Kanban design and management based on SOR model

Ruihang Ma; Chuan Wang; Xiangdong Kong; Lei Liu

doi:10.1117/12.3007631

25 October 2023 Kanban design and management based on SOR model

Ruihang Ma, Chuan Wang, Xiangdong Kong, Lei Liu

Proceedings Volume 12801, Ninth International Conference on Mechanical Engineering, Materials, and Automation Technology (MMEAT 2023); 128012K (2023) https://doi.org/10.1117/12.3007631
Event: Ninth International Conference on Mechanical Engineering, Materials, and Automation Technology (MMEAT 2023), 2023, Dalian, China

Abstract

With the advent of Industry 4.0, information has become the driving force of the manufacturing industry. The interactive process of manufacturing information is full of volatility, complexity and uncertainty. In the modern production management system, lean production brings greater benefits, in which Kanban management coordinates the production system of the entire organization and guides operations. The premise of a reasonable and orderly operation of the manufacturing industry is a team skilled in controlling information. This paper takes a manufacturing and assembly company in Henan Province as the research object, and integrates its information flow. From the perspective of "Stimulus-Organism-Response", the original Kanban was designed. The research results show that the reasonable layout of Kanban information can shorten the time-consuming process of worker identification information by 52.6%, which is very important for the company to carry out lean manufacturing.

(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Ruihang Ma, Chuan Wang, Xiangdong Kong, and Lei Liu "Kanban design and management based on SOR model", Proc. SPIE 12801, Ninth International Conference on Mechanical Engineering, Materials, and Automation Technology (MMEAT 2023), 128012K (25 October 2023); https://doi.org/10.1117/12.3007631

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available