Hsin Rau

Integrated inventory model for deteriorating items under a multi-echelon supply chain environment

Abstract As the industrial environment becomes more competitive, supply chain management has become essential. The objective of this research is to develop a multi-echelon inventory model for a deteriorating item and to derive an optimal joint total cost from an integrated perspective among the supplier, the producer, and the buyer. A computer code is developed to derive the optimal solution. A numerical example is given to illustrate the model. This paper shows that the integrated approach strategy results in the lowest joint total cost as compared with the independent decision approaches.

Two-sided assembly lines balancing with assignment restrictions

Abstract Two-sided assembly line is a set of sequential workstations where task operations can be performed in two sides of the line. The line is important for large-sized products, such as trucks, buses and cars. In this paper, we proposed a mathematical model for two-sided assembly line type II (TALBP-II) with assignment restrictions. The aim of the model is minimizing the cycle time for a given number of mated-workstations and balancing the workstation simultaneously. The model provides a more realistic situation of the two-sided assembly line problems. Genetic algorithm and iterative first-fit rule are used to solve the problem. The performances of both methods are compared using six numerical examples. Based on the experiments, the iterative first-fit rule can take the advantage of finding the best position over many workstations and the genetic algorithm provides more flexible task assignment and is significantly faster than the iterative first-fit rule.

An optimal batch size for integrated production-inventory policy in a supply chain

Abstract This study presents a new integrated production–inventory policy under a finite planning horizon and a linear trend in demand. We assume that the vendor makes a single product and supplies it to a buyer with a non-periodic and just-in-time (JIT) replenishment policy in a supply chain environment. The objective is to minimize the joint total costs incurred by the vendor and the buyer. In this study, first, we develop a mathematical model and prove that it has the optimal solution. Then, we describe an explicit solution procedure for obtaining the optimal solution. Finally, we provide two numerical examples to illustrate both increasing and decreasing demands in our proposed model, and we show that the performance of the integrated consideration is better than the performance of any independent decision from either the buyer or the vendor.

Capacity planning with capability for multiple semiconductor manufacturing fabs

A capacity planning system (CPS) that considers the capacity and capability of equipment is developed for multiple semiconductor manufacturing fabs. On the basis of pull philosophy and the assumption of infinite equipment capacity, the system determines each lots release time, start fab, and the capability of the equipment. CPS includes three main modules-the WIP-Pulling Module (WPM), the Workload Accumulation Module (WAM) and the Wafer Release Module (WRM). WPM pulls WIP from the end of the process route to meet the master production schedule (MPS). WAM then calculates the expected equipment loading in different time buckets. If WIP cannot meet the MPS requirement, then for each lot to be released, WRM evaluates the expected loading of many fabs, based on the lots planned start time, and then determines the lot release time, the start fab and the equipment capability, to optimize the workload balance among all fabs. Simulation results indicate the effectiveness and efficiency of this system. A CPS that combines Adjusted Release Time (ART) and Path Load performs best in terms of three performance measures. This finding shows that CPS based on the combination of ART and Path Load can efficiently balance the equipment workload among the various fabs, on various days, and across various equipment at various levels of demands.

Deteriorating item inventory model with shortage due to supplier in an integrated supply chain

The aim of this paper is to develop an inventory model for deteriorating items with a shortage occurring at the supplier involving a supply chain between the producer and buyer. A numerical example is used to illustrate the model and demonstrate that integrated decisions are more cost-effective compared with independent decisions from the supplier, producer or buyer. The optimal number of deliveries is derived with the minimal joint total cost from the integrated viewpoint. This study compares cases with and without shortages. A sensitivity analysis is given to explore the effect from a supplier shortage.

Learning-based automated negotiation between shipper and forwarder

This paper studies an automated negotiation system by means of a learning-based approach. Negotiation between shipper and forwarder is used as an example in which the issues of negotiation are unit shipping price, delay penalty, due date, and shipping quantity. A data ratios method is proposed as the input of the neural network technique to explore the learning in automated negotiation with the negotiation decision functions (NDFs) developed by [Faratin, P., Sierra, C., & Jennings, N.R. (1998). Negotiation Decision Functions for Autonomous Agents. Robotics and Autonomous Systems, 24 (3), 159-182]. The concession tactic and weight of every issue offered by the opponent can be learned from this process exactly. After learning, a trade-off mechanism can be applied to achieve better negotiation result on the distance to Pareto optimal solution. Based on the results of this study, we believe that our findings can provide more insight into agent-based negotiation and can be applied to improve negotiation processes.

Genetic algorithm modeling for the inspection allocation in reentrant production systems

One of the most important characteristics of reentrant production systems is that the products are manufactured layer-by-layer, so it is difficult to inspect some defects after they are covered by the next layer. This study proposes a genetic algorithm (GA) approach that is very suitable for solving the inspection allocation problem, because the codes used in the chromosome of the GA approach are exactly the same as the representation of the inspection allocation policy for workstations in the production system. Meanwhile, this study shows better performance than the researches done in the literature and is very much closer to the optimization method based on complete enumeration. In addition, a discussion regarding GA parameters is performed to suggest proper parameters used for various production systems. The result obtained in this study is highly practical, extensible and applicable, so it can serve as a production planning tool to solve the inspection allocation problem in reentrant production systems.

A general and optimal approach for three inventory models with a linear trend in demand

This study provides a general and simple algorithm to obtain an optimal solution for three inventory models with a replenishment batching policy, production batching policy, and an integrated replenishment/production batching policy in a manufacturing system, under a finite time horizon and linear trend in demand. This study determines the replenishment or production schedule with one general equation for these three problems and provides fully theoretical proofs for relaxing some of the conjectures in previous studies. A general and explicit procedure to derive the optimal solution for these three inventory models is presented, while considering both linearly increasing and decreasing demands. In addition, demonstrations of applicability are performed.

Develop a negotiation framework for automating B2B processes in the RosettaNet environment using fuzzy technology

The electronic trade between enterprises becomes more popular due to the rapid development of electronic commerce. Under the electronic business environment, in order to make the trade process smoother and faster, most enterprises adopt industry standards, such as EDI and RosettaNet, for developing electronic business platforms to transact business processes. These standards and platforms can help both trading sides to control and facilitate the business processes and validate the document format. However, these processes still need human efforts to make decisions, which might cause business losses due to time delay or human error during the process. In order to solve the problem, this study takes a step further to propose a negotiation framework for automating the B2B processes. This study chooses RosettaNet purchase order management processes as an example to implement automated negotiations on Biztalk platform. In order to evaluate the negotiation behavior of the opponent, two fuzzy membership functions, preference degree and opponents concession degree, are proposed to develop 25 levels of fuzzy rules to determine better offers to help to reach a settlement more responsively and dynamically. Experiment results show that our approach can help B2B transaction effectively.

Application of simulation to the scheduling problem for a LED sorting system

The scheduling problem of LED chip sorting workstation is a multiprocessor open shop scheduling problem which is categorized as a NP-hard problem. In practice, this problem is usually solved with finding a dispatching rule to achieve certain performance indices through simulation. To find the most effective rule from five proposed dispatching rules was considered in this study. Experimental design was applied to find significant factors, and a two-stage process was used to select the best dispatching rule. In the first stage, where make-span as the performance index, three dispatching rules are selected for the next stage comparison, and they are common in applying LPT in bottleneck machines. In the second stage, a dispatching rule with applying SPT in non-bottleneck machines has least average queuing time among those three, and this rule is recommended for practical application.