A reference architecture for the collaborative planning modelling process in multi-tier supply chain networks: a Zachman-based approach

A prominent and contemporary challenge for supply chain (SC) managers concerns the coordination of the efforts of the nodes of the SC in order to mitigate unpredictable market behaviour and satisfy variable customer demand. A productive response to this challenge is to share pertinent market-related information, on a timely basis, in order to effectively manage the decision-making associated with the SC production and transportation planning processes. This paper analyses the most well-known reference modelling languages and frameworks in the collaborative SC field and proposes a novel reference architecture, based upon the Zachman Framework (ZF), for supporting collaborative plan- ning (CP) in multi-level, SC networks. The architecture is applied to an automotive supply chain configuration, where, under a collaborative and decentralised approach, improvements in the service levels for each node were observed. The architecture was shown to provide the base discipline for the organisation of the processes required to manage the CP activity.The authors thanks the support from the project 'Operations Design and Management in Global Supply Chains (GLOBOP)' (Ref. DPI2012-38061-C02-01), funded by the Ministry of Science and Education of Spain, for the supply chain environment research contribution.Hernández Hormazábal, JE.; Lyons, AC.; Poler, R.; Mula, J.; Goncalves, R. (2014). A reference architecture for the collaborative planning modelling process in multi-tier supply chain networks: a Zachman-based approach. Production Planning and Control. 25(13-14):1118-1134. https://doi.org/10.1080/09537287.2013.808842S111811342513-14Al-Mutawah, K., Lee, V., & Cheung, Y. (2008). A new multi-agent system framework for tacit knowledge management in manufacturing supply chains. Journal of Intelligent Manufacturing, 20(5), 593-610. doi:10.1007/s10845-008-0142-0Baïna, S., Panetto, H., & Morel, G. (2009). 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A framework for smart production-logistics systems based on CPS and industrial IoT

Industrial Internet of Things (IIoT) has received increasing attention from both academia and industry. However, several challenges including excessively long waiting time and a serious waste of energy still exist in the IIoT-based integration between production and logistics in job shops. To address these challenges, a framework depicting the mechanism and methodology of smart production-logistics systems is proposed to implement intelligent modeling of key manufacturing resources and investigate self-organizing configuration mechanisms. A data-driven model based on analytical target cascading is developed to implement the self-organizing configuration. A case study based on a Chinese engine manufacturer is presented to validate the feasibility and evaluate the performance of the proposed framework and the developed method. The results show that the manufacturing time and the energy consumption are reduced and the computing time is reasonable. This paper potentially enables manufacturers to deploy IIoT-based applications and improve the efficiency of production-logistics systems

Special Session on Industry 4.0

No abstract available

An agent-based dynamic information network for supply chain management

One of the main research issues in supply chain management is to improve the global efficiency of supply chains. However, the improvement efforts often fail because supply chains are complex, are subject to frequent changes, and collaboration and information sharing in the supply chains are often infeasible. This paper presents a practical collaboration framework for supply chain management wherein multi-agent systems form dynamic information networks and coordinate their production and order planning according to synchronized estimation of market demands. In the framework, agents employ an iterative relaxation contract net protocol to find the most desirable suppliers by using data envelopment analysis. Furthermore, the chain of buyers and suppliers, from the end markets to raw material suppliers, form dynamic information networks for synchronized planning. This paper presents an agent-based dynamic information network for supply chain management and discusses the associated pros and cons