Inventory Management With Supply Chain

SNU MAI Lab. 2004

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Inventory Management

in Closed-Loop Supply Chain

2004. 8. 21

임 치 훈

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Business Aspects of Closed-Loop Supply Chains–Rommert Dekker et al., Inventory Control in Reverse Logistics

Karl Inderfurth, Optimal policies in hybrid manufacturing/remanufacturing systems with product substitution


The Carnegie Bosch InstituteInternational Conference on Closed-Loop Supply Chains

Business Aspects of Closed-Loop Supply Chains

May 31 – June 2, 2001Pittsburgh, Pennsylvania

Inventory Control in Reverse Logistics

Rommer Dekker and Erwin van der Laan, Erasmus University Rotterdam, The Netherlands


A continuous time inventory model for a product recovery system with multiple options

Classification of Inventory Control Problems Classification of Inventory Control Problems

Inventory Control for Direct ReuseInventory Control for Direct Reuse

The Use of Accounting Information

Introduction

Inventory Control for Value-Added RecoveryInventory Control for Value-Added Recovery

Summary and Outlook


A schematic overview of reverse logistics situations


Classification of Inventory Control Problems

Return reason–Rework–Commercial return, outdated product–Product recall–Warranty return–Repair–End-of-use return–End-of-life return

Recovery option–Selling or donation–Store and reuse (direct reuse)–Value-added recovery–Recycle–Disposal


Inventory Control for Direct Reuse

Single-period Inventory Decision Problem–Considers only order quantity–Fashion product, final order problem–Vlachos and Dekker (2000)

• Known percentage of returns arrives in time to be resold• Most return recovery options can be reduced to the standard newsboy optimality equation

Multi-period Infinite Horizon Inventory Decision Problem–Considers both reorder point and order quantity–Spare parts control of a refinery–Fleischmann et al. (1997)

• Independent Poisson processes for demands and returns• (s,S) policies remain optimal

Multi-period Finite Horizon Inventory Decision Problem–Considers both reorder point and order quantity–Demand and returns are specified per period–Richter and Sombrutzki (2000)

• Reverse economic lot sizing model with an unlimited return quantity• Zero-inventory regeneration property


Inventory Control for Direct Reuse

Netting Approach–Considers returns as negative demands–The net demands are treated with traditional methods for single source inventory control–Van der Laan et al. (1996)

• Satisfactory method when return rates are low• The net demand is much more variable than the total demand

Direct Reuse in Network Inventories–Considers containers and reusable packaging–Determines how many containers are needed at each depot for a given time–Shen and Khoong (1995)

• Decision Support System for this problem

Disposal –When return rates exceed demand rates


Inventory Control for Value-Added Recovery

Late 1960’s inventory control for repairable inventory–Physical closed-loop system

• After repair the items stay with or return to the original owner/user

–A demand and a production return always coincide

Product Remanufacturing–Functional closed-loop system–Variability and uncertainty in the timing and quantity of product returns

→ Difficult to balance supply with demand

–Variability and uncertainty in the quality of returned products→ Operations involved with remanufacturing are usually of a very stochastic nature

–Toktay et al. (1999) – Kodak single-use camera–Krikke et al. (1999) – copiers at Océ

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The most common assumptions–Inventory systems are single item, single component systems–Product returns are independent of product demands–The demand and return processes are Poisson processes–Yields are certain–Processes are stationary–Leadtimes are constant and independent of the order size

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Optimal Policies–Inderfurth (1997)

• (L,M,U) policy • Remanufacturing leadtime = manufacturing leadtime, no fixed setup cost

–Minner and Kleber (1999)• Deterministic setting with dynamic demand and return patterns

–Inderfurth et al. (2001)• n different remanufacturing options, each sold on a separate market

Heuristic Policies–Muckstadt and Isaac (1981)

• Manufacturing – continuous review (s,Q) policy• Product returns are remanufactured upon arrival with stochastic service times and limited capacity

–Van der Laan et al. (1997)• Continuous review push and pull policies• The push policy concentrates stocks in serviceable inventory

–Inderfurth and Van der Laan (1998)• Treats the remanufacturing leadtime as a decision variable

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Dependency relation between demands and returns–Enables forecasts for timing and quantity of product returns–Kiesmüller and Van der Laan (2001)

• If good forecasts are incorporated in the inventory policy, they considerably improve system performance

–Kelle and Silver (1986)• Tracking and tracing of individual products leads to superior return forecasts

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Optimal policies in hybrid manufacturing/remanufacturing systems

with product substitution

International journal of production economics 90 (2004) 325-343

Karl Inderfurth*

*Faculty of Economics and Management, Otto-von-Guericke-University Magdeburg, Magdeburg, Germany

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A continuous time inventory model for a product recovery system with multiple options

General model formulation General model formulation

Case A. Short manufacturing leadtimeCase A. Short manufacturing leadtime

Case B. Short remanufacturing leadtimeCase B. Short remanufacturing leadtime

Decision problemDecision problem

Managerial insights

Further research

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Decision problem

If remanufactured products are significantly different from new ones, they are sold in different markets to different customers at different prices

If a company is willing to offer its customers of remanufactured items a higher-valued original one in an out-of-stock situation. (downward substitution)

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General model formulation

Optimally coordinated manufacturing/remanufacturing policy under product substitution

–Objective : maximize the expected profit –Single-stage, single-period–Independent stochastic demands for both product types–Deterministic leadtimes for manufacturing and remanufacturing–Stochastic returns of used products–Returned items which are not remanufactured will be disposed of

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Notation–i = M for manufacturing(MP)–i = R for remanufacturing(RP)

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Revenues from selling and salvaging MPs/expected revenues

Substitution quantity/expected amount of substitution

Expected total profit

Bound

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Case A. Short manufacturing leadtime

At the time of the manufacturing decision the number of returns R which can be used for remanufacturing is known with certainty

Optimization problem

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Theorem 1–TP(yM, yR) is jointly concave in yM and yR

→ Optimal reaction function

Theorem 2, 3–SM(yR) is monotonously decreasing with

• : Newsboy solution of the separate manufacturing problem (yR →∞)

• : Solution in case of zero RP inventory (yR = 0)

–SR(yM) is monotonously decreasing with • : Newsboy solution of the separate remanufacturing problem (yM = 0)

• : Solution in case of unlimited MP inventory (yM →∞)

optimal ‘order-up-to-levels’

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Optimal policy structure in Case A

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Case B. Short remanufacturing leadtime

At the time of the manufacturing decision the return uncertainty may not yet have been completely revealed

Optimization problem for remanufacturing

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Theorem 4–TPR(yR, yM, xR ,R) is jointly concave in yR

→ Optimal reaction function

from

Theorem 5–UR (yM) is identical to function SR(yM) in Case A

–So it is monotonously decreasing with

Optimal remanufacturing decision

Optimal profit from remanufacturing

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Optimization problem for manufacturing

Theorem 6–TPM(yM, xM, xR) is concave in yM

→Optimal reaction function

from

‘Manufacture-up-to policy’

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Optimal policy structure in Case B

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정리

Closed-Loop Supply Chain 의 Production Planning and Control–현재까지는 Inventory control 분야에 많이 집중되어 있음–Optimal policy 에 관한 연구들은 실제 사례에 사용하기 어려움–Heuristic method 사용한 inventory control 에 대한 논문 review 계획

Inventory Management With Supply Chain

Technology