مشخصات مقاله | |
ترجمه عنوان مقاله | تصمیم گیری در مورد انتخاب ابزار ناب با استفاده از رویکرد QFD فازی و FMEA در صنعت تولید |
عنوان انگلیسی مقاله | Decision-making on the selection of lean tools using fuzzy QFD and FMEA approach in the manufacturing industry |
انتشار | مقاله سال 2022 |
تعداد صفحات مقاله انگلیسی | 12 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 | |
ایمپکت فاکتور(IF) |
8.673 در سال 2020 |
شاخص H_index | 207 در سال 2021 |
شاخص SJR | 1.368 در سال 2020 |
شناسه ISSN | 0957-4174 |
شاخص Quartile (چارک) | Q1 در سال 2020 |
فرضیه | ندارد |
مدل مفهومی | دارد |
پرسشنامه | ندارد |
متغیر | ندارد |
رفرنس | ندارد |
رشته های مرتبط | مهندسی مکانیک، مهندسی صنایع |
گرایش های مرتبط | ساخت و تولید، مدیریت نوآوری و فناوری، بهینه سازی سیستم |
نوع ارائه مقاله |
ژورنال |
مجله | سیستم های خبره با برنامه های کاربردی – Expert Systems with Applications |
دانشگاه | Department of Mechanical and Industrial Engineering, Indian Institute of Technology Roorkee, India |
کلمات کلیدی | نقشهبرداری جریان ارزش، تولید ناب، منطق فازی، FMEA، میانگین هندسی وزندار فازی، QFD |
کلمات کلیدی انگلیسی | Value stream mapping, Lean manufacturing, Fuzzy logic, FMEA, Fuzzy weighted geometric mean, QFD |
شناسه دیجیتال – doi |
https://doi.org/10.1016/j.eswa.2021.116416 |
کد محصول | E15992 |
وضعیت ترجمه مقاله | ترجمه آماده این مقاله موجود نمیباشد. میتوانید از طریق دکمه پایین سفارش دهید. |
دانلود رایگان مقاله | دانلود رایگان مقاله انگلیسی |
سفارش ترجمه این مقاله | سفارش ترجمه این مقاله |
فهرست مطالب مقاله: |
Abstract Keywords 1. Introduction 2. Literature review 3. Research methodology 4. Case study 5. Results and discussions 6. Conclusions 7. Compliance with ethical standards Declaration of Competing Interest References |
بخشی از متن مقاله: |
Abstract Lean manufacturing is a profound system designed to enhance every manufacturing industry’s efficiency by reducing waste through internationally recognized tools and techniques. Manufacturing industries strive to adopt lean concepts to maximize their resources like staff, facilities, materials, and schedules to be economically effective. However, managers face difficulty selecting the appropriate lean tools out of the many available LM tools for successful lean implementation. This study suggests an innovative approach to choose suitable lean tools to maximize these essential resources. Herein the Value Stream Mapping and plant layout are considered for waste identification. Fuzzy QFD and FMEA prioritize the crucial resources concerning the defined wastes and determine the risk associated with each failure mode’s sub-element for lean application. It saves time by analyzing only the most critical resources for a successful lean implementation since its focus only on the most important resources. The applicability of the proposed approach is demonstrated through a case study of an Ethiopian shoe manufacturing firm. With the aid of future state plant layout and value stream map, total cycle time is reduced by 56.3%, lead-time is reduced by 69.7%, materials transportation distance and transportation activities are reduced by more than 75%, and workers required are reduced from 202 to 200. 1. Introduction Companies adopt lean manufacturing (LM) principles and tools for various reasons, including global competition, an uncertain market environment, and rising customers’ expectations. The concepts of LM can make it possible to use their resources effectively and increase their competitiveness. According to Deif and ElMaraghy (2014) and Goshime, Kitaw, and Jilcha (2018), LM is characterized by doing more with less. It focuses on reducing/eliminating waste in order to increase productivity and maximize customer values (Belekoukias et al., 2014). With the origin of the Toyota Production System, several LM techniques and tools were developed and used to achieve lean. Some of them are TPM, JIT, TQM, kaizen, kanban, production smoothing, cellular manufacturing, one-piece flow, Value Stream Mapping (VSM), and standardized work. Most of them are adopted in discrete manufacturers (Kumar & Parameshwaran, 2018). LM techniques and tools where effectively implemented in Automotive (Vamsi Krishna Jasti & Sharma, 2014), chemical (Jilcha & Kitaw, 2015), textile industry (Hodge, Goforth Ross, Joines, & Thoney, 2011), construction (Ko, 2010; Aka, Danladi Isah, Eze, & Timileyin, 2020), and healthcare industries (Barberato, Freitas, Godinho, & Francisco, 2016). |