Assembly Supply Chain Research Articles

Supply Coordination and Optimization Model of Assembly Supply Chain Based on Different Delivery Policies

After analysis and description of delivery policy 1 that the manufacturer takes charge of the cost caused by compressing lead time,and delivery policy 2 that the manufacturer and suppliers both takes charge of the cost,supply coordination model of assembly supply chain based on two-supplier and one manufacturer under different delivery policies are established.The stackelberg model of assembly supply chain based on two-suppliers and one-manufacturer is constructed according to policy 1 and the optimal decision of each side is given.According to policy 2 the joint inventory model of assembly supply chain based on two-suppliers and one-manufacturer system is built up,and the algorithm of optimal solution is given.Then range of the cost sharing coefficient is given after analysis of the situation that policy 2 is superior to policy 1,and then the coordination policy of asymmetric nash equilibrium is put forward based on adapted expected utility theory.The two delivery policies are compared and the sharing collaborative policy is proved effective in numerical example.

Impact of Demand Uncertainty on Stability of Supplier Alliances in Assembly Models

In their recent paper, Nagarajan and Sosic (2009) study an assembly supply chain in which suppliers sell complementary components to a downstream assembler, who faces a price-sensitive deterministic demand. Suppliers may form alliances, and each alliance then sells a kit of components to the assembler and determines the price for that kit. The assembler buys the components (kits) from the alliances and sets the selling price of the product. Nagarajan and Sosic consider three modes of competition – Supplier Stackelberg, Vertical Nash, and Assembler Stackelberg models – which correspond to different power structures in the market, and study stable supplier alliances when the assembler faces linear and isoelastic demand.In this paper, we study the impact that demand uncertainty has on stability results obtained in Nagarajan and Sosic (2009). We first analyze models in which all decisions are made before the uncertainty is resolved, and show that the alliance of all suppliers remains stable when demand is isoelastic, or under Stackelberg models when demand is linear. However, demand uncertainty may change stability results when both parties make decisions simultaneously (Vertical Nash model) and demand is linear. We then extend our results by considering scenarios in which some decisions may be postponed and made after the actual demand is known. When the ordering quantity can be determined after observing the true demand, we show that stable outcomes correspond to those obtained in the deterministic case and uncertainty has no impact on coalition stability; if only the assembler's pricing decision is postponed, we need additional conditions for stability results to carry over in the additive demand model.

Game-theoretic analyses of decentralized assembly supply chains: Non-cooperative equilibria vs. coordination with cost-sharing contracts

This paper considers a multiple-supplier, single manufacturer assembly supply chain where the suppliers produce components of a short life-cycle product which is assembled by the manufacturer. In this single-period problem the suppliers determine their production quantities and the manufacturer chooses the retail price. We assume that the manufacturer faces a random price-dependent demand in either additive or multiplicative form. For each case, we analyze both simultaneous-move and leader–follower games to respectively determine the Nash and Stackelberg equilibria, and find the globally-optimal solution that maximizes the system-wide expected profit. Then, we introduce appropriate buy-back and lost-sales cost-sharing contracts to coordinate this assembly supply chain, so that when all the suppliers and the manufacturer adopt their equilibrium solutions, the system-wide expected profit is maximized.

A Complexity Model for Assembly Supply Chains and Its Application to Configuration Design

A complexity measure for assembly supply chains has been proposed based on Shannon’s information entropy. This paper extends the definition of such a measure by incorporating the detailed information of the supply chain structure, the number of variants offered by each node in the supply chain, and the mix ratios of the variants at each node. The complexity measure is then applied to finding the optimal assembly supply chain configuration given the number of variants offered at the final assembler and the mix ratios of these variants. The optimal assembly supply chain configuration is theoretically studied in two special scenarios: (1) there is only one dominant variant among all the variants offered by the final assembler, and (2) demand shares are equal across all variants at the final assembler. It is shown that in the first scenario where one variant dominates the demand, the optimal assembly supply chain should be nonmodular; but in the scenario of equal demand shares, a modular supply chain is better than nonmodular one when the product variety is high. Finally a methodology is developed to find the optimal supply chain with/without assembly sequence constraints for general demands.

Optimal configuration of assembly supply chains using analytical target cascading

This paper proposes to apply analytical target cascading (ATC) for configuring assembly supply chains with convergent structures. Individual enterprises in a supply chain are represented as separate elements in an ATC hierarchy. They are able to maintain autonomous and heterogeneous decision systems for optimising their private decision variables and objectives. They collaborate vertically and laterally along the ATC hierarchy through their common decisions to achieve the overall consistency and optimality. ATC offers a competitive balance between computational efficiency and effectiveness while providing an opportunity for parallel computation to further improve the efficiency. This paper also investigates the feasibility for individual enterprises to set local targets while participating in the supply chain configuration (SCC). SCC usually involves discrete decision variables, causing significant difficulties for existing ATC techniques to achieve system consistency. Therefore, a new consistency scheme has to be proposed in this paper, including two techniques: importance weighting factor (IWF) and dynamic constraints (DC). A case study is used to demonstrate the application of the ATC method for solving typical SCC problems. A series of comparative analyses are conducted to identify the strengths of the ATC method and demonstrate the effectiveness of the proposed consistency scheme.

Supplier Competition in Decentralized Assembly Systems with Price-Sensitive and Uncertain Demand

In a decentralized assembly supply chain, independent suppliers produce a set of complementary components from which an assembler assembles a final product and sells it to the market. In such a channel, several competitive forces interact with one another to affect the price and quantity decisions of the firms involved. These include: (1) the direct competition each supplier faces for producing the same component, (2) the indirect competition among the suppliers producing the set of complementary components needed for assembling the final product, and (3) the vertical interaction between the assembler and the component suppliers. This paper shows that the direct competition that one supplier faces helps improve the performance of the assembler and all the other suppliers in the channel; and surprisingly, it can help improve the performance of this particular supplier facing the competition as well. Second, the assembler benefits from a merger of suppliers producing different components in the complementary set. Furthermore, the assembler prefers a merger of suppliers with less direct competition over a merger of suppliers with more direct competition.

Supply chain modeling in uncertain environment with bi-objective approach

Supply chain is viewed as a large-scale system that consists of production and inventory units, organized in a serial structure. Uncertainty is the main attribute in managing the supply chains. Managing a supply chain (SC) is very difficult, since various sources of uncertainty and complex interrelationships among various entities exist in the SC. Uncertainty may result from customer’s demand variability or unreliability in external suppliers. In this paper we develop an inventory model for an assembly supply chain network (each unit has at most one immediate successor, but any number of immediate predecessors) which fuzzy demand for single product in one hand and fuzzy reliability of external suppliers in other hand affect on determination of inventory policy in SCM. External supplier’s reliability has determined using a fuzzy expert system. Also the performance of supply chain is assessed by two criteria including total cost and fill rate. To solve this bi-criteria model, hybridization of multi-objective particle swarm optimization and simulation optimization is considered. Results indicate the efficiency of proposed approach in performance measurement.

Minimizing customer order lead-time in a two-stage assembly supply chain

Coordination across different process stages of the supply chain is becoming more common as the information needed for this coordination is easier to obtain and share. With the availability of this information, managers are beginning to recognize that there can be benefits to scheduling processes in a coordinated fashion. Thus, finding good schedules for the entire supply chain has added importance to today’s managers. Coordination of the material as it moves from one stage to the next should lead to improved customer order lead-time performance for the whole chain and thus better customer service overall. We look at a two-stage assembly supply chain with the objective of minimizing the average customer order lead-time. Minimizing lead-time is becoming increasingly important as customers demand quicker response. But beyond this better customer service objective, minimizing lead-time is consistent with keeping inventory costs low. We introduce a number of properties of optimal solutions, results for special problem cases, and a series of lower bounds. We also provide a number of intuitive heuristics for coordinated supply chain scheduling and test them to determine their effectiveness.

Competition in Multiechelon Assembly Supply Chains

In this paper, we study competition in multiechelon supply chains with an assembly structure. Firms in the supply chain are grouped into homogenous sectors (nodes) that contain identical firms with identical production capabilities that all produce exactly one undifferentiated product (that may itself be a “kit” of components). Each sector may use several inputs to produce its product, and these inputs are supplied by different sectors. The production process within any sector is taken to be pure assembly in fixed proportions. The number of firms in each sector is known. The demand curve for the final product is assumed to be linear, as are production costs in all sectors. Competition is modeled via a “coordinated successive Cournot” model in which firms choose production quantities for their downstream market so as to maximize profits, given prices for all inputs and all complementary products. Production quantities for sectors supplying the same successor are coordinated through pricing mechanisms, so that complementary products are produced in the right proportions. Under these assumptions, equilibrium prices for any multiechelon assembly network are characterized by a system of linear equations. We derive closed-form expressions for equilibrium quantities and prices in any two-stage system (i.e., a system with multiple input sectors and a single assembly sector). We show that any assembly structure can be converted to an equivalent (larger) structure in which no more than two components are assembled at any node. Finally, large structures can be solved either by direct solution of the characteristic linear equations or through an iterative reduction (compression) to smaller structures.

Business-to-business electronic commerce and convergent assembly supply chain management

Electronic commerce (e-commerce) can occur between a business and its customers, as well as between a business and its suppliers. To facilitate interorganizational e-commerce it is often necessary to share supply and demand information between supply chain partners. Based on our analysis of supply chains in several industries we identify the mechanisms (business processes) required for effective supply chain management. We also identify the information system components needed to support these mechanisms, show how the individual components can be integrated into an information infrastructure framework and identify some technologies currently available that can fit within our proposed infrastructure. We illustrate the usefulness of our framework by simulating convergent assembly (commonly associated with motor vehicle and aerospace production) supply chain performance under various information-sharing strategies supported by our proposed infrastructure. We find that inventory costs can be reduced while maintaining acceptable order fulfilment cycle times. This is true because information, which provides the basis for enhanced coordination and reduced uncertainty, can substitute for inventory.

Business-to-Business Electronic Commerce and Convergent Assembly Supply Chain Management

Electronic commerce (e-commerce) can occur between a business and its customers, as well as between a business and its suppliers. To facilitate interorganizational e-commerce it is often necessary to share supply and demand information between supply chain partners. Based on our analysis of supply chains in several industries we identify the mechanisms (business processes) required for effective supply chain management. We also identify the information system components needed to support these mechanisms, show how the individual components can be integrated into an information infrastructure framework and identify some technologies currently available that can fit within our proposed infrastructure. We illustrate the usefulness of our framework by simulating convergent assembly (commonly associated with motor vehicle and aerospace production) supply chain performance under various information-sharing strategies supported by our proposed infrastructure. We find that inventory costs can be reduced while maintaining acceptable order fulfilment cycle times. This is true because information, which provides the basis for enhanced coordination and reduced uncertainty, can substitute for inventory.