Andy Wu

The impact of estimation error on the dynamic order admission policy in B2B MTO environments

When swarming demands cause stringent capacity situations, order promising becomes a challenging job. However, a dynamic order admission policy by utilizing the concept of revenue management may find a good way to solve the problem. Unfortunately, the expected profit under different dynamic order admission policies is sensitive to the estimation error of order forecasts. In this paper, the impact of estimation error is investigated under various order structures. The post analysis is performed and shows significant statistical difference among the optimal unbiased DSKP policy, biased DSKP policy, and FCFS policy. The results reveal the robustness and superiority of DSKP policy in most scenarios.

On a multi-product lot scheduling problem subject to an imperfect process with standby modules

An Economic Lot Scheduling Problem is considered under the condition that the production process may shift from an in-control state to an out-of-control state due to the deterioration of the facility’s key module. We adopt the Common Cycle policy in two mathematical models depending on whether the key module is repairable or not. Several standby modules are available during a production run. For the model with non-repairable key modules, the active key module, once deteriorated, is disposed of and replaced by a new standby. For the model with repairable key modules, the active one is replaced by a standby as soon as it is deteriorated. The failing module will be restored in a repair shop and rejoin the standbys. The objective is to determine an optimal production cycle time and the economic number of standby modules in order to minimise the long-term average cost including set-up, inventory carrying, standby and defective costs. The convexity of the cost functions is revealed so that efficient algorithms can be developed accordingly to achieve optimal production-inventory policies. It is shown that these policies can be used to significantly improve the system performance.

A supportive pricing model for suppliers with purchase order financing

Traditionally, lowering the purchase price is welcomed by a business buyer since people believe it can reduce the costs. However, it can be another story if her supplier is short of money and applies for purchase order financing to fund the production. This paper identifies the conditions under which a buyer has the motivation of allowing higher purchase price to facilitate the supplier’s loan application and consequently improve the supply availability. We use a Stackelberg model to describe the interaction between the supplier’s plan (deciding the loan amount and production input simultaneously) and the buyer’s order design (deciding the purchase price and order size jointly). We show the buyer’s optimal order design has four kinds of closed-form solutions as the supplier’s operational state follows a two-point distribution. The design choice should depend on the item value and the supplier’s reliability. In short, this research shows when to increase the purchase price and how to coordinate the order size with it. Generally speaking, if the item value is high and the supplier’s reliability is medium, a buyer allowing a premium price can ensure the supply and actually maximise her expected profit.

Supporting small suppliers through buyer-backed purchase order financing

Supporting small and medium enterprises (SMEs) to access finance has received rapidly-rising attention in recent years. In some countries, large buyers in supply chains are considering credit guarantee schemes (CGS) through which the credit coverage can be extended to assist their SME suppliers. While such support is beneficial to the suppliers, an issue arises regarding the motivation of the large buyers to join and support the SME suppliers. In practice, SMEs are often attractive but riskier sources of supply. Supporting SME suppliers through the financial guarantee may bring even more risk concern to buyers. To study the buyers’ sourcing and guarantee strategy, we analyze a simplified model where a core enterprise procures components from only two sources: an SME supplier with a lower price and the spot market with a higher price. A novel Buyer-Backed Purchase Order Financing (BPOF) scheme is studied in supporting the supplier’s financing. We analyze the effect of the market interest and identify the properties of the buyer’s optimal joint sourcing and credit-guarantee decisions. Through numerical experiments, BPOF is shown to significantly improve the core enterprise‘s profitability.

Reduce shortage with self-reservation policy for a manufacturer paying both fixed and variable stockout expenditure

This study considers a single item make-to-stock system with continuous-time production and inventory controls to meet bulk demand with an exponential inter-arrival time. A key issue in this system is the non-convex shortage cost consisting of fixed and variable expenditures when the demand is not fully satisfied. We propose a self-reservation policy by building a Markov Decision Process to minimize the overall cost. We find that the optimal production control is still a base stock policy, but the structure of the optimal self-reservation policy is very complicated. However, if the effective outstanding variable shortage cost is sufficiently large, the optimal self-reservation policy has an easy form of “Reserve All or Nothing.” Our numerical examples indicate the optimal policy may reduce the total average cost by 47% on average.

Academia-industry collaboration in SoC design education: wishes and reality

The complexity of IC has been growing each year, now reaching nano-scale design rule and over billion transistors on a chip. To develop advanced SoCs, huge amount and high quality of resources and research activities are necessary for design as well as for technology development. It is getting even more vital to recruit well-trained students, who can lead the global competition. Industry is also expecting for universities to help raise probability of success of SoCs, the market of which is even more limited in time-to-market and product life in spite of the huge investment. These are the major motivations, for which SoC industry wishes to share resources and risk with universities. Industry has even established consortiums to improve and activate the relationship with universities toward these goals. In this panel, views from universities and industry are discussed and analyzed to explore successful collaboration.