Download - Progress Presentation Final (4)Print

7/31/2019 Progress Presentation Final (4)Print

1/43

ByMiss Kamolwon Cha-Ume ID 5322300210

Industrial Engineering ProgramSirindhorn International Institute of Technology

Thammasat University


2/43

Introduction & Previous work studiedObjectivesLiterature Reviews

MethodologyResults & DiscussionsConclusionFurther Study


3/43

The companies that can response to the changefrom customers faster more competitiveadvantage over the othersNeed to understand different types ofuncertaintiesApply some tools/ policies to reduce theuncertainties in the system or to maximize thewhole chain profits


4/43

Study different factors thateffecting the profitability of aretail store

Construct a simulation modelthat can capture the overalloperation of the whole supply

chain Study and compare the basecase with different types ofuncertainties

Study the interaction effectswith different type ofuncertainties

Study two components of thedouble probabilistic setting:epistemic and aleatoryuncertainty Suggest solutions for reducinguncertainties in the system Investigate effects of inventorypolicy (Lateral Transshipment) Apply two types oftransshipment policies : TBAand TIE to the model

Analyze and investigate eachtype of uncertainty in moredetails


5/43

To understand the application of LateralTransshipment in a retail Supply Chain networkTo study various types of Lateral TransshipmentPolicies

To find the optimal policy of LateralTransshipment in order to reduce supply shortageTo analyze and evaluate the effects andsignificances along with providing suitable

recommendations


6/43

Two components of the double probabilistic setting: aleatoryand epistemic uncertainty (De Rocquigny et al.,2008)

Aleatory uncertainty is to sampling the demand for anappropriate mean

- arises from an inherent randomness in the properties orbehaviour of the system under study

Epistemic uncertainty is to sampling the mean ofuncertainty- derives from a lack of knowledge about the appropriatevalue to use for a quantity that is assumed to have a fixedvalue in the context of a particular analysis


7/43

Base model (No lateral transshipment)(NLS)Lateral Transshipment Based on Availability (TBA)Lateral Transshipment for Inventory Equalization(TIE)

Lateral Transshipment with service leveladjustment (SLA)


8/43

Retailer A Retailer B Retailer C Retailer D

Overstock 10 units Overstock 2 units Stock out 5 units Stock out 3 units

Transshipment quantity = Min( Max(Overstock) ,Max (Stock out) )= Min (10,5) = 5


Overstock 5 units Overstock 2 units Stock balance Stock out 3 units

Transshipment quantity = 3 units

Stop process , No stock out

Transshipment can be done many times in a cycle


9/43


Inventory 10 units

Inventory 2 units

Inventory5 units

Inventory3 units

Forecast demand4 units




Redistribution of Stock According to the Proportion of Demand


E1 = 8 units E2 = 6 units E3 = 4 units E4 = 2 units

Lateral Transshipment for Inventory Equalization (TIE)

Pick-up 10-8 =2 Drop-off 6-2=4 Pick-up 5-4= 1 Pick-up 3-2=1

Transshipment can be done only one time in a cycle


10/43


Upper Level

Target Level

Lower Level

Transshipped Quantity = Min ( 5 , 2 ) = 2

Assume all retailers have the same level For example; If = 9 and = 2Upper level = int (9 + 0.52x2) = 10

For example; If = 5 and = 2 Lower level = int(5 - 0.82 x 2) = 3Target level = int (5 + 0 x 2) = 5

10

3

5

15 units

5 units

2 units

7 units

Retailer A Retailer DTransshipped 2 units

Transshipment can be done many times in a cycle


11/43

Steps of the overall modelManufacturer model stepsRetailers model steps


12/43


13/43

Retailer x 4


14/43

C u s t o m e r

D e m a n

d

( I n

t e r - a r r i v a

l t i m e o

f c u s t o m e r s ) NORM (2, 25% of the mean)

NORM (2, 50% of the mean)



Retailer 1

Retailer 2

Retailer 3

Retailer 4

Wagner Within Algorithm8 Week Rolling

Planning Horizon

Manufacturer

Supplier


15/43

This will be used to vary

**(Excluded from the model)

Epistemic Uncertainty


16/43

Maximize Profit = Manufacture Profit +(Retailer 1s Profit + Retailer 2s Profit+Retailer3s Profit + Retailer 4s Profit )

Manufacture Profit = Sale (RM Cost +Reorder Cost + Operating Cost +Holding Cost+ Penalty Cost )


17/43

Retailer Profit = Sale (RM Cost +Reorder

Cost + Operating Cost +Holding Cost+ Penalty Cost)


18/43

Constraint: Profit of Each Member 0

Decision variables Target Stock Levels(TSL) at Retailer 1, Retailer 2, Retailer 3,and Retailer 4

These variables will be searched for theiroptimal setting by the OptQuestThe lower and upper bounds guaranteed to belarge enough to ensure that the optimal settingfalls inside the boundary


19/43

ManufactureSelling price = $20/unitRM cost = $5/unitHolding cost = $0.16/unit/weekShortage cost = $20/unit

Production cost = $5/unitOrdering cost = $ 250/order

RetailerSelling price = $50/unitHolding cost = $0.40/unit/weekShortage cost = $50/unitOrdering cost = $250/orderOperating cost = $100/unit/year


20/43

Transshipment costsThe cost of transshipment will be set at sixdifferent levels to observe the effect on theprofitability

Transshipment cost = 0%, 20%, 40%, 60%, 80%,and 100% of the shortage cost, which is equalto $0, $10, $20, $30, $40 and $50 per each unittransshipped respectively


21/43


22/43


23/43

Note:

1. Assume there are no uncertainties in demand, supply and lead time butthere is a variation in inter-arrival time ( Aleatory uncertainty)2. Aleatory uncertainty is an inherent variation associated with thephysical system or the environment also referred to as variability,

irreducible uncertainty, and stochastic uncertainty, random uncertainty

Using the following Optimized Target StockLevel for the base model

Optimized TSL Retailer 1(units)

Retailer 2

(units)

Retailer 3

(units)

Retailer 4

(units) Base Case 114 117 120 124


24/43

Retailer 4 has the highest variation ofnorm(2,100% of the mean)

Lowest profitRevenue and RM are lowestHolding cost and operating cost are highest

Aleatory uncertainty has an effect to theprofit of retailers


25/43

Lateral Transshipment Based onAvailability (TBA)

Lateral Transshipment for InventoryEqualization (TIE)

Service Level Adjustment (SLA)


26/43


27/43

560,000.00

570,000.00

580,000.00

590,000.00

600,000.00

610,000.00

620,000.00

0% 20% 40% 60% 80% 100%

P r o

f i t ( $ )

% Variation of transshipment cost with respect to shortage cost

Whole Chain Profit Comparison of Base Case

NLS

TBA

TIE

SLA


28/43

At the Base Case setting, SLA is the policythat generates highest profits under allpercentage of transshipment cost levels

Profits generated by TBA decrease the mostdrastically as the transshipment costincreasesTIE is the only policy where profits generated

rises with increasing of the transshipmentcost


29/43


30/43

The uncertainties cause a negative impact onthe whole chain s profitHigh level of uncertainty has the largest effect

on both types of uncertaintiesProcess uncertainty has higher effect thandemand uncertaintyA high level of process uncertainty (HM) the

profit has reduced up to 9.66%A low level of demand uncertainty (LD) theprofit has reduced only 1.93%


31/43


32/43

Transshipment leads to a significant increase inprofits when the transshipment policies areapplied The TBA policy is better, when the % variationis around 0% to 20% of transshipment cost withrespect to shortage cost

Higher number of transshipment reduce theexcess inventory (lower the overall holding costs

and shortage costs)TBA is not beneficial transshipment cost ishigh or closed to the shortage cost (the holdingcosts and transshipment cost have incurred)


33/43

The TIE policy is better, when thetransshipment cost with respect to shortagecost is greater than 50%

TIE has higher profit than TBA policyTIE will perform only once per cycle less effectto transshipment costsThe total holding cost stable

The SLA is the policy that generates highestprofits in most of the cases


34/43

The main reason forhigh profit of SLAmodel highnumber of lateral

transshipment doneby the model

The transshipmentquantity of TIE islowest because thetransshipment canbe done only onceduring each cycle


35/43

It is recommended SLA policy if theirtransshipment costs are under 80% variationwith respect to shortage cost, and TIE iftransshipment costs otherwise


36/43


37/43

Introducing transshipment helps the supply chain todeal with the problem of having stock out whenthere is demand and process uncertaintyThe TBA policy is recommended the

transshipment cost with respect to shortage cost isaround 0% to 20%The TIE policy is recommended the transshipmentcost with respect to shortage cost is greater than

50%The SLA policy generates the highest profits inmost of the cases


38/43

It is recommended SLA policy if the transshipmentcosts are under 80% of the shortage cost, and TIE ifotherwiseFactors that need to be considered before

implementing transshipment- Holding cost- Transshipment cost- Shortage cost


39/43


40/43

Introduce self decision making simulationmodel

1) If need to do transshipment policy which policy should be implemented?

2) Select whether to do or not to dotransshipment policy Check the profitof implemented transshipment > NLS?


41/43


42/43

International Conference on Business andInformationDate : 4 July 2012 , Sapporo (JAPAN)Title : The impact of uncertainty and transshipmenton a retail supply chain under various transshipment

policies and costsInternational Journal of Logistics Systems andManagemen t (With no impact factor)

Accepted: May 2012

Published: 27 August 2012 Title: Simulation of retail supply chain behaviour andfinancial impact in an uncertain environmentReference: Int. J. Logistics Systems and Management,Vol. 13, No. 2, pp.162 186.


43/43

Download - Progress Presentation Final (4)Print

Top Related