We study a multicomponent, multiproduct production and inventory system in which individual components are made to stock but final products are assembled to customer orders. Each component is produced by an independent production facility with finite capacity, and the component inventory is controlled by an independent base-stock policy. For any given base-stock policy, we derive the key performance measures, including the probability of fulfilling a customer order within any specified time window. Computational procedures and numerical examples are also presented. A similar approach applies to the generic multi-item make-to-stock inventory systems in which a typical customer order consists of a kit of items. T his paper concerns the evaluation and analysis of order fulfillment performance measures for a multiitem, assemble-to-order production/inventory system with stochastic leadtimes. Order fulfillment performance has become increasingly important as companies that must adapt quickly to market and technology changes move toward "assemble-to-order," as opposed to the traditional "make-to-stock," inventory planning systems. In an assemble-to-order system, products are designed around interchangeable modules, and the company makes and stocks only the modules and other major components. When a customer order arrives requesting a specific kit of modules and components, the company quickly assembles these items and delivers the end product to the customer. Since each customer order requires the simultaneous availability of several items, the questions inventory managers ask most frequently are the following: For any given safety-stock level of each item, what is the probability a demand can be satisfied immediately (order fill rate)? What is the probability a customer order can be met within a time window (customer waiting time distribution; also termed order response time reliability in industry)? The same issue exists for many multi-item distribution systems as well, including the emerging mail-order businesses (see, for example, Cohen and Lee 1990, Lee and Billington 1992, Song 1998). In particular, a typical customer order to a manufacturer consists of a combination of several finished goods. Reliable and speedy delivery of orders is one of the most crucial factors for customer satisfaction. So, the order-based performance measures, such as the order fill rate and the customer waiting time distribution, are the important ones. Standard inventory models assume that demands are independent across items, which is a valid assumption for some situations in the make-to-stock environment but not for assemble-to-order systems, in which one must jointly manage inventories and production capacities across various items. Evidently, new models and methods are in demand to address important issues in assemble-to-order systems. The purpose of this paper is to conduct an exact analysis on a wide range of performance measures in the assembleto-order systems with sequential, capacitated stochastic production processes. In particular, we model the demand process as a multivariate Poisson process. That is, the overall demand arrives according to a Poisson process, but there is a fixed probability that a demand requests a particular kit of different items. Each item's inventory is controlled by a separate base-stock policy. Demands are filled on an FCFS basis. Demands for an item that cannot be filled immediately are queued in a backlog queue with a certain capacity, whose value may range from zero to infinity. Infinite capacity corresponds to the complete backlog case, whereas zero capacity corresponds to the lost-sale case. The supply system of each item is an independent, single-machine production facility with i.i.d. exponentially distributed processing times. For any given base-stock policy and backlog queue limits, we present a procedure to evaluate the item-based, order-based, and system-based performance measures, such as fill rate, service level (the probability that an order
REF stated that order fulfillment process of assemble to order (ATO)/ make to order(MTO) was crucial for the organizations to deliver the product quickly to market as compared to the traditional MTO inventory planning systems.
Order-Fulfillment Performance Measures in an Assemble-to-Order System with Stochastic Leadtimes
Oper. Res.
Oper. Res.
Computer Science Mathematics