extended supply chain. Journal of Business Logistics, 22(1), 1–27). This need for enterprise efficiency is compelling companies to review, to identify, and to adopt supply chain initiatives. This research investigates the use of common measurement metrics in an attempt to determine which one(s) are most useful for measuring performance as companies implement SCM practices. For firms that were engaged in SCM we found inventory and cycle time to be the most significant metrics.     

Value of information exchange and synchronization in a multi-tier supply chain

We investigate the value of various information exchange mechanisms in a four-echelon supply chain under a material requirements planning framework. In the absence of any information sharing, each echelon would develop its own forecasts and plan its inventories based on the history of actual demand from its downstream customer (or echelon). Through a simulation study, we compare this policy with policies where each echelon has access to (i) the end-user demand history and (ii) the planned order schedule of the downstream echelon. Among all the demand information exchange mechanisms, planning inventories based on the planned downstream order schedules resulted in the lowest average inventory level for the entire supply chain. However, use of end-user demand history to forecast and plan inventories at all echelons resulted in the lowest total cost. In addition to the information exchange mechanisms, a simple synchronized replenishment system was considered and evaluated in the study. In the synchronized system, the retailer determines a fixed order interval and the upper echelons replenish only at integer multiples of this interval. The study found that synchronized inventory replenishments among the echelons, even without any exchange of demand information, can bring about more benefits and cost reduction than any of the information exchange mechanisms.     

Assembly tolerance allocation using a coalitional game method

Assembly tolerance allocation in modern manufacturing industries is important because it directly affects product quality and manufacturing cost. Loose tolerances may cause quality deficiency while tight tolerances can increase the cost. It is significant to develop a reasonable tolerance allocation strategy for every assembly component combining the cost and quality demands. Traditionally, designers often adopt the single objective optimization with some kind of constraint or establish a comprehensive evaluation function combining several optimization objectives with different weights to solve the tolerance allocation problem. These approaches may not be desirable as it is difficult to adequately consider the interaction and conflict between the cost and quality demands. In this article, an assembly tolerance allocation method using coalitional game theory is proposed in an attempt to find a trade-off between the assembly cost and the assembly quality. First, the assembly tolerance allocation problem is formulated as a multi-objective optimization problem and the concept of the Pareto-optimal solution is introduced. Then, how the assembly tolerance allocation model is transformed into a coalitional game model is discussed, and a key technique of transforming the tolerance design variables into the game strategies is presented. Further, the Shapley value method of coalitional game based on each player's contribution evaluation to the profit of the whole coalition is given. Finally, the feasibility of the procedure is demonstrated through an example of vehicle front structure assembly.     

Modelling a complex supply chain: understanding the effect of simplified assumptions

The benefits of coordinating activities and consolidating distribution points in supply chains are well highlighted and intuitively logical. However, the impact of these decisions on the overall performance of a complex supply chain may not be as obvious as usually perceived. This study models a relatively complex supply chain and evaluates the impact of simplifying demand and lead time assumptions under various supply chain configurations. Of particular interest is the investigation of the effect of risk pooling and the synchronization of production cycles in a multi-level multi-retailer supply chain under the influence of various parameters such as batch size, delivery frequency and ordering cycle. This study highlights the extent of complicated interaction effects among various factors exist in a complex supply chain and shows that that the intricacy of these effects can be better understood with a simulation model.     

Using a just-in-time selling strategy to strengthen supply chain linkages

A two-stage JIT-selling strategy is proposed as an alternative for strengthening buyer–seller linkages throughout the supply chain. The impact of implementation of such a strategy on organizational performance is investigated. Stage 1 of the JIT-selling strategy requires implementation and execution of selling tactics that build value during the selling process based on the organization's JIT related capabilities, such as zero-defect production, on-time delivery and quantity precision. Stage 2 requires development of single-source relationships with customers that result in the full integration of on-site sales representatives into customers’ purchasing processes. Data related to implementation of the JIT-selling strategy and organizational performance were collected from 175 manufacturers, and the relationship between the constructs was assessed using correlation and structural equation modelling techniques. Results support the proposition that implementation of a JIT-selling strategy to strengthen supply chain linkages will result in improved organizational performance.     

Comprehensive framework for the development of a supply chain strategy

Current competition among companies is fought through their supply chains. As the performance of the supply chain depends not only on manufacturing and marketing attributes, it becomes necessary to establish a framework upon which to develop a supply chain strategy. The paper presents the rationale and principles of a customer–product–process–resource (CPPR) framework for the simultaneous analysis of the business, supplier, manufacturing, planning, marketing and customer dimensions of a supply chain strategy. The originality of the CPPR framework is that it establishes a set of supply chain structural elements, that when put together determine the degree of alignment of a supply chain strategy. As the main objective of a supply chain strategy is to achieve customer satisfaction as an output of the supply chain operations, the CPPR framework becomes a realignment tool when used in combination with a realignment methodology, which is also presented in the paper.     

A technology selection framework for integrating manufacturing within a supply chain

This paper describes a structured analytical approach for selecting a manufacturing technology. A framework consisting of six integrated steps is proposed by considering the growing importance of supply chains in manufacturing organisations. The framework makes use of the analytical hierarchy process (AHP) approach combined with strategic assessment model (SAM) to evaluate and select the technologies appropriate for providing overall competitive advantage. The framework is intended to assist industrial managers in promoting manufacturing and supply chain collaboration and co-ordination by including intra-organisational perspective in their organisational technology selection decision making process.     

Pricing decisions of complementary products in a two-level fuzzy supply chain

Pricing decisions of two complementary products in a two-level fuzzy supply chain with two manufacturers and one common retailer are studied in this paper. By considering the two manufacturers and one common retailer’s leader–follower relationship, the two manufacturers’ pricing strategy and the fuzzy uncertainties associated with the manufacturing costs and customer demands of the complementary products, seven pricing games are considered. The corresponding closed-form optimal pricing decisions are obtained in the seven pricing games. Through using numerical studies and sensitivity analysis of parameters’ fuzzy degree, we compare the analytical results of different games and investigate the firms’ optimal decisions facing changing pricing environments. At last, we analyse the effect of the fuzzy degree of key parameters on optimal prices, maximal expected demands and maximal expected profits of different games. Some interesting and valuable managerial insights are established.     

Coordination of a supply chain with loss-averse consumers in service quality

We develop a two-period game model to study the coordination mechanism for a supply chain with loss-averse consumers who are assumed to have dwindling sensitivity to service quality gain relative to loss. We find that all-unit quantity discount coupling with service subsidy rate can coordinate the retailer’s price and service quality decisions together in each period. When consumers become more loss-averse in service quality, the coordinated wholesale price in the first period might increase; whereas that in the second period decreases. With Pareto coordination mechanism, larger loss-aversion might weaken the supplier’s bargaining power. We provide managerial insights on how to adjust the coordinated contract when the consumers’ loss-aversion and reference value of service quality level change.     

Performance optimization of a leagility inspired supply chain model: a CFGTSA algorithm based approach

Lean and agile principles have attracted considerable interest in the past few decades. Industrial sectors throughout the world are upgrading to these principles to enhance their performance, since they have been proven to be efficient in handling supply chains. However, the present market trend demands a more robust strategy incorporating the salient features of both lean and agile principles. Inspired by these, the leagility principle has emerged, encapsulating both lean and agile features. The present work proposes a leagile supply chain based model for manufacturing industries. The paper emphasizes the various aspects of leagile supply chain modeling and implementation and proposes a new Hybrid Chaos-based Fast Genetic Tabu Simulated Annealing (CFGTSA) algorithm to solve the complex scheduling problem prevailing in the leagile environment. The proposed CFGTSA algorithm is compared with the GA, SA, TS and Hybrid Tabu SA algorithms to demonstrate its efficacy in handling complex scheduling problems.     

Budget allocation in coping with supply chain disruption risks

Disruption management, as an important research topic, has attracted scholars’ broad attention in recent years due to the increasing exposure of disruption risks in supply chains. To date, researches in this field often focus on either prevention or mitigation measures and the budget allocation problem is paid relatively little attention. This paper therefore proposes an approach to determine the optimal budget allocation based on prevention measures in combination with mitigation measures. First, considering different disruption situations, the bow-tie is applied to developing the disruption management frameworks that integrate risk prevention and risk mitigation. Second, the corresponding optimization models are formulated to determine the optimal budget allocation plans. In order to validate the proposed approach, we compare the computation results with those obtained from the prevention approach and the mitigation approach. Also, random experiments are conducted to analyse the impacts of randomly generated disruption and response scenarios. Finally, a real-life case is provided to testify the usefulness and merits of our proposed approach. The results show that the proposed approach can help decision-makers reduce more loss caused by the disruption risks.     

A strategic decision framework for a value added supply chain

Supply chains are becoming increasingly complex. The structure of the supply chain and the suppliers who participate in it are critical decisions for managers. The supply chain is no longer simply a source of inputs or services but an integral source of value added. It is clear that in some cases strategic supply chain objectives may require trade-offs, for example, between cost and innovation capability or between managing risk and maximising flexibility. These decisions balancing trade-offs between desirable partner characteristics are critical and can make a significant contribution to business performance. A framework is outlined, based on the foundation of extant literature, within which firms can make strategic decisions on supply chain structure by categorising the characteristics they prioritise in their supply chain strategy. There is also a strong foundation in the literature on developing mathematical models that provide insight into the decision-making process. A mixed integer programming model is specified that incorporates the opportunity for diversification and provides a demand allocation decision. The model is robust enough to allow for single or diversified supplier strategies based not only on capacity constraints but also on risk pooling and minimum performance requirements for key characteristics that form the basis of the strategy. A Lagrangian relaxation is proposed and satisfactory performance results are provided.     

Integrated inventory models with fuzzy annual demand and fuzzy production rate in a supply chain

The successful implementation of Just-in-time (JIT) production in today's supply chain environment requires a new spirit of cooperation between the buyer and the vendor. An integrated inventory model with such a consideration is based on the total cost optimization under a common stock policy and business formula. However, the supposition of known annual demand in most related literature may not be realistic. This paper proposes the inclusion of fuzzy annual demand and/or the production rate, and then employs the signed distance, a ranking method for fuzzy numbers, to find the estimate of the common total cost in the fuzzy sense, and subsequently derives the corresponding optimal buyer's quantity and the integer number of lots in which the items are delivered from the vendor to the purchaser. Numerical examples are provided to illustrate the results of proposed models.     

Order allocation in purchasing management: a review of state-of-the-art studies from a supply chain perspective

Supplier selection (SS) and order allocation (OA) are strategic decisions that have a substantial effect on a company’s performance. However, order allocation is often neglected, since it results from supplier selection and is considered supplementary: little attention has been paid to its specific nature and complexity. Consequently, the authors conducted a systematic literature review specifically regarding order allocation methods. The research aimed to evaluate how often and when the issue has been dignified with an individual focus, independently of the supplier selection problem. This study conducted a comprehensive examination of the order allocation models and solutions, criteria for order quantity allocation, features of suppliers, items, planning periods, and demand most commonly considered in the literature. Finally, it aimed to discover whether supply chain configurations and trends have been considered in efforts to find a solution to the problem. The scientific contribution of this study is threefold: (i) to expand the review of scientific literature regarding order allocation models, (ii) to identify research gaps and highlight research opportunities, and (iii) to suggest a research agenda for the development of order allocation models according to the requirements of current trends in supply chain management.     

Optimal pricing and trade-in policies in a dual-channel supply chain when considering market segmentation

Many companies are implementing trade-in programmes through multiple channels. This may ultimately lead to fiercer channel conflict and competition. Few studies have explored firms’ optimal trade-in policies in such an environment. To fill the gap, we build a theoretical model that captures the features of a dual-channel situation in which a manufacturer implements a trade-in programme through retail and direct channels simultaneously. Compared with the case in which there is no trade-in rebate, the results show that a trade-in programme can intensify or mitigate the double marginalisation effect if the retailer can initially decide the trade-in rebate in the retail channel. This significantly relies on market segmentation. However, when the retailer cannot decide the trade-in rebate in the retail channel, the trade-in programme aggravates the double marginalisation effect. Second, the trade-in rebate offered by the retailer may be higher than the subsidy offered by the manufacturer, as long as the retailer can autonomously decide the trade-in rebate in the retail channel. Furthermore, we find that both the manufacturer and retailer prefer to obtain the right to autonomously decide the trade-in rebate in the retail channel, but the supply chain prefers that the manufacturer do it. Some numerical examples are provided to further explain these outcomes.     

Investigation of relationships in a supply chain in order to improve environmental performance

This paper presents a methodology to combine environmental assessment information and knowledge on supplier relationships. The work is based on a case study of production of a chair. The methods used are shown to be effective to reduce the number of suppliers that should be managed from an environmental point of view and also obtain an overview over which suppliers that can be influenced. It is also shown how suppliers with the presumably highest potential for improvements are identified. The end-producer can thus obtain control over most of the environmental impact originating from upstream activities through a limited number of suppliers. In the case study the number of suppliers that should be managed is reduced to 3. Small and medium sized enterprises have often limited possibilities to influence the suppliers, but in this paper it is demonstrated how this problem can be overcome by cooperative purchasing within a branch of industry with a common demand for information from the suppliers.

Application of control theoretic principles to manage inventory replenishment in a supply chain

Using uncertain real-time information to update supply chain operational policies creates a need for developing dynamic supply chain management capabilities that increase responsiveness to demand and decrease volatility of the replenishment process (popularly known as the Bullwhip Effect). To this end, we explore the use of control theoretic principles to manage the inventory replenishment process in a supply chain under different forecast situations. We study the use of proportional, proportional-integral and proportional-derivative control schemes to determine the conditions under which specific control actions are beneficial. Analytical models and simulation runs are used to study the trade-off between responsiveness to demand and volatility. Our analysis indicates that using proportional control to manage inventory replenishment is suitable for high forecast error situations. Proportional control along with integral control works well in situations where the forecast bias is relatively higher than the forecast error. Proportional control along with derivative control works best in situations with moderate forecast errors.