مقاله انگلیسی رایگان در مورد مصرف نیرو در عملیات حفاری – الزویر 2019

 

مشخصات مقاله
ترجمه عنوان مقاله مدل پیش بینی مبتنی بر مکانیک برای پوشش ابزار و مصرف نیرو در عملیات حفاری و کاربردهای آن
عنوان انگلیسی مقاله A mechanics based prediction model for tool wear and power consumption in drilling operations and its applications
انتشار مقاله سال 2019
تعداد صفحات مقاله انگلیسی 14 صفحه
هزینه دانلود مقاله انگلیسی رایگان میباشد.
پایگاه داده نشریه الزویر
نوع نگارش مقاله
مقاله پژوهشی (Research Article)
مقاله بیس این مقاله بیس نمیباشد
نمایه (index) Scopus – Master Journals List – JCR
نوع مقاله ISI
فرمت مقاله انگلیسی  PDF
ایمپکت فاکتور(IF)
7.096 در سال 2018
شاخص H_index 150 در سال 2019
شاخص SJR 1.620 در سال 2018
شناسه ISSN 0959-6526
شاخص Quartile (چارک) Q1 در سال 2018
مدل مفهومی ندارد
پرسشنامه ندارد
متغیر ندارد
رفرنس دارد
رشته های مرتبط مهندسی مکانیک
گرایش های مرتبط ساخت و تولید
نوع ارائه مقاله
ژورنال
مجله / کنفرانس مجله تولید پاک – Journal of Cleaner Production
دانشگاه  The Key Laboratory of Contemporary Design and Integrated Manufacturing Technology, Ministry of Education, Northwestern Polytechnical University, China
کلمات کلیدی مدلسازی مصرف انرژی، حفاری، نیروی برشی، پوشش ابزار، بهینه سازی پارامتر
کلمات کلیدی انگلیسی Energy consumption modelling، Drilling، Cutting force، Tool wear، Parameter optimization
شناسه دیجیتال – doi
https://doi.org/10.1016/j.jclepro.2019.06.148
کد محصول  E12832
وضعیت ترجمه مقاله  ترجمه آماده این مقاله موجود نمیباشد. میتوانید از طریق دکمه پایین سفارش دهید.
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فهرست مطالب مقاله:
Abstract
Nomenclature
1. Introduction
2. Model of energy consumption considering tool wear in a drilling process
3. Energy consumption model calibration experiments
4. Model validations and discussion
5. Applications
6. Conclusions
Acknowledgements
References

 

بخشی از متن مقاله:
Abstract

We present a mechanics based model for predicting the power consumption of drilling operations. Different from existing power models in machining that ignore the tool wear, our model takes into full consideration the tool wear which is particularly pronounced in drilling and causes extra power consumption. For any given spindle speed n and feed rate f, our model establishes the relationship between the length of drill and the total power consumption as well as the amount of tool wear. With this prediction model established, we can then optimize the drilling parameters (n, f) towards different objectives, such as the two applications reported in this paper e to minimize the average power consumption per unit length of drill and to maximize the tool usage before its replacement. Physical drilling experiments of the proposed power prediction model and its two optimization applications are also reported in this paper which have validated the accuracy of the model and convincingly demonstrated its efficacy in deciding optimal drilling parameters (n, f) for energy minimization and other objectives.

Introduction

Drilling is a simple yet fundamental machining operation needed in many manufacturing applications. For example, it is estimated that there are more than 6500 holes in a medium-sized aeroplane (Portillo et al., 2012) and most of them are drilled. When drilling on hard materials (such as Nickel-based super-alloy) which are commonly used for aeronautical parts, the biggest concern is the wear of the tool as it typically deteriorates very fast due to the exceedingly large cutting force (Sun et al., 2015). As drilling is simple, when the tool is fixed, the only affecting machining parameters are the spindle rpm n and tool feed rate f. The fundamental process planning task is then to determine a best pair of (n, f) towards various objectives. In particular, amid today’s high societal attention on sustainability, the following objective on energy minimization naturally rises: how to plan (n, f) to minimize the average power consumption per unit length of drill? Another objective that is related to the cost of tool could be: given a tool replacement threshold on the tool wear (i.e., the maximum tool wear at which the tool must be replaced), how to find the best (n, f) so that the maximum length of drill can be achieved by a single tool? A similar minimization problem could also be defined on time efficiency. These objectives are different and may conflict each other. Regardless, the fundamental prerequisite is a correct modelling of the relationship among the tool wear, the length of drill, the power consumption, and the machining parameters (n, f).

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