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    Research on Lead—time Compression of Inventory Integrating Remanufacturing and Manufacturing System for the IOT Environment

    2015-10-21 19:39:14HanShu-Xian

    Han Shu-Xian

    【Abstract】The lead time compression is the core of supply chain management with time competition and the powerful source of competitive advantage of supply chain.As an emerging technology,The Internet of things is a huge network which combined Various Information sensing device (such as RFID,infrared sensors,global position system,communication device,etc.)with internet.So it can improve information sharing,cut logistical operations time and reduce lead-time.Base on the assumption that the market demand forecast accuracy varies with lead-time,this paper will establish the inventory model of the remanufacturing/manufacturing system and give the optimization algorithms of this mode.Finally,the conclusion is validated through a numerical example,proved the practicability of the model in practice.

    【Key words】Remanufacturing;inventory;Lead-time compression;Forecast;IOT cost

    1.Introduction

    The supplychain enterprises from traditional precedence competition mode transfer to time based competition (time-based competition, TBC)[1]model because of market competition increasing and clients requirements rapidly changing.If you need to shorten the time span of demand forecasting and improve the accuracy of it,then likely the best choice is IOT for the shortest amount of lead time. The key technology of the IOT provides a possible for supply chain enterprises to cut lead times.Among existing researches on lead time of R/M integrated supply chain recyclable product parts, some do not take lead time as a variable to study the effect of lead time on the supply chain and benefit of members; others do not think about cost squeeze in lead time and specific methods for shortening lead time. In this paper, based on the hypothesis that there exists linear relation between demand prediction accuracy and lead time, shorten lead time of recyclable products by using key technology of Internet of Things and consider cost of Internet of Things and lead time as variables to determine inventory optimization model of R/M integrated supply chain[2].

    2.Model description

    Mostoftheremanufacturingof recycled products is the remanufacturing of some partsand components of these products.After the recycled products are detected and demounted,the available parts and components are cleaned,renovated or upgraded,so as to restore to the new state,and this process is called the remanufacturing of parts and components,and such partsandcomponentsandcalled remanufactured parts and components.The products assembled with the remanufactured parts and components are called remanufactured parts.Because of uncertainty of the recyclable parts and components,when there are insufficient recyclable parts and components,itisneededtopurchasenewonesforreplacement.Theremanufactu

    red parts and components and the new ones share a storagespace,therefore,theinventoryintegratingremanufacturingandmanufac

    turingsystem is formed.

    3.Basic hypothesis and symbols

    Accordingtotheinventoryintegratingremanufacturingandmanufacturing

    system given above,the single-variety partsandcomponents are considered, and it is assumed that:

    (1)It is assumed that the time from order submission to the goods receiving is T,and T is the lead time of supplier,and the time of order submissioninthewarehouseisrecorded as 0.Itis assumed that the warehouse of available parts and components does not submit the order at the time of 0,but in a time point t(0

    The market demand D is a random variable of normal distribution with mathematical expectation μ≡constant, and mean square error σ. Due to compression of lead time, the ordering time is delayed, the market information collected by the retailer more approximate to the sales season is more sufficient,so the forecast precision to the market demand is higher.RIFD technology is applied to compress the lead time of supply chain and improve the forecast of market demand.At t,the retailer can forecast that the density function of market demandXisf(x,t),distribution function is F(x,t),mathematical expectation μ and mean square error (i.e. forecast error)σ=σ+t,[4] in whichσ0is the forecasted mean square error at 0,σTis the forecasted mean square error at T,σT<σ0,i.e.the forecast accuracy is improve with the compression of lead time.

    (2)It is assumed that the remanufactured parts and components and the new ones are of equivalent quality replacement without difference, but theprice of new components is higher than that of the remanufactured one, and each price is C0 higher.

    (3)For the inventory cost, it is required to undertake the expense of key technical application of internet of things,so it is assumed that w is the unit cost of label of internet of things.

    (4)h is the inventory storage fee of unit parts and components.

    (5)CT is the total inventory cost.

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