دانلود مقاله ISI انگلیسی شماره 12409
عنوان فارسی مقاله

روش سیستماتیک برای تسطیح حجم کم و تولید ترکیبی بالا

کد مقاله سال انتشار مقاله انگلیسی ترجمه فارسی تعداد کلمات
12409 2013 6 صفحه PDF سفارش دهید 4770 کلمه
خرید مقاله
پس از پرداخت، فوراً می توانید مقاله را دانلود فرمایید.
عنوان انگلیسی
Systematic procedure for leveling of low volume and high mix production
منبع

Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)

Journal : CIRP Journal of Manufacturing Science and Technology, Volume 6, Issue 1, 2013, Pages 53–58

کلمات کلیدی
- تسطیح تولید - برنامه ریزی تولید - حجم پائین و تولید ترکیبی بالا - فن آوری گروهی - تولید ناب
پیش نمایش مقاله
پیش نمایش مقاله روش سیستماتیک برای تسطیح حجم کم و تولید ترکیبی بالا

چکیده انگلیسی

The application of conventional leveling approaches is limited to large scale production. This paper presents a systematic procedure for leveling of low volume and high mix production. It employs clustering techniques to group product types into product families. After that, a family-based leveling pattern is created which describes a repetitive sequence of capacity slots considering all families. According to the leveling pattern, each family is manufactured within a periodic interval. The paper provides a brief overview of the systematic procedure. It focuses on the creation of the leveling pattern using operations research methods and presents a real life application.

مقدمه انگلیسی

Production leveling also referred to as production smoothing or heijunka is an essential element of the Toyota Production System and lean production, respectively [1]. The objective of production leveling is to balance production volume as well as production mix [1] and [2]. Hereby, production leveling decreases variation in form of peaks and valleys in the production schedule [3]. It enables companies to enhance efficiency by reducing waste, overburden of people or equipment, and unevenness [1]. The objective of production leveling is to balance production volume as well as production mix by decoupling production orders and customer demand [1]. Thus, work load in production and logistic processes is balanced [3]. Conventional leveling approaches aim at distributing production volume and mix to equable short periods [3]. The sequence of these periods describes a kind of manufacturing frequency. According to this leveling pattern every product type is manufactured within a periodic interval, for example a day or a shift [4]. The duration of this interval is depicted by the key figure EPEI (every part every interval). The EPEI-value is used as an index for reactivity and it also reflects lot sizes [5]. An EPEI-value of one day, for example, reveals that all product types are manufactured once a day. Considering requirements of conventional approaches, leveling is predominantly utilized in large scale production. Nevertheless, it can be implemented in low volume and high mix production by means of an adapted leveling procedure presented here. The paper is organized as follows: after a brief literature review in Section 2, an overview of the procedure for leveling of low volume and high mix production is given in Section 3. This procedure consists of two fundamental steps. Section 4 deals with the first step. In this step product families are formed for leveling based on manufacturing similarities. Using these families, a leveling pattern is created in the second step. The methodology for leveling pattern creation is the focus of this paper. It is described in detail in Section 5. After that, a case study is presented in Section 6 and a conclusion is given in Section 7.

نتیجه گیری انگلیسی

This paper presents a systematic procedure for leveling low volume and high mix production based on the principles of Group Technology. This procedure uses clustering techniques to subsume the large number of product types into a manageable number of product families. These families are utilized to create a family-oriented leveling pattern. This aspect is focused on in this paper. It describes how product families can be used for leveling using operations research methods amongst others. In this context, a first real life application is presented. For further practical application a software tool kit was developed. This tool kit supports product family formation as well as pattern creation. For family formation the open-source data mining software RapidMiner was employed. The procedure for pattern creation described in Section 5 was implemented in MS Excel using VBA.

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