دانلود ترجمه مقاله مدل کمیت تولید اقتصادی با ظرفیت محدود و عدم ترمیم – مجله الزویر

فهرست مطالب:

چکیده
۱  مقدمه
۲  مدلسازی و فرمول نویسی
۱  ۲ فرمولاسیون
۲  ۲ محدودیت
۳  ۲ مدل نهایی
۳  روش حل
۴  روش حل
۵  مثال عددی
۶  تحلیل آماری
۷  نتیجه گیری

بخشی از ترجمه:

مقدمه

یکی از عوامل اصلی در هر فرایند تولید، مواد می باشد. مدیریت مواد با مقررات و کنترل جریان مواد به، در و از سازمان سرو کار دارد. کارایی جریان مواد تاثیرقابل توجهی برهزینه ها و همچنین قابلیت های درآمدزایی می گذارد. مدیریت مواد شامل تعادل بین کمبودها و مازادهای سهام در یک محیط نامعلوم می شود. با جهانی شدن تجارت در سالهای اخیر، شرکت ها مواد خام، قطعات و کالاهای آماده شده را در کره زمین تامین و توزیع می کنند. مشتریان خواهان دریافت سریع محصولات کیفی خود میباشند. در نتیجه، مدیریت موجودی کارآمد، برنامه ریزی و زمان بندی تولید برای نیل به انعطاف پذیری و پاسخ سریع، به یک برتری رقابتی اصلی تبدیل شده است. به منظور نیل به اهداف استراتژیهای عملیاتی، شرکت بایستی توانایی استفاده موثر از منابع و تقلیل هزینه ها را داشته باشد. در شرکت های تولیدی، زمانی که اقلام در داخل تولید می شوند، به جای اینکه از یک عرضه کننده خارجی بدست آیند، آنگاه اغلب از مدل کمیت تولید اقتصادی (EPQ) برای تعیین اندازه مقدار تولید بهینه استفاده می شود، اندازه ای که هزینه های کلی تولید/ موجودی را تقلیل می دهد. مدل EPQ کلاسیکی این گونه تصور می کند که در طول جریان تولید، کارخانه تولیدی عملکردی کامل ازخود به معرض نمایش می گذارد. اما، به خاطر تحلیل فرایند یا برخی فاکتورهای دیگر، اقلام کیفی ناقص حتمی و اجتناب ناپذیر می باشد.

 ۷٫ نتیجه گیری
مطالعه حاضر یک مدل EPQ با محدودیت ظرفیت تولید و نرخ تولید معیوب تصادفی و خرابی حین تعمیر را مطرح می کند. هدف ما تعیین طول دوره بهینه ، کمیت های سفارش معوقه، و کمیت های سفارش می باشد. تابع هدف مدل عددی پیشنهاد شده محدب می باشد. از دو مثال عددی و تحلیل های حساسیت با استفاده از توابع توزیع عادی و یکنواخت برای   و   به منظور تشریح کاربردهای عملی روش پیشنهادی استفاده شده است. این مطالعه، بینش های مدیریتی لازم در زمینه طراحی یک مدل EPQ با اقلام معیوب تصادفی و خرابی حین تعمیر برای دست اندرکاران عرضه می نماید. تحقیق آتی باید بر مسائل چند محصولی چند محدودیتی در یک محیط نامعلوم تاکید کند.

بخشی از مقاله انگلیسی:

Introduction

One of the critical factors in any production process is material. The management of material concerns the regulation ofthe flow of materials to, within, and from the organization. The efficiency of the material flow can substantially influencecosts as well as revenue generation capabilities [1]. The management of material involves a balance between the shortagesand excesses of stock in an uncertain environment. With the globalization of business in recent years, firms are sourcing anddistributing raw materials, components, and finished goods across the globe. Customers want to receive their quality productsquickly. As a result, efficient inventory management, production planning and scheduling to achieve flexibility andquick response has become a core competitive advantage. To achieve operation strategies goals, the company must be ableto effectively utilize resources and minimize costs. In manufacturing companies, when items are internally produced insteadof being obtained from an outside supplier, the economic production quantity (EPQ) model is often employed to determinethe optimal production lot size that minimizes the overall production/inventory costs. The classic EPQ model assumes thatduring a production run a manufacturing facility functions perfectly. However, due to process deterioration or some otherfactors, imperfect quality items are inevitable. Some examples of the rework processes are: printed circuit board assemblyin the PCBA manufacturing, metal components, and plastic injection molding. A considerable amount of research has beencarried out by Cheng [2], Chiu et al. [3], Chung [4], Lee and Rosenblatt [5], and Rosenblatt and Lee [6] to address the imperfectquality EPQ problem. They assumed that at some random time, the process might shift from an in-control to an out-ofcontrolstate. Hayek and Salameh [7] derived an optimal operating policy for finite production (EPQ) model with reworkand imperfect quality items. They assumed that all defective items were repairable and that backorders were allowed.Numerous studies have been carried out to address the problems of imperfect quality EPQ model with rework (see, forexample, [7–۱۲]). Chan et al. [13] presented a new EPQ model with increasing lower pricing, rework and reject situations.Teng et al. [14] studied optimal ordering decisions with returns and excess inventory. Islam and Roy [15] formulated anEPQ model considering flexible and reliable production process and with fuzzy demand-dependent-unit production cost.Bayindir et al. [16] considered the EPQ model with general inventory cost rate function and piecewise linear concave productioncosts, and proposed an effective solution procedure for deriving the economic order quantity. Hou [17] studiedan EPQ model with setup cost and process quality as a function of capital expenditure and developed an efficient procedureto derive the optimal production run time, setup cost, and process quality. Chiu et al. [10] investigated an EPQ model withscrap, rework, and stochastic machine breakdowns to determine the optimal run time and production quantity. Chiu [18]later showed that the same problem can be derived without derivatives. Li et al. [19] developed an EPQ-based model withplanned backorders to evaluate the impact of the postponement strategy on a manufacturer in a supply chain. Pentico et al.[20] extended the EPQ model with partial back ordering where the decision variables were production quantity and periodlength. Teng and Chung [21] considered the EPQ model under two levels of trade credit policy to optimize the productionquantity and period length. Chiu et al. [22] considered the effects of random defective rate and imperfect rework processon economic production quantity model. Wee et al. [23] developed an inventory model for items with imperfect qualityand shortage backordering. Taleizadeh et al. [24] developed an EPQ model under limited production capacity and scrapeditems production. Taleizadeh et al. [25] developed an EPQ model with stochastic scraped production rate, partial back orderingand service level constraint. From our literature search, none of the above has so far developed an economic productionquantity (EPQ) model with random defective items and failure in repair with capacity constraint. In the case of multi product-single machine systems, Haji et al. [26] studied an imperfect manufacturing process with rework where several productsare manufactured on a unique machine. Recently, Widyadana and Wee [27] studied the optimal deteriorating items productioninventory models with random machine breakdown and stochastic repair time. 2. Modeling and formulationThe imperfect quality EPQ model by Chiu et al. [14] considered a manufacturing process with a constant production rate Plarger than the demand rate D. This process randomly generates x percent of defective items at a rate k. All items produced arescreened and the inspection cost per item is included in the unit production cost CP. All defective items produced can be reworkedat a rate of P1, and rework starts when the regular production process ends. A random portion h of the reworked itemsis assumed to be scrap. Let k denote production rate of defective items during regular manufacturing process, and k can be expressedas the product of production rate P and the defective percentage x. Therefore, k ¼ Px. Let k1 denote production rate ofscrap items during rework, and k1 can be expressed as the product of reworking rate times the percentage of scrap items producedduring rework process. Hence, k1 ¼ P1h. A real constant production capacity limitation on a single machine on which allproducts are produced and that the setup cost is considered nonzero. Since all products are manufactured on a single machinewith a limited capacity, the cycle length for all of them are equal (T1 ¼ T2 ¼    ¼ Tn ¼ T). From Table 1, the main differencesbetween this research and others are as follows: Firstly, our model investigates multi-product single-machine. Secondly, weconsider capacity limitation. Moreover, during the regular production time, defective items may be produced randomly. Therandom fraction of defective items is reworked during the rework process and complete backordering is allowed.