Daisuke Hirotani

An adaptive pull strategy for remanufacturing systems

Recently, remanufacturing systems have been studied from various viewpoints. Van der Laan and Teunter (Eur J Oper Res 175(2):1084–1102, 2006), for example, proposed simple heuristics for push and pull remanufacturing strategies. However, because they are only simple heuristics they are not very useful in a stochastic demand situation. An adaptive strategy should be incorporated into the pull strategy to improve performance; therefore, we propose an adaptive pull strategy for remanufacturing systems that can control manufacturing and remanufacturing rates in the remanufacturing system. The performance and effectiveness of our proposed system is analyzed by Markov analysis, and the results are shown in this paper.

Adaptive Kanban control systems for two-stage production lines

To respond to demands while reducing inventories, the Kanban control system (KCS) has been developed as a typical system for just-in-time production system. The original KCS has been revised to adaptive KCS by Tardif and Maaseidvaag (2001). However, in the adaptive KCS, how to adjust the number of Kanbans at each stage has never been considered. This paper proposes two types of adaptive KCS for two-stage production lines according to the difference of adjusting the number of Kanbans at each stage. A queuing-network model of the two types of adaptive KCSs is developed, and the performance is analysed and compared with each other by using Markov analysis. Numerical calculations are conducted to investigate the influence of the processing rate and cost parameters on the performance measures. The results show the advantages of each system over the other.

An Adaptive Kanban and Production Capacity Control Mechanism

This paper proposes an adaptive kanban and production capacity control system as a new production planning and control mechanism for Just-in-Time environments to minimize the long term average inventories, Work-In-Process, backorders and operating costs. It is based on the adaptive kanban system proposed by Tardif and Maaseidvaag (2001), but dynamically adjusts both the number of kanbans and the level of production capacity with respect to inventories and backorders. It is expected to be more resistant to changes in the demand than previous pull ordering mechanisms. We present how to evaluate its performance for the case of a single-stage, single-product manufacturing process with exponential processing times and demand following a Poisson process. Simulation results under variable demand means are presented.

Performance evaluation of candidate appointment schedules using clearing functions

This study is concerned with the problem of reducing the waiting times of outpatients. Both scheduled patients and walk-ins are included among the outpatients to reflect the typical medical environment in Japan. The consultation time of a hospital is divided into several blocks, and each scheduled patient is given the start time of a block as his or her scheduled time of the consultation as an appointment. It is assumed that all scheduled patients arrive at the hospital at their scheduled times, while walk-ins arrive randomly. A set of candidate appointment schedules is given, and the process of selecting promising schedules in terms of average waiting times is the focus of the work. To support the selection process without conducting a conventional simulation, the notion of a clearing function is adopted to evaluate each candidate schedule. The clearing function of a system gives the expected output or throughput of the system under varying levels of workload of the system. Although it is necessary to conduct exploratory experiments in advance to obtain the clearing function, the expected waiting time can be estimated by simple calculations with the aid of the clearing function. The average waiting times of four schedules in two scenarios are calculated and compared with those obtained from conventional simulations. It is revealed that the proposed procedure based on the clearing function gives acceptable estimated average values.

Policy for Rearranging Workers for a Self-Balancing Production Line with Worker Learning

In the traditional production lines such as assembly lines, each worker is usually assigned to a particular fixed position, and the speed of performing the task decreases until the worker masters the assigned work. However, when an imbalance in the speeds of the workers exists, any given worker can delay the overall work on the production line, and the production rate of the particular line will also decrease. To avoid this problem, the “Self-Balancing Production Line” was introduced. In this type of production line, each worker is assigned work dynamically so they can keep the production line balanced while satisfying the specific conditions. A previous paper studying worker learning has been published. When a worker learns, the speed of the worker can be increased. In that paper, the authors analyzed the conditions with and without passing and claimed that if passing is allowed, self-balancing of a production line can be achieved. However, even if the initial sequence is slowest to fastest (this is the best sequence for self-balance in the previous paper) and if passing is allowed, much more time is required to balance some conditions of speed and degree of learning (we call this the learning rate). Therefore, a new policy for rearranging workers that changes the sequence before passing should be considered for rapid balance of the production line. In this paper, the policy for rearranging workers that changes the sequence being learned is proposed, and to verify the policy, numerical experiments are performed under various conditions of speed and learning rate.

An adaptive cellular manufacturing system for responding to changes in demand

Cellular manufacturing systems are designed for producing multiple products effectively, and the configuration should be changed responding to changes in demand for each product for maintaining the effectiveness. In this paper, we propose an adaptive cellular manufacturing system that can change the configuration responding to real-time changes in demand. Markov chain model of the system is proposed, and the performance is analyzed and compared with that of previous cellular manufacturing systems.

Integrated Approach for Self-Balancing Production Line with Multiple Parts

In a “Self-Balancing Production Line”, each worker is assigned work dynamically, thus they can keep the balanced production under satisfying the specific conditions. For structure of line, in-tree assembly network line has been analyzed in previous paper. In that paper, line are virtually integrated to one and slowest to fastest sequence can be balanced under the integrated line. However, if an item consists of multiple parts and parallel work is possible, a new approach is applicable under the condition, and performance measure increase comparing to integrated line. In this paper, new integrated approach for both previous self-balancing line and buffer is proposed, and we compare the line that had been proposed in the previous paper.