Analysis of a bullwhip effect in supply chain with level constraints

Zadnja leta se gospodarske družbe in posamezna podjetja povezana v oskrbovalne verige soočajo z nestabilnimi razmerami, med katerimi je pomembnejše nihanje v potrebah kupcev. Ob upoštevanju nivojskih omejitev in različnih ovir pri prenosu informacij med posameznimi udeleženci v verigi, lahko nastanejo razlike v variancah naročil do dobaviteljev glede na povpraševanja kupcev. Velikost teh razlik pri premikanju po verigi navzdol ni vedno enaka in se odraža z nihanjem, ki je glavni pokazatelj obnašanja verige. Ta pojav je opredeljen kot učinek biča. Manjša kot je velikost učinka biča, manjše je nihanje in boljše je obnašanje verige. Takrat so tudi ostali rezultati verige boljši. V konceptu servisiranja kupcev iz zaloge plani proizvodnje in ostale aktivnosti temeljijo na napovedih povpraševanja kupcev. Da bi družbe in podjetja, vključena v oskrbovalno verigo, lahko imela vpogled v svoje potenciale v prihodnjih obdobjih, je bil v doktorski disertaciji analiziran učinek biča v oskrbovalnih verigah z nivojskimi omejitvami za prihodnje obdobje. V ta namen je bil zgrajen simulacijski model tročlenske verige s časovno vrsto sezonskega in desezoniranega značaja. V model je vgrajena skupna učinkovitost proizvodnih procesov (ang. Overall equipment effectiveness – OEE) in različna politika zalog. Simulacije različnih situacij so pokazale, da trenutni kazalec OEE in izbrana politika zalog vplivata na velikost učinka biča in s tem na obnašanje verige v prihodnje. Rezultati simulacij so potrdili naša pričakovanja, zato je model lahko uporaben tudi v širšem aplikativnem smislu.In the past few years, companies involved in the supply chins are facing instabilities, which the variations in costumer needs is significant. Considering level constraints and various barriers at the transfer of information between different members in the supply chain, the difference in the variances of orders and demand may occur. The measure of variances increasingly fluctuates by moving upstream the supply chain. This phenomenon is called the bullwhip effect, which is the most common way of describing supply chain behaviour. For small bullwhip values behaviour of supply chain is better what indicates a better supply chain results. In make-to-stock production systems production plans and activities are based on demand forecasting. Companies involved in supply chain, should be able to see their potential in future business. In the dissertation we have built the simulation model and experimented it (by simulating) with a special case of a simple three-stage supply chain using seasonal and deseasonalized time series of the market demand data in order to identify, illustrate and discuss influence of equipment effectiveness (OEE) and constrained inventory policies on bullwhip effect and other supply chain measures. Simulations of different situations have shown that the recent OEE level and chosen inventory policy influenced on future bullwhip measures and supply chain behaviour. Results have confirmed our expectation, so the model can also be used in broader applicative sense