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R. Grubbström, J. Wikner (1996)
Inventory trigger control policies developed in terms of control theoryInternational Journal of Production Economics, 45
S. Disney, D. Towill (2005)
Eliminating drift in inventory and order based production control systemsInternational Journal of Production Economics, 93
Jeroen Dejonckheere, S. Disney, M. Lambrecht, D. Towill (2003)
Measuring and avoiding the bullwhip effect: A control theoretic approachEur. J. Oper. Res., 147
Management Science, 35
S. Disney, M. Naim, A. Potter (2004)
Assessing the impact of e-business on supply chain dynamicsInternational Journal of Production Economics, 89
S. Disney, D. Towill, R. Warburton (2006)
On the equivalence of control theoretic, differential, and difference equation approaches to modeling supply chainsInternational Journal of Production Economics, 101
M. Ortega, L. Lin (2004)
Control theory applications to the production–inventory problem: a reviewInternational Journal of Production Research, 42
G. Evans, M. Naim, D. Towill (1998)
Application of a simulation methodology to the redesign of a logistical control systemInternational Journal of Production Economics
D. Towill (1982)
Dynamic analysis of an inventory and order based production control systemInternational Journal of Production Research, 20
H. Sarimveis, Panagiotis Patrinos, C. Tarantilis, C. Kiranoudis (2008)
Dynamic modeling and control of supply chain systems: A reviewComput. Oper. Res., 35
D. Towill, G. Evans, P. Cheema (1997)
Analysis and design of an adaptive minimum reasonable inventory control systemProduction Planning & Control, 8
T. Hosoda, M. Naim, S. Disney, A. Potter (2008)
Is there a benefit to sharing market sales information? Linking theory and practiceComput. Ind. Eng., 54
S. Disney, D. Towill, W. Velde (2004)
Variance amplification and the golden ratio in production and inventory controlInternational Journal of Production Economics, 90
Virginia Spiegler (2013)
Designing supply chains resilient to nonlinear system dynamics
A. White, M. Censlive (2013)
An alternative state-space representation for APVIOBPCS inventory systemsJournal of Manufacturing Technology Management, 24
B. Jacob, H. Zwart (2012)
State Space Representation
R. Warburton, S. Disney, D. Towill, J. Hodgson (2004)
Technical Note: Further insights into ‘the stability of supply chains’International Journal of Production Research, 42
S. Disney, D. Towill (2003)
On the bullwhip and inventory variance produced by an ordering policyManagement Science
J. Simon, M. Naim, D. Towill (1994)
Dynamic analysis of a WIP compensated decision support system
Yongchang Wei, Hongwei Wang, Chao Qi (2013)
On the stability and bullwhip effect of a production and inventory control systemInternational Journal of Production Research, 51
DEPARTEMENT TOEGEPASTE ECONOMISCHE WETENSCHAPPEN
H. Simon (1952)
On the Application of Servomechanism Theory in the Study of Production ControlEconometrica, 20
Xun Wang, S. Disney (2016)
The bullwhip effect: Progress, trends and directionsEur. J. Oper. Res., 250
Logistyka, 12
Herbert Vassian (1955)
Application of Discrete Variable Servo Theory to Inventory ControlOper. Res., 3
Santiago Tosetti, H. Patiño, F. Capraro, A. Gambier (2008)
Control of a production-inventory system using a PID controller and demand predictionIFAC Proceedings Volumes, 41
European Journal of Operational Research, 153
S. Disney, M. Lambrecht (2008)
On Replenishment Rules, Forecasting, and the Bullwhip Effect in Supply ChainsFound. Trends Technol. Inf. Oper. Manag., 2
K. Åström, T. Hägglund (2000)
The future of PID controlControl Engineering Practice, 9
K. Åström, P. Kumar (2014)
Control: A perspectiveAutom., 50
Stephen Boyd, C. Barratt (1991)
Linear controller design: limits of performance
C. Riddalls, S. Bennett (2002)
Production-inventory system controller design and supply chain dynamicsInternational Journal of Systems Science, 33
Berrin Ağaran (2007)
Regulating Bullwhip Effect in Supply Chains through Modern Control TheoryPICMET '07 - 2007 Portland International Conference on Management of Engineering & Technology
D.L. Capozzi, C. Vecchio, L. Glielmo (2003)
A novel work in progress based production control system2003 European Control Conference (ECC)
K. Hoberg, U. Thonemann (2015)
Analyzing Variability, Cost, and Responsiveness of Base-Stock Inventory Policies with Linear Control TheoryIIE Transactions, 47
S. Cannella, E. Ciancimino (2010)
On the Bullwhip Avoidance Phase: supply chain collaboration and order smoothingInternational Journal of Production Research, 48
Eleni Aggelogiannaki, H. Sarimveis (2008)
Design of a novel adaptive inventory control system based on the online identification of lead timeInternational Journal of Production Economics, 114
S. Disney (2008)
Supply chain aperiodicity, bullwhip and stability analysis with Jury's innersIma Journal of Management Mathematics, 19
C. Lalwani, S. Disney, D. Towill (2006)
Controllable, observable and stable state space representations of a generalized order-up-to policyInternational Journal of Production Economics, 101
Keith Tizzard (1977)
Management System DynamicsJournal of the Operational Research Society, 29
C. Riddalls, S. Bennett (2002)
The stability of supply chainsInternational Journal of Production Research, 40
J. Schwartz, D. Rivera (2010)
A process control approach to tactical inventory management in production-inventory systemsInternational Journal of Production Economics, 125
PurposeThe purpose of this paper is to examine the impact of applying two classical controller strategies, including two proportional (P) controllers with two feedback loops and one proportional–integral–derivative (PID) controller with one feedback loop, on the order and inventory performance within a production-inventory control system.Design/methodology/approachThe simulation experiments of the dynamics behaviour of the production-inventory control system are conducted using a model based on control theory techniques. The Laplace transformation of an Order–Up–To (OUT) model is obtained using a state-space approach, and then the state-space representation is used to design and simulate a controlled model. The simulations of each model with two control configurations are tested by subjecting the system to a random retail sales pattern. The performance of inventory level is quantified by using the Integral of Absolute Error (IAE), whereas the bullwhip effect is measured by using the Variance ratio (Var).FindingsThe simulation results show that one PID controller with one feedback loop outperforms two P controllers with two feedback loops at reducing the bullwhip effect and regulating the inventory level.Originality/valueThe production-inventory control system is broken down into three components, namely: the forecasting mechanism, controller strategy and production-inventory process. A state-space approach is adopted to design and simulate the different controller strategy.
Journal of Modelling in Management – Emerald Publishing
Published: Feb 12, 2018
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