Measuring and eliminating the bullwhip in closed loop supply chains using control theory and Internet of Things

Closed-loop supply chains are complex systems as they involve the seamless backward and forward flow of products and information. With the advent of e-commerce and online shopping, there has been a growing interest in product returns and the associated impact on inventory variance and the bullwhip effect. In this paper, a novel four-echelon closed-loop supply chain model is presented, where base-stock replenishment policies are modelled by means of a proportional controller. A stochastic state-space model is implemented, initially to capture the supply chain dynamics while the model is analysed under stationarity conditions with the aid of a covariance matrix. This allows the bullwhip effect to be expressed as a function of replenishment policies and product return rates. Next, an optimisation method is introduced to study the impact of the Internet of Things on inventory variance and the bullwhip effect. The results show that the Internet of Things can reduce costs associated with inventory fluctuations and eliminate the bullwhip effect in closed-loop supply chains.

[1]  Hau L. Lee,et al.  The bullwhip effect in supply chains , 2015, IEEE Engineering Management Review.

[2]  Philip Robinson,et al.  The Bullwhip Effect and VM Sprawl in the Cloud Supply Chain , 2010, ServiceWave Workshops.

[3]  Stefan Minner,et al.  Inventory Management in Closed Loop Supply Chains , 2004 .

[4]  Eleonora Bottani,et al.  Reverse Logistics: a stochastic EOQ-based inventory control model for mixed manufacturing/remanufacturing systems with return policies , 2012 .

[5]  Alexandre Dolgui,et al.  Does the ripple effect influence the bullwhip effect? An integrated analysis of structural and operational dynamics in the supply chain† , 2019, Int. J. Prod. Res..

[6]  G. Marthandan,et al.  Supplier Development Activities and Buying Firm’s Performance: An Empirical Investigation of Iranian SMEs , 2019 .

[7]  Hai Feng Guo,et al.  LMI-Based H ∞ Control for Dual-Channel E-Commerce CLSC Networks and its Bullwhip Effect , 2015 .

[8]  Gu Hai-feng.  H∞ Control of a State Matrix Model of Multiechelon Supply Chains System and Its Bullwhip Effect , 2007, 2007 International Conference on Management Science and Engineering.

[9]  Antonio Carlos Braz,et al.  The bullwhip effect in closed-loop supply chains: A systematic literature review , 2018, Journal of Cleaner Production.

[10]  Christopher S. Tang,et al.  Handbook of Information Exchange in Supply Chain Management , 2017 .

[11]  J. Forrester.  Industrial Dynamics , 1997 .

[12]  Suhaiza Hanim Binti Dato Mohamad Zailani,et al.  Product return management: Linking product returns, closed-loop supply chain activities and the effectiveness of the reverse supply chains , 2017 .

[13]  Wuxue Jiang,et al.  An Intelligent Supply Chain Information Collaboration Model Based on Internet of Things and Big Data , 2019, IEEE Access.

[14]  Stephen M. Disney,et al.  Measuring and avoiding the bullwhip effect: A control theoretic approach , 2003, Eur. J. Oper. Res..

[15]  Angappa Gunasekaran,et al.  Vision, applications and future challenges of Internet of Things: A bibliometric study of the recent literature , 2016, Ind. Manag. Data Syst..

[16]  Panos M. Pardalos,et al.  An Experimental Research on Closed Loop Supply Chain Management with Internet of Things , 2016 .

[17]  Mohamed Mohamed Naim,et al.  Why do nonlinearities matter? The repercussions of linear assumptions on the dynamic behaviour of assemble-to-order systems , 2019, Int. J. Prod. Res..

[18]  Przemysław Ignaciuk.  Networked base-stock policy for continuous-review goods distribution systems with uncertain demand , 2017, 2017 21st International Conference on System Theory, Control and Computing (ICSTCC).

[19]  Wenyan Zhou,et al.  The impact of the package opening process on product returns , 2018 .

[20]  Haifeng Guo,et al.  Model predictive control algorithm of closed-loop supply chain networks dynamic system and its bullwhip effect , 2017, 2017 36th Chinese Control Conference (CCC).

[21]  Teresa Olivares,et al.  An end-to-end Internet of Things solution for Reverse Supply Chain Management in Industry 4.0 , 2019, Comput. Ind..

[22]  Benjamin T. Hazen,et al.  Remanufacturing for the Circular Economy: An Examination of Consumer Switching Behavior , 2015 .

[23]  Zhou Zhigang,et al.  Applying RFID to reduce bullwhip effect in a FMCG supply chain , 2011, 2011 International Conference on E-Business and E-Government (ICEE).

[24]  Manfredi Bruccoleri,et al.  Impact of reverse logistics on supply chain performance , 2013 .

[25]  J. Framiñan,et al.  Quantifying the Bullwhip Effect in closed-loop supply chains: The interplay of information transparencies, return rates, and lead times , 2020 .

[26]  J. Framiñan,et al.  Closed-loop supply chains: What reverse logistics factors influence performance? , 2016 .

[27]  G. Hammes,et al.  Reverse Logistics Costs: Case Study in a Packaging Industry , 2018, Industrial Engineering and Operations Management I.

[28]  M. Pishvaee,et al.  Competitive closed-loop supply chain network design under uncertainty , 2015 .

[29]  Sampath Rajagopalan,et al.  Information Leakage in Supply Chains , 2017 .

[30]  Erwin A. van der Laan,et al.  Production , Manufacturing and Logistics Inventory control with product returns : The impact of imperfect information , 2009 .

[31]  Ata Allah Taleizadeh,et al.  A robust optimization model for coordinating pharmaceutical reverse supply chains under return strategies , 2020, Ann. Oper. Res..

[32]  S. Lozano,et al.  An analysis of the main factors affecting bullwhip in reverse supply chains , 2012 .

[33]  Philip M. Kaminsky,et al.  Designing and managing the supply chain : concepts, strategies, and case studies , 2007 .

[34]  Mohamed Abdel-Basset,et al.  Internet of Things (IoT) and its impact on supply chain: A framework for building smart, secure and efficient systems , 2018, Future Gener. Comput. Syst..

[35]  Pietro De Giovanni,et al.  Closed-loop supply chain coordination through incentives with asymmetric information , 2017, Ann. Oper. Res..

[36]  Yongfeng Zhang,et al.  Bullwhip effect mitigation of green supply chain optimization in electronics industry , 2018 .

[37]  Hamid Khaloozadeh,et al.  Nonlinear modeling and performance analysis of a closed-loop supply chain in the presence of stochastic noise , 2019, Mathematical and Computer Modelling of Dynamical Systems.

[38]  Lizhen Huang,et al.  Supply Chain Dynamics Under the Sustainable Development , 2008, 2008 4th International Conference on Wireless Communications, Networking and Mobile Computing.

[39]  Alexandre Dolgui,et al.  ON APPLICABILITY OF OPTIMAL CONTROL THEORY TO ADAPTIVE SUPPLY CHAIN PLANNING AND SCHEDULING , 2011 .

[40]  Stephen M. Disney,et al.  The impact of information sharing, random yield, correlation, and lead times in closed loop supply chains , 2015, Eur. J. Oper. Res..

[41]  J. Stock,et al.  Exploring the processing of product returns from a complex adaptive system perspective , 2019, International Journal of Logistics Management.

[42]  El-Houssaine Aghezzaf,et al.  A Distributed Model Predictive Control Strategy for the Bullwhip Reducing Inventory Management Policy , 2019, IEEE Transactions on Industrial Informatics.

[43]  Vipul Jain,et al.  Closed-loop supply chain network design and modelling under risks and demand uncertainty: an integrated robust optimization approach , 2020, Ann. Oper. Res..

[44]  R. K. Pati,et al.  Quantifying bullwhip effect in a closed loop supply chain , 2010 .

[45]  Kannan Govindan,et al.  A review of reverse logistics and closed-loop supply chains: a Journal of Cleaner Production focus , 2017 .

[46]  Hong Xue,et al.  Research progress on control theory application to supply chain management , 2011, Proceedings of the 30th Chinese Control Conference.

[47]  Suresh P. Sethi,et al.  A survey on control theory applications to operational systems, supply chain management, and Industry 4.0 , 2018, Annu. Rev. Control..

[48]  Cong Jin,et al.  Smart Reverse Supply Chain: An Application of IoT to Green Manufacturing , 2011 .

[49]  Jing Chen,et al.  The impact of customer returns on supply chain decisions under various channel interactions , 2013, Annals of Operations Research.

[50]  Panos M. Pardalos,et al.  Optimal production planning in a hybrid manufacturing and recovering system based on the internet of things with closed loop supply chains , 2016, Oper. Res..

[51]  Kaijun Leng,et al.  Research on closed-loop supply chain coordination control model based on difference equation load model , 2019, Journal of Difference Equations and Applications.

[52]  Simone Zanoni,et al.  Cost performance and bullwhip effect in a hybrid manufacturing and remanufacturing system with different control policies , 2006 .

[53]  Dean C. Chatfield,et al.  Returns and the bullwhip effect , 2013 .

[54]  Bo Sun,et al.  H-infinity Control for Dual-Channel Closed-Loop Supply Chain Model with B2B E-market and Reverse Logistics , 2010, 2010 Third International Conference on Intelligent Networks and Intelligent Systems.

[55]  Ramesh Anbanandam,et al.  A robust hybrid multi-criteria decision making methodology for contractor evaluation and selection in third-party reverse logistics , 2014, Expert Syst. Appl..

[56]  Boris V. Sokolov,et al.  Applicability of optimal control theory to adaptive supply chain planning and scheduling , 2012, Annu. Rev. Control..

[57]  Ioannis Mallidis,et al.  Development of a single period inventory planning model for perishable product redistribution , 2018, Ann. Oper. Res..

[58]  Stephen M. Disney,et al.  Bullwhip and inventory variance in a closed loop supply chain , 2006, OR Spectr..

[59]  Vladimír Strejc,et al.  State Space Theory of Discrete Linear Control , 1982, IEEE Transactions on Systems, Man, and Cybernetics.

[60]  I. Baihaqi,et al.  The impact of a substitution policy on the bullwhip effect in a closed loop supply chain with remanufacturing , 2020, Journal of Remanufacturing.

[61]  Bernardo Almada-Lobo,et al.  A hybrid VNS approach for the short-term production planning and scheduling: A case study in the pulp and paper industry , 2013, Comput. Oper. Res..

[62]  O. Tang,et al.  The impact of information transparency on the dynamic behaviour of a hybrid manufacturing/remanufacturing system , 2004 .

[63]  R. Hartley.  Stochastic Modelling and Control , 1985 .

[64]  Li Wei,et al.  Modeling and Bullwhip Effects Control of Internet+ Supply Chain , 2019, 2019 Chinese Control And Decision Conference (CCDC).

[65]  Michael E. Ketzenberg,et al.  The value of information in a capacitated closed loop supply chain , 2009, Eur. J. Oper. Res..

[66]  C. E. Riddalls,et al.  The optimal control of batched production and its effect on demand amplification , 2001 .

[67]  Ali Gharbi,et al.  Production planning of an unreliable hybrid manufacturing-remanufacturing system under uncertainties and supply constraints , 2019, Comput. Ind. Eng..

[68]  Ozalp Vayvay,et al.  The impact of remanufacturing on total inventory cost and order variance , 2014 .

[69]  Zhou Hui,et al.  Simulation of remanufacturing in reverse supply chain based on system dynamics , 2008, 2008 International Conference on Service Systems and Service Management.

[70]  J. Framiñan,et al.  On the dynamics of closed-loop supply chains under remanufacturing lead time variability , 2020, Omega.

[71]  Mohamed Mohamed Naim,et al.  The impact of product returns and remanufacturing uncertainties on the dynamic performance of a multi-echelon closed-loop supply chain , 2017 .