Shie-Gheun Koh

An optimal ordering and recovery policy for reusable items

This paper deals with a joint EOQ and EPQ model in which the stationary demand can be satisfied by recycled products and newly purchased products. The model assumes that a fixed proportion of the used products are collected from customers and later recovered for reuse. The recovered products are regarded as perfectly new ones. We obtain (i) the economic order quantity for newly procured products and (ii) the optimal inventory level of recoverable items to start the recovery process, simultaneously. According to the relationship between parameters, we propose some numerical models to analyze the system. Then a solution procedure to find the optimal control parameters is presented, and finally some numerical examples are given to illustrate the model.

A generalized ordering and recovery policy for reusable items

This paper deals with a joint EOQ and EPQ model in which a stationary demand is satisfied by recovered products as well as newly purchased products. It is assumed that a fixed proportion of the used products are collected from customers and later recovered for reuse. We generalize the (P, R) policy in the literature by treating the sequence of orders for newly purchasing products and setups for recovery process within a cycle as a decision variable. Through example problems we illustrate the validity of the model and solution procedure developed.

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.

Comparison of DBR with CONWIP in an unbalanced production line with three stations

The recently developed alternatives to traditional production planning and control systems such as material requirement planning (MRP) and Kanban are the drum–buffer–rope (DBR) and CONWIP (CONstant Work In Process) systems. Each system is best described as a combination push (like an MRP)/pull (like a Kanban) logistical procedure. Materials are pulled into the shop via the appropriate logic, and once released, materials are then pushed to subsequent workcentres. The performance of the DBR and CONWIP control policies are analysed and compared in a three-stage unbalanced tandem production line. Using a continuous Markov process model, steady-state probability distributions for the systems are derived, and then the performance measures of the systems can be evaluated. To compare the two systems, an optimization model for each system is proposed. From sensitivity analyses for the optimization models, the proposed models are validated, the differences of the two systems are investigated, and it is found that DBR is better than CONWIP under the proposed performance measures.

Travel time model for the warehousing system with a tower crane S/R machine

This paper studies the characteristics of a warehousing system in which the storage and retrieval orders are performed by a tower crane. The crane is located at the center of the round storage area and it can rotate in both clockwise and counterclockwise directions. We develop some mathematical travel time models for this warehousing system using the characteristic of the S/R crane that the S/R device can move in radial and circumferential directions simultaneously. First, we derive travel time models for single command and dual command cycles under the randomized storage assignment rule. Then, assuming that the turnover rates for items are different from each other, we calculate expected travel time under the turnover-based assignment rule through a numerical approach. For each model some illustrative examples are presented.

Spatial scheduling for shape-changing mega-blocks in a shipbuilding company

To overcome space restriction and to increase productivity, some shipbuilding companies use floating-docks on the sea instead of dry-docks on the land. In that case, a floating-crane that is capable of lifting very heavy objects (up to 3600 tons) is used to handle the blocks which are the basic units in shipbuilding processes, and therefore, very large blocks (also called mega-blocks) can be used to build a ship, but because there are some positional restrictions under which the mega-block assembly yard can be constructed, the space is the scarcest resource in the process. The focus of the research reported in this paper is to develop an efficient spatial schedule for the mega-block assembly yard. First, we develop a length-time two-dimensional packing model for this problem. Since the optimisation model cannot be solved using an analytical method, we propose a GA-based heuristic algorithm using computational geometry theory. Through performing a series of computational experiments, we finally show that the proposed spatial scheduling algorithm can provide solutions of good quality very efficiently.

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.

Spatial Scheduling for Mega-block Assembly Yard in Shipbuilding Company

To mitigate space restriction and to raise productivity, some shipbuilding companies use floating-docks on the sea instead of dry-docks on the land. In that case, a floating-crane that can lift very heavy objects (up to 3,600 tons) is used to handle the blocks which are the basic units in shipbuilding processes, and so, very large blocks (these are called the mega-blocks) can be used to build a ship. But, because these mega-blocks can be made only in the area near the floating-dock and beside the sea, the space is very important resource for the process. Therefore, our problem is to make an efficient spatial schedule for the mega-block assembly yard. First of all, we formulate this situation into a mathematical model and find optimal solution for a small problem using a commercial optimization software. But, the software could not give optimal solutions for practical sized problems in a reasonable time, and so we propose a GA-based heuristic algorithm. Through a numerical experiment, finally, we show that the spatial scheduling algorithm can provide a very good performance.

A genetic algorithm for dynamic inbound ordering and outbound dispatching problem with delivery time windows

This article considers an inbound ordering and outbound dispatching problem for a single product in a third-party warehouse, where the demands are dynamic over a discrete and finite time horizon, and moreover, each demand has a time window in which it must be satisfied. Replenishing orders are shipped in containers and the freight cost is proportional to the number of containers used. The problem is classified into two cases, i.e. non-split demand case and split demand case, and a mathematical model for each case is presented. An in-depth analysis of the models shows that they are very complicated and difficult to find optimal solutions as the problem size becomes large. Therefore, genetic algorithm (GA) based heuristic approaches are designed to solve the problems in a reasonable time. To validate and evaluate the algorithms, finally, some computational experiments are conducted.

Skid scheduling algorithm for a shipbuilding company

In the small- and medium-sized shipbuilding companies, the skid system, which is a kind of slips located on flat seashore, is widely used. To improve the productivity of the skid, many shipbuilders adopt the semi-tandem system, under which a number of ships can be built on a skid simultaneously. The focus of the research reported in this paper is to develop an efficient spatial schedule for the skid system that uses the semi-tandem system. First, we develop a length-time, two-dimensional packing model for this problem and propose a heuristic algorithm to use the skid efficiently when the launching schedule for ships is given. Then, by combining this heuristic and the GA (genetic algorithm), we develop a hybrid GA algorithm to determine the launching schedule of ships as well as the spatial schedule for the skid, which maximises the number of ships that can be built on the skid and minimises delayed or early launching of each ship. Through performing a series of computational experiments, we finally show that the proposed algorithm can provide solutions of good quality very efficiently.