انجام ماشینکاری با مصرف بهینه انرژی برای تولید پایدار
ترجمه نشده

انجام ماشینکاری با مصرف بهینه انرژی برای تولید پایدار

عنوان فارسی مقاله: یک مدل بهینه سازی برای انجام ماشینکاری با مصرف بهینه انرژی برای تولید پایدار
عنوان انگلیسی مقاله: An optimization model for energy-efficient machining for sustainable production
مجله/کنفرانس: مجله تولید پاک - Journal of Cleaner Production
رشته های تحصیلی مرتبط: مکانیک
گرایش های تحصیلی مرتبط: مکاترونیک، طراحی کاربردی
کلمات کلیدی فارسی: الگوریتم بهینه سازی کلونی مورچه، STEP-NC، ماشینکاری با مصرف بهینه انرژی
کلمات کلیدی انگلیسی: Ant colony optimization algorithm، STEP-NC، Energy-efficient machining
نوع نگارش مقاله: مقاله پژوهشی (Research Article)
نمایه: Scopus - Master Journals List - JCR
شناسه دیجیتال (DOI): https://doi.org/10.1016/j.jclepro.2019.05.271
دانشگاه: Department of Mechanical and Electrical Engineering, Ocean University of China, Qingdao, 266100, China
ناشر: الزویر - Elsevier
نوع ارائه مقاله: ژورنال
نوع مقاله: ISI
سال انتشار مقاله: 2019
ایمپکت فاکتور: 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
فرمت مقاله انگلیسی: PDF
تعداد صفحات مقاله انگلیسی: 13
وضعیت ترجمه: ترجمه نشده است
قیمت مقاله انگلیسی: رایگان
آیا این مقاله بیس است: خیر
آیا این مقاله مدل مفهومی دارد: ندارد
آیا این مقاله پرسشنامه دارد: ندارد
آیا این مقاله متغیر دارد: دارد
کد محصول: E13115
رفرنس: دارای رفرنس در داخل متن و انتهای مقاله
فهرست انگلیسی مطالب

Abstract


1- Introduction


2- Literature review


3- STEP-NC enabled approach


4- Energy consumption calculation via STEP-NC


5- Proposed model by considering energy consumption


6- An improved ACO solution for the proposed model


7- Case study and discussions


8- Conclusions


References

نمونه متن انگلیسی مقاله

Abstract


Sustainable production plays an important role in product lifecycle management by considering the social sustainability. Energy-efficient machining is an efficient approach for sustainable production in current manufacturing sectors. Although many related efforts have been achieved, a comprehensive energy optimization approach oriented to manufacturing parts is still a challenge. Therefore, this paper selects Standard for the Exchange of Product model data-Numerical Control (STEP-NC) as the enabling technology to achieve energy-efficient machining. An optimization model is proposed based on the energy calculation method using the workingstep in STEP-NC. An improved ant colony optimization (ACO) solution, consisting of encoding and decoding, initialization, machining scheme generation, idea of local multiple iteration, evaluation, pheromone evaporation and update, is presented. A part with typical manufacturing features is applied to verify the effectiveness of the proposed approach. The generated solution can provide a comprehensive machining scheme for low energy demandI by improving the efficiency with 25% for solving the optimization problem.


Introduction


Due to soaring energy prices and environmental pollution, research on sustainable product lifecycle management (SPLM) has been focused recently. Sustainable production is one important phase of SPLM. Reducing energy consumption during machining operations plays a critical role in achieving sustainable production, i.e., energy-efficient machining. Energy-efficient machining has attracted increasingly more efforts in recent years (CamposecoNegrete, 2013; Gong et al., 2016; Velchev et al., 2014; Yan and Li, 2013; Zhou et al., 2016). Deciding machining schemes (MSs) for a part to be machined from the perspective of energy efficiency is an effective way to perform energy-efficient machining. A MS consists of many key elements, e.g., machining resources, machining parameters, tool path, process route, etc. In general, there exist more than one reasonable MS, which could constitute a group of candidate machining schemes (CMSs), and the best machining scheme (BMS), i.e., energy-efficient machining scheme (EEMS), is generated from this group. It is obvious that this process refers to an optimization problem. To solve the optimization problem, two key procedures are necessary, i.e., optimization model and the corresponding solution method. An optimization model includes optimization objective, optimization variables and constraints. The objective may be single (i.e. only energy consumption) or multiple (e.g. time, energy, tool life, etc.). No matter single-objective or multipleobjectives optimization, an energy consumption model for indicating the energy calculation approach during machining processes is essential, which is used to formulating the optimization objective. Besides, the optimization variables are the contributing factors to the objective, and the constraints are determined in terms of the specific conditions. Regarding the solution method, a metaheuristic algorithm is a type of effective method of solving the optimization model, such as genetic algorithm (GA), ant colony optimization (ACO), particle swarm optimization (PSO), tabu search (TS), simulated annealing (SA) and NSGA-II.

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