Seung-Lae Kim

Implementation of JIT purchasing: An integrated approach

This article addresses the necessity of integration between buyer and supplier for effective implementation of the JIT system. An integrated lot-splitting model of facilitating multiple shipments in small lots is developed and compared with the existing approach in a simple JIT environment, single-buyer-single-supplier, under deterministic conditions for a single product. It is shown that the optimal policy adopted by the integrated approach can provide a strong and consistent cost-minimizing effect for both buyer and supplier over the existing approach.

A JIT lot-splitting model for supply chain management: Enhancing buyer-supplier linkage

Abstract This study develops a buyer–supplier coordination model to facilitate frequent deliveries in small lot sizes in a manufacturing supply chain. The proposed model, based on the integrated total relevant costs of both buyer and supplier, determines optimal order quantity, the number of deliveries/setups, and shipping quantity over a finite planning horizon in a relatively simple JIT single buyer single supplier scenario. Under deterministic conditions for a single product, we show that the optimal delivery policy adopted by both buyer and supplier in a cooperative manner can be economically beneficial to both parties. It is shown that the optimal delivery size can be unique, regardless of the order quantity and the number of deliveries. Numerical results are also presented.

An integrated JIT inventory model

Derives an integrated inventory replenishment model for a buyer that buys a single product from a vendor that manufactures this item and delivers it to the former in fixed quantities. It is assumed that both parties co‐operate and exchange information, including cost data, which is not unheard of in a JIT based partnering relationship, in deriving a jointly optimal inventory replenishment policy, rather than individually deriving their own independent policies. Such an approach can result in significant savings in the joint total relevant cost incurred by both parties. These savings may be shared in some fair and equitable manner, so that, from an economic standpoint, both the buyer and the vendor derive substantive benefits from such an integrated, jointly optimal policy. Illustrates the model and the related concepts through a simple numerical example.

JIT purchasing and setup reduction in an integrated inventory model

We study the effects of JIT order quantities on the purchase of raw materials and of the investments to reduce setup time. We examine the total relevant cost for an integrated inventory model, which unifies the finished product and the raw materials used for manufacturing it. A comparison of the total costs between our JIT model and the conventional ‘economic production quantity’ model suggests that JIT order splitting and investment in setup reduction could be cost-effective.

Production and delivery policies for enhanced supply chain partnerships

Recent research on supply chain management has highlighted the importance of building strong customer–supplier relationships in order to gain competitive advantage. This paper examines the benefits of buyer–supplier partnerships over lot-for-lot, i.e. single setup single delivery (SSSD) systems and suggests two policies that the supplier can pursue in order to meet customers’ needs: (1) Single setup multiple delivery (SSMD), and (2) Multiple setup multiple delivery (MSMD). If its fixed setup cost is relatively high, the supplier would prefer to implement SSMD and produce an entire order with one setup. However, if the supplier can reduce the setup cost and the suppliers capacity is greater than the threshold level (P = 2D), it is more beneficial for the supplier to implement the multiple setups and multiple deliveries (MSMD) policy, even though he pays more frequent setup costs since the savings in inventory holding costs is greater than the increased setup costs. In the latter case, setup reduction is realized by the knowledge and efficiency gained through frequent setup operations. To provide guidelines for the policy selection, we examine the interactions among variables, such as production capacity, learning rate, and holding costs for both parties. The paper also discusses the benefit sharing plan, which discusses according to the contribution (or sacrifice) each party made to the partnership efforts.

An inventory model with partial backordering and unit backorder cost linearly increasing with the waiting time

As the implementation of JIT practice becomes increasingly popular, each echelon in a supply chain tends to carry fewer inventories, and thus the whole supply chain is made more vulnerable to lost sales and/or backorders. The purpose of this paper is to recast the inventory model to be more relevant to current situations, where the penalty cost for a shortage occurrence at a downstream stage in a supply chain is continually transmitted to the upstream stages. The supplier, in this case, at the upstream of the supply chain is responsible for all the downstream shortages due to the chain reaction of its backlog. The current paper proposes a model in which the backorder cost per unit time is a linearly increasing function of shortage time, and it claims that the optimal policy for the supplier is setting the optimal shortage time per inventory cycle to minimize its total relevant cost in a JIT environment.

Combining and selecting forecasting models using rule based induction

Abstract As inaccurate forecasts can lead to lost business and inefficient operations, it is imperative that forecasts be as accurate as possible. A major problem however, is that no single forecasting method is the most accurate for every data time series. Thus, generating a forecast is often an uncertain affair, involving the use of heuristics by human experts and/or the consistent use of forecasting models whose accuracy may or may not be the most accurate for that time series. To compound matters, the best forecasts are often produced by combining forecasting models. This research describes the use of an Artificial Intelligence (AI)-based technique, rule-based induction, to improve forecasting accuracy. By using training sets of time series (and their features), induced rules were created to predict the most appropriate forecasting method or combination of methods for new time series. The results of this experiment, which appear promising, are presented, together with guidelines for its practical application. Potential benefits include dramatic reductions in the effort and cost of forecasting; the provision of an expert ‘assistant’ for specialist forecasters; and increases in forecasting accuracy.

Dynamic setup reduction in production lot sizing with nonconstant deterministic demand

Abstract We examine three production policies under nonconstant, deterministic demand and dynamic setup cost reduction, where a decision to invest in setup reduction is made at the beginning of each period of a planning horizon. The three production policies are the reorder point, order quantity ( s , Q ) policy; the fixed production cycle, variable order quantity ( t , Q i ) policy; and the variable production cycle, variable order quantity ( t i , Q i ). We study the behavior of the total relevant cost and develop a lot sizing and an investment solution procedure. Numerical examples are provided and dynamic setup cost reduction is compared with static setup cost reduction, where the decision to invest in setup reduction is made only at the initial setup.

A multicriteria model for supporting setup reduction investment decisions

Abstract One critical manufacturing challenge of the 1990s is for firms to effectively apply new operations management techniques while embracing wider philosophies such as total quality management (TQM) and computer integrated manufacturing (CIM), etc. Setup cost and/or time reduction is one such technique capable of producing many benefits for manufacturing firms, including reduced inventory, better equipment utilization, and improved quality. It is thereby viewed as an important component of just-in-time (JIT) manufacturing practice. Existing problems with the setup reduction decision include the many factors that must be considered, as well of an absence of validated and usable models for estimating potential benefits from setup reduction investment made in different contexts. This paper discusses the attainment of gains from setup reduction mainly by improving existing equipment and work practices rather than purchasing new equipment or technology. The model proposed in this paper is based on the app...

Note on: An integrated vendor–buyer cooperative inventory model for items with imperfect quality

Huang [Huang, C., 2002. An integrated vendor–buyer cooperative inventory model for items with imperfect quality. Production Planning and Control, 13 (4), 355–361] proposes an integrated inventory model which allows a vendor and a buyer to minimise their expected integrated total cost function when the vendors production process is not perfect. This note identifies two errors in the paper and provides a reformulation of the model.