The Optimal area covered with a single autonomous guided vehicle using Humanized Computing
سال انتشار: 1403
نوع سند: مقاله ژورنالی
زبان: انگلیسی
مشاهده: 270
فایل این مقاله در 13 صفحه با فرمت PDF قابل دریافت می باشد
- صدور گواهی نمایه سازی
- من نویسنده این مقاله هستم
استخراج به نرم افزارهای پژوهشی:
شناسه ملی سند علمی:
JR_IJIEPR-35-2_013
تاریخ نمایه سازی: 14 مهر 1403
چکیده مقاله:
The area coverage of machines on the production line to address the scheduling and routing problem of autonomous guided vehicles (AGV) is an innovative way to improve productivity in manufacturing enterprises. This paper proposed a new model for the optimal area coverage of machines in the production line by applying a single AGV to minimize both the transfer costs and the number of breakpoints of AGV. One of the unique advantages of the area coverage employed in the present study is that it minimizes transfer costs and breakpoints, and makes it possible to provide service for several machines simultaneously since the underlying assumption was finding a path to ensure that every point in a given workspace is covered at least once. Since rail AGV is used in this study, AGV can only pass horizontal and vertical distances in the production line. The reversal of the AGV path in vertical and horizontal distances implies failure and breakpoint in the present paper. The simulation results confirm the feasibility of the proposed method.
کلیدواژه ها:
autonomous guided vehicles (AGV) ، regional coverage ، failure ، horizontal distances ، vertical distances
نویسندگان
mansour abedian
Department of Industrial Engineering, Najafabad Branch, Islamic Azad University, Najafabad, Iran
Amirhossein Karimpour
Department of Industrial Engineering, Faculty of Engineering, Yazd University, Yazd,
Morteza Pourgharibshahi
Department of Industrial Engineering, Faculty of Engineering, Yazd University, Yazd,
Atefeh Amindoust
Department of Industrial Engineering, Najafabad Branch, Islamic Azad University, Najafabad, Iran
مراجع و منابع این مقاله:
لیست زیر مراجع و منابع استفاده شده در این مقاله را نمایش می دهد. این مراجع به صورت کاملا ماشینی و بر اساس هوش مصنوعی استخراج شده اند و لذا ممکن است دارای اشکالاتی باشند که به مرور زمان دقت استخراج این محتوا افزایش می یابد. مراجعی که مقالات مربوط به آنها در سیویلیکا نمایه شده و پیدا شده اند، به خود مقاله لینک شده اند :