Reduction of oscillating demand magnification effect in supply chain.
Veza, Ivica ; Gjeldum, Nikola ; Bilic, Bozenko 等
1. INTRODUCTION
In a supply chain, for a typical final product consumer, even when
consumer sales do not seem to vary much, there is pronounced variability
in the retailers' orders to the wholesalers. Orders to the
manufacturer, and to the manufacturers' supplier, oscillate even
more. According to the lean production principles, excessive production
and high inventory level are the biggest waste in production process
(Rother, 2003). To solve the problem of distorted information, companies
need to first understand what creates the oscillating demand
magnification effect, so called Bullwhip effect so they can counteract
it (Tempelmeier, 2006). Innovative companies in different industries
have found that they can control the Bullwhip effect and improve their
supply chain performance by coordinating information and planning along
the supply chain.
2. CAUSES OF THE BULLWHIP EFFECT
Because costumer demand is rarely perfect stable, business must
forecast its own demand in order to properly position inventory. Demand
forecasting is frequently different from the actual production plan
(Nishioka, 2003). Because forecast errors[degrees]Ccurs, companies need
to have an inventory buffer called safety stock. Some of the main causes
for Bullwhip effect are (Lee, 1997):
* Demand forecast mistakes
* Order batching
* Price and season fluctuation
* Costumer order reductions or cancellations
* Adjustment of inventory control parameters with each demand
observation
* Misperceptions of feedback and time delays
* Panic ordering reactions after unmet demands
The described effect can lead to either inefficient production or
excessive inventory as the producer needs to fulfil the demand of its
predecessor in the supply chain. This also leads to a low utilization of
the distribution channels. It is important to use techniques and tools
that can control the Bullwhip effect, that is, to control the increase
in variability in the supply chain (Simchi-Levi 2000).
3. CHANGING DEMANDS IN A SUPPLY CHAIN
In this paper, a three-stage supply chain is presented, where
manufacturer, responsible for consumer order demands fulfilling, is
supplied with raw materials and semi products by two tiers of suppliers.
The supply chain is modelled in ProModel software, to acquire data and
graphs about intermediate orders and inventory levels of supply chain
participants by its statistical module.
The most common changing demand cases as input data for simulation
are described together with direct consequences on supply chain material
flow. All participants in the supply chain change the order demands for
resumption of inventory level in one order period. The demands quantity
changes as follows:
1) The order demand is constant at initial value of 100 items, up
to period 4. Intermediate order quantities are constant at all three
stages.
2) In period 4 the order demand is increased for 10%, and then
returned to initial value in. The demands in intermediate participants
are respectively magnified in period 4, and the last participant,
Supplier 2 increases production for 80 %. The next period, results with
cancellation of Supplier 2 production. This variation is caused by
Bullwhip effect.
3) For next two periods, 6 and 7, of same effect like in point 2),
the magnification is even larger, and results with 120 % higher Supplier
2 production.
4) Periods 7 to 13 are set at constant initial value to present
speed of stabilization for intermediate demand quantities.
5) Periods 14 to 19 show the reaction on 20 % demand reduction. The
magnification is strong enough to cause cancellation of Supply 2
production in period 15.
6) Periods 20 to 31 are set to change order from 80 items to 250
items in 10% incremental increases in every period. Intermediate orders
are unstable and magnified in start of increasing period, but stabilized
as order quantity increasing continues.
The conclusion can be made that the Bullwhip effect[degrees]Ccurs
only in case of demand quantities change after periods of constant
orders quantity, or after periods of constantly increasing or decreasing
orders quantities. The bigger deviation from previous order quantity
trend results with stronger Bullwhip effect.
The strong Bullwhip effect can be recognized in periods 4 to 8, and
than in period 14. In periods 20 and 32, the effect is weak, but also
influential on warehouse level quantity.
In the simulation model, the inventory level of 500 units is set in
every supply chain participant warehouse. The data about sequence of
released market orders, the intermediate order quantities along the
supply chain and the contents of every participant warehouse are shown
separately for every participant of a supply chain on Fig 1. and in
Table 1.
[FIGURE 1 OMITTED]
In order to reduce oscillating demand magnification effect in those
critical periods, the mathematical model is presented. The production
demand can be expressed by a linear equation:
Q = [x.sub.0] + [f.sub.1][x.sub.1] + [f.sub.2][x.sub.2] (1)
The value [x.sub.0] is production demand, and gives a production
plan according to the produced quantity in the previous period of
simulation. The first parameter [x.sub.1] is the difference between
quantity in current order from upstream participant and produced
quantity in last period. The second parameter [x.sub.2] is difference
between current inventory level and inventory level which has to be
maintained.
In order to achieve the smallest range of order variation, and
smallest range of inventory level during simulation, factors of
signification f1 and f2 are optimized. For this particular order
sequence factors of signification are f1=0.75 and f2=0.62, so the
optimal mathematical model is:
Q = [x.sub.0] + 0.75[x.sub.1]+0.62[x.sub.2] (2)
[FIGURE 2 OMITTED]
The graphical results of improved behaviour of supply chain are
shown on Fig 2.
4. CONCLUSION
The Bullwhip effect[degrees]Ccurs in case of demand quantity change
from achieved routine in previous period. The routine can be constant
order quantity and increasing or decreasing order quantity during
previous period. The second main prerequisite for Bullwhip effect is
rapid response on order quantity demand change with intention for
resumption of inventory level in one period assuming the new order
quantity will maintain in next periods. This results with progressive
increase or decrease order quantity in upstream supply chain stages. The
aim of this paper was to define approach with mathematical model used
for defining intermediate order quantities in supply chain which reduce
Bullwhip effect by changing the factors of signification in order to
achieve satisfying speed of response on changing order quantities. The
research described in this paper was necessary preliminary work before
modelling of virtual production network without significant influence of
Bullwhip effect in order to reduce excessive inventory, improve costumer
services and achieve effective transportation planning.
5. REFERENCES
Lee, H. L.; Padmanabhan, V. & Whang, S. (1997). The bullwhip
Effect in Supply Chains, Sloan Menagement, Review 38, Spring 1997,
93-102
Nishioka, Y. (2003). Collaborative Agents for Production Planning and Scheduling, Available from: http://www.pslx.org/en/doc/TR-001.pdf,
Accessed: 2008-06-18
Rother, M. & Shook, J.(2003), Learning to See, The lean
enterprise institute, ISBN: 0-9667843-0-8, Brookline Simchi-Levi, D.;
Kaminski, P. & Simchi-Levi, E. (2000).
Designing and managing the supply chain, McGraw-Hill Higher
education, ISBN:0-0256-26168-7, New York
Tempelmeier, H. (2006) Inventory menagement in supply
networks--problems, models, solutions, ISBN 3-83345373-7, New York
Tab. 1. Order quantities of
supply chain participants
Per. Mark. Manu. Supp. 1 Supp. 2
Order order order order
1 100 100 100 100
2 100 100 100 100
3 100 100 100 100
4 110 120 140 180
5 100 90 60 0
6 110 120 150 220
7 100 90 60 0
8 100 100 110 130
9 100 100 100 90
10 100 100 100 100
11 100 100 100 100
12 100 100 100 100
13 100 100 100 100
14 80 60 20 0
15 80 80 100 120
16 80 80 80 60
17 80 80 80 80
18 80 80 80 80
19 80 80 80 80
20 88 96 112 144
21 97 94 87 74
22 106 116 139 190
23 117 128 139 140
24 129 141 153 167
25 142 155 169 184
26 156 170 186 202
27 171 187 204 223
28 189 206 224 245
29 207 226 247 269
30 228 249 272 296
31 250 272 295 317
32 250 250 228 162
33 250 250 250 272
34 250 250 250 250
35 250 250 250 250
36 250 250 250 250
37 250 250 250 250
38 250 250 250 250
39 250 250 250 250
40 250 250 250 250