| کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن | 
|---|---|---|---|---|
| 10321934 | 660776 | 2015 | 41 صفحه PDF | دانلود رایگان | 
عنوان انگلیسی مقاله ISI
												A real-time SPC inventory replenishment system to improve supply chain performances
												
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																																												کلمات کلیدی
												
											موضوعات مرتبط
												
													مهندسی و علوم پایه
													مهندسی کامپیوتر
													هوش مصنوعی
												
											پیش نمایش صفحه اول مقاله
												 
												چکیده انگلیسی
												Inventory replenishment rules contribute significantly to the bullwhip effect and inventory instability in supply chains. Smoothing replenishment rules have been suggested as a mitigation solution for the bullwhip effect but dampening the bullwhip effect might increase inventory instability. This paper evaluates a real-time inventory replenishment system denoted as SPC that utilizes a control chart approach to counteract the bullwhip effect whilst achieving competitive inventory stability. The SPC employs two control charts integrated with a set of decision rules to estimate the expected demand and adjust the inventory position, respectively. The first control chart works as a forecasting mechanism and the second control chart is devoted to control the inventory position variation whilst allowing order smoothing. A simulation analysis has been conducted to evaluate and compare SPC with a generalized (R, S) policy in a four-echelon supply chain, under various operational settings in terms of demand process, lead-time and information sharing. The results show that SPC is superior to the traditional (R, S) and comparable to the smoothing one in terms of bullwhip effect, inventory variance, and service level. Further managerial implications have been obtained from the results.
											ناشر
												Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Expert Systems with Applications - Volume 42, Issue 3, 15 February 2015, Pages 1665-1683
											Journal: Expert Systems with Applications - Volume 42, Issue 3, 15 February 2015, Pages 1665-1683
نویسندگان
												Francesco Costantino, Giulio Di Gravio, Ahmed Shaban, Massimo Tronci,