Pyung-Hoi Koo

Scheduling parallel batch processing machines with arbitrary job sizes and incompatible job families

Motivated by a bottleneck operation in an MLCC (multi-layer ceramic capacitor) production line, we study the scheduling problem of parallel batch processing machines in which a number of jobs can be processed simultaneously in a machine as a batch. Volumes of the jobs are different from each other and each job belongs to the family in which all jobs have the same processing time. In this situation, we analyse three kinds of problems whose performance measures are makespan, total completion time, and total weighted completion time, respectively. Since these problems are known to be NP-hard, we propose a number of heuristics and design genetic algorithms for the problems. Through some computational experiments, we evaluate the performances of the heuristic algorithms proposed, including the genetic algorithms for each of three problems.

Vehicle Travel Time Models for AGV Systems under Various Dispatching Rules

The design and evaluation of AGV-based material handling systems are highly complex because of the randomness and the large number of variables involved. Vehicle travel time is a fundamental parameter for solving various flexible manufacturing system (FMS) design problems. This article presents stochastic vehicle travel time models for AGV-based material handling systems with emphasis on the empty travel times of vehicles. Various vehicle dispatching rules examined here include the nearest vehicle selection rule and the longest idle vehicle selection rule. A simulation experiment is used to evaluate and demonstrate the presented models.

The use of bucket brigades in zone order picking systems

As the transactions through electronic commerce and TV home shopping increase, the warehouses often receive a large amount of small orders to be picked within tight time windows. One of the important warehousing activities is order picking, the process of retrieving a number of items from warehouse storage to meet a number of independent customer orders. This paper examines a new order picking method, bucket brigade order picking (BB picking). Bucket brigade is a way of coordinating workers who progressively perform a set of operations on a flow line. In the BB picking system, a worker performs operations on an order until the next worker downstream takes it over; then goes back to the previous worker upstream to take over a new order. We discuss distinct characteristics in order picking systems when bucket brigades are applied. We identify some efficiency losses under the BB picking and present a new BB picking protocol to improve the performance of order picking systems. The new BB picking is compared with the existing BB picking and zone picking through simulation experiments.

Determination of batch size at a bottleneck machine in manufacturing systems

In manufacturing systems, there often exists a bottleneck machine whose capacity is equal to or less than the market demand. Any idle or waste time at the bottleneck machine directly impacts the output of the entire plant because it results in a loss of throughput. In order to maximize the capacity utilization by less setup losses at the bottleneck machine, the parts are often produced in batches. Traditionally, most batch sizing decisions are made based on the economic order quantity model where setup and inventory holding costs are considered. This paper presents an alternative method to determine batch size at a bottleneck machine. We present a new objective function and cost factors for batch sizing and investigate queuing and throughput models. A linear search algorithm is introduced to find the optimal throughput rate and batch size at the same time. Numerical examples are examined to see how the batching algorithm works.

Simulation-based patient flow analysis in an endoscopy unit

One of the major elements in improving efficiency of healthcare services is patient flow. Patients require a variety of healthcare resources as they receive healthcare services. Poor management of patient flow results in long waiting time of patients, under/over utilization of medical resources, low quality of care and high healthcare cost. This article addresses patient flow problems at a Gastrointestinal endoscopy unit. We attempt to analyze the main factors that contribute to the inefficient patient flow and process bottlenecks and to propose efficient patient scheduling and staff allocation alternatives to increase the system efficiency. Simulation models are used to examine various healthcare operational strategies.

Transporter scheduling based on a network flow model under a dynamic block transportation environment1

This paper considers a transporter scheduling problem under dynamic block transportation environment in shipbuilding. In dynamic situations, there exist the addition, cancellation or change of block transportation requirements, sudden breakdowns, and maintenance of transporters. Some blocks are available to be picked up at a specific time during the planning horizon while some other blocks need to be delivered before a specific time. These requirements cause two penalty times: 1) delay times incurred when a block is picked up after a required start time, and 2) tardy times incurred when a block shipment is completed after a required delivery time. The blocks are located at different areas in the shipyard and transported by transporters. The objective of this paper is to propose a heuristic algorithm based on a network flow model which minimize the weighted sum of empty transporter travel times, delay times, and tardy times. Also, a rolling scheduling algorithm is proposed for dynamic block transportation environment. The performance of the proposed heuristic algorithms are evaluated through a simulation experiment.

A Study on Big Data Based Investment Strategy Using Internet Search Trends

Together with soaring interest on Big Data, now there are vigor ous reports that unearth various social values lying underneath those data from a number of application areas. Among those reports many are using such data as Internet search histories from Google site, social relationships from Facebook, and transactional or locational traces collected from various ubiquitous devices. Many of those researches, howe ver, are conducted based on the data sets that are accumulated over the North American and European areas, which means that direct interpretation and application of social values exhibited by those researches to the other are as like Korea can be a disturbing task.This research has started from a validation study against Korean environment of the former paper which says an investment strategy that exploits up and down of Google sear ch volume on a carefully selected set of terms shows high market performance. A huge difference between North Americ an and Korean environment can be eye witnessed via the distinction in profit rates that are exhibited by the corresponding set of search terms. Two sets of search terms actually presented low correlation in their profit rates over two financial markets. Even in an experiment which compares the profit rates with two different investment periods with the same set of search terms showed no such meaningful result that outperforms the market average. With all these results, we cautiously conclude that establishing an investment strategy that exploits Internet search volume ove r a specified word set needs more conscious approach.

Production batch sizing at multi-product bottleneck machines

In common manufacturing systems, there exist bottleneck machines that limit the capacity of the entire system. This paper addresses a batch sizing problem at the bottleneck machines in which various product types are processed. Koo et al. (2006) have presented a batch sizing model at single-product bottleneck machines. This paper is an extension to the previous research work where multiple products are taken into explicit considerations in batch sizing. We introduce a linear search algorithm to find optimal throughput rate and batch size at the same time. Numerical examples are provided to see how the proposed method works.

Performance Analysis of a New Work Assignment in Assembly Cells

This paper addresses the work assignment problems in assembly cells. The assembly cells are known to be more flexible and productive than the traditional assembly line. To maximize the utilization of resources in assembly cells, it is important to have the line balanced. This paper presents a dynamic work assignment method where each worker performs assembly operations on a product until the next worker downstream takes it over. This pull-type assignment method balances the assembly cell in an autonomous way. The performance of the new assignment method is examined and compared with existing assignment methods.

A Real-Time Loading Strategy of Batch Processing Machines for Average Tardiness Minimization

Pyung-Hoi KooDepartment of Systems Management and Engineering, Pukyong National UniversityThis paper provides a real-time loading strategy for batch processing machines in which a number of jobs are simultaneously processed as a batch. The batch processing machines can be seen in both manufacturing indus-tries (e.g., semiconductor, automobile and metal working) and service industries (transportation vehicles, mail shipment and theme park). This paper focuses on batch processing machines in semiconductor manufacturing. We present a look-ahead loading strategy for tardiness minimization where future arrivals and due dates are taken into consideration. Simulation tests are performed on the presented strategy and some existing loading heuristics under various production settings with different traffic intensities and forecasting errors. Experimental results show that our strategy provides the performance of good quality.