Forecasting of Service Parts Based on Fuzzy Reliability of the Product

This paper presents a forecasting model depends on the reliability of product and the failure of its parts to forecast the required quantity of spare parts. Fuzzy logic is integrated with the forecasted model to treat the uncertainty that may be exist around defining the parameters values. Fuzzification of the product reliability is constructed using alpha cut and triangular fuzzy number. The effect of fuzzy process on the forecasted required demand of spare parts will be studied in three cases: 1) fuzzification of the mean of the product reliability, 2) fuzzification of the standard deviation of the product reliability, and 3) fuzzification of both the mean and standard deviation of the product reliability. Four suggested defuzzification methods (mean-max, centroid, signed distance, and graded mean integration representation) were used to figure out the difference between the crisp and the fuzzy forecasted demand with its related costs and to save the stock with the suitable production ranges. From the results, the maximum deviation between the crisp and the fuzzy forecasted demand was resulted from the fuzzification of both the mean and the standard deviation with percentage range from 2.06 up to 5.45 that would save the non-stock out than crisp forecasting

Volume flexible multi items inventory system with imprecise environment

This paper addresses a multi items volume flexible system for time dependent decaying items with the concept of machine breakdown and imprecise environment. In this study, partially backlogged shortages have been discussed. All the costs are fuzzified with signed distance method. Numerical examples are given to illustrate the theoretical results and sensitivity analysis is given to validate the results for various parameters

A Fuzzy Two-warehouse Inventory Model for Single Deteriorating Item with Selling-Price-Dependent Demand and Shortage under Partial-Backlogged condition

In this paper we have developed an inventory model for a single deteriorating item with two separate storage facilities (one is owned warehouse (OW) and the other a rented warehouse (RW)) and in which demand is selling- price dependent. Shortage is allowed and is partially backlogged with a rate dependent on the duration of waiting time up to the arrival of next lot. It is assumed that the holding cost of the rented warehouse is higher than that of owned warehouse. As demand, selling- price, holding- cost, shortage, lost- sale, deterioration- rate are uncertain in nature, we consider them as triangular fuzzy numbers and developed the model for fuzzy total cost function and is defuzzified by using Signed Distance and Centroid methods. In order to validate the proposed model, we compare the results of crisp and fuzzy models through a numerical example and based on the example the effect of different parameters have been rigorously studied by sensitivity analysis taking one parameter at a time keeping the other parameters unchanged

Fuzzy production planning models for an unreliable production system with fuzzy production rate and stochastic/fuzzy demand rate

In this article, we consider a single-unit unreliable production system which produces a single item. During a production run, the production process may shift from the in-control state to the out-of-control state at any random time when it produces some defective items. The defective item production rate is assumed to be imprecise and is characterized by a trapezoidal fuzzy number. The production rate is proportional to the demand rate where the proportionality constant is taken to be a fuzzy number. Two production planning models are developed on the basis of fuzzy and stochastic demand patterns. The expected cost per unit time in the fuzzy sense is derived in each model and defuzzified by using the graded mean integration representation method. Numerical examples are provided to illustrate the optimal results of the proposed fuzzy models

WSNs Based- L4L Rule for Fuzzy Inventory Control Decision Making (WSN-FL4L)

تعد وظيفة السيطرة على الخزين واحدة من اهم الانشطة التي تقوم بها الشركات الصناعية . تلعب انظمة السيطرة على الخزين دور كبير في ضمان الرقابة التامة على عناصر المخزون. من جهة ثانية،  نال استخدام تقنية شبكات الاستشعار اللاسلكية اهتماماً كبيراً من حيث تطبيقها في حقل السيطرة على الخزين كونها تقنية كفوءة و رخيصة الثمن و سهلة التنصيب . اقترح البحث الحالي نظام سيطرة مخزنية ذكي بالاعتماد على تقنية الاستشعار اللاسلكي و المنطق المضبب، بالاعتماد على قاعدة حجم الدفعة المكافيء للاحتياج  ضمن نظام تخطيط الاحتياجات المادية ليمكن استخدامه لحل اغلب المشاكل الصناعية. تم تطبيق النظام المقترح على حالة افتراضية لمنتوج يمثل قطعة من الاثاث الخشبي خماسي الدواليب الجرارة.  تكمن فائدة النظام المقترح في قدرته على المساعدة في اتخاذ قرارات المخزون في ظل حالات مختلفة فقد تم اختبار حالات متعددة لاعادة تعزيز المخزون بالاعتماد على قاعدة (اذا – عند ذلك) من المنطق الضبابي. تم نشر وبرمجة حساسات لقياس المسافة لغرض حساب عدد قطع مفردات المخزون بالاعتماد على قياس سمك القطعة.. تم اعتماد تقنية ASP.net و لغة C# بالاعتماد على قاعدة بيانات في الخادم الرئيس. Inventory control is one of the most important tasks for industrial companies. Inventory control systems play an important role in inventory monitoring. Wireless Sensor Networks (WSNs) technology has been taken into great attention in the field of inventory control because it is considered as an efficient, low-cost technology to control inventories. This paper proposes an intelligent inventory control system depending on WSNs and fuzzy logic to control the dependent demand items effectively under MRP system and L4L lot sizing rule. to be used to solve the industrial problems. A numerical example of a 5 drawers - chest of drawers product has been experimented. The advantage of the proposed WSN-FL4L system could be represented in its ability to make decisions in different inventory states. Different cases of replenishment were investigated depending on the (IF-THEN rules) statement of fuzzy logic. Ultrasonic - distance sensor has been programmed to compute the number of items’ pieces, depending on the thickness of each piece. ASP.net web application and C# programming language based on SQL database server are applied

A Novel Method for Optimal Solution of Fuzzy Chance Constraint Single-Period Inventory Model

A method is proposed for solving single-period inventory fuzzy probabilistic model (SPIFPM) with fuzzy demand and fuzzy storage space under a chance constraint. Our objective is to maximize the total profit for both overstock and understock situations, where the demand D~j for each product j in the objective function is considered as a fuzzy random variable (FRV) and with the available storage space area W~, which is also a FRV under normal distribution and exponential distribution. Initially we used the weighted sum method to consider both overstock and understock situations. Then the fuzziness of the model is removed by ranking function method and the randomness of the model is removed by chance constrained programming problem, which is a deterministic nonlinear programming problem (NLPP) model. Finally this NLPP is solved by using LINGO software. To validate and to demonstrate the results of the proposed model, numerical examples are given