2005 Fiscal Year Final Research Report Summary
Study on IT-based Evolution of JIT production systems
| Project/Area Number |
16510112
|
|---|
| Research Category |
Grant-in-Aid for Scientific Research (C)
|
| Allocation Type | Single-year Grants |
|---|
| Section | 一般 |
|---|
| Research Field |
Social systems engineering/Safety system
|
|---|
| Research Institution | Aichi Institute of Technology |
|---|
Principal Investigator |
OHNO Katsuhisa Aichi Institute of Technology, Faculty of Management and Information Science, Professor, 経営情報科学部, 教授 (50026118)
|
|---|
| Co-Investigator(Kenkyū-buntansha) |
TAMURA Takayoshi Nagoya Institute of Technology, Graduate School of Engineering, Professor, 工学研究科, 教授 (70093101)
NAKADA Koichi Nagoya Institute of Technology, Graduate School of Engineering, Professor, 工学研究科, 教授 (50207825)
KOJIMA Mitsutoshi Nagoya Institute of Technology, Graduate School of Engineering, Research Assistant, 工学研究科, 助手 (20273310)
SUZUKI Tatsuo Aichi Institute of Technology, Faculty of Management and Information Science, Professor, 経営情報科学部, 教授 (00064949)
ITO Masaru Aichi Institute of Technology, Faculty of Management and Information Science, Professor, 経営情報科学部, 教授 (80221026)
|
|---|
| Project Period (FY) |
2004 – 2005
|
| Keywords | Just-In-Time production system / IT-based evolution / mixed-model assembly line / Neuro DP algorithm / Optimization algorithm / Cell production system / vehicle routine problem / 最適統合生産 |
|---|
| Research Abstract |
The information cost is reducing rapidly due to the information technology (IT) revolution. In this study, we attempt to evolve JIT production systems by utilizing IT fully. The following five points are the results obtained through this study :
1.An academic book "Just In Time production system" was written by the above investigators and others in Japanese and was published by Nikkan Kougyou Shinbunsya in 2004.
2.An optimal control problem for a failure-prone multi-stage production and distribution system with stochastic demand that minimizes expected total cost per unit time is formulated as an undiscounted Markov decision process. A new neuro DP algorithm called the SBMPIM is developed to solve the problem. Moreover, the expected total costs per unit time of pull production systems such as Base stock, Kanban and CONWIP are numerically compared with the expected total costs per unit time computed by the SBMPIM.
3.Practical and efficient algorithms are developed for solving optimization problems of mixed-model assembly lines with complex constraints.
4.Performance evaluation algorithms of various types of cell production systems, which are adapted to diversification of customer demand and a short product life cycle, are development by organically combining queueing theory with simulation.
5.Practical meta-heuristic algorithms for solving three-dimensional packing problems and vehicle routine problems are developed to attain optimal distribution systems based on the JIT philosophy.
|
