System Dynamics Modeling in Additive Manufacturing Supply Chain Management

Jairo Nuñez Rodriguez,Hugo Hernando Andrade Sosa,Angel Ortiz,Sylvia Maria Villarreal Archila

doi:10.3390/pr9060982

Abstract

A system dynamics model was developed with the primary purpose of visualizing the behavior of a supply chain (SC) when it adopts a disruptive technology such as additive manufacturing (AM). The model proposed a dynamic hypothesis that defines the following issue: what is the impact of the AM characteristics and processes in the SC? The model was represented through a causal diagram in thirteen variables related to the SC, organized in two feedback cycles and a data flow diagram, based mainly on the three-essential links of the SC and the order display traceability: supplier–focal manufacturer–distribution Network. Once proposed, the model was validated through the evaluation of extreme conditions and sensitivity analysis. As a result, the dynamic behavior of the variables that condition the chain management was analyzed, evidencing reduction times in production, especially in products that require greater complexity and detail, as well as reductions in inventories and the amount of raw material due to production and storing practices from AM. This model is the starting point for alternative supply chain scenarios through structural operating policies and operating policies in terms of process management.

Highlights

The application of modeling with system dynamics (SD) in supply chain management (SCM) has its roots in Forrester’s Industrial Dynamics, through the definition of a model structured in six flow systems that interact among them transmission of the information, materials, orders, money, labor, and capital [1]
The model will be an experimental laboratory to study what could happen with the behavior of the network structure, generating new questions such as: What would happen if there were more actors in the supply chain? What would happen if additive production was centralized or distributed in different regions? What would happen with inventory levels and transportation times? What would happen if the structures of the chains were changed?
This paper reaffirms the importance of system dynamics to represent the behavior of the supply chain, visualizing the links that integrate it

Summary

Introduction

The application of modeling with system dynamics (SD) in supply chain management (SCM) has its roots in Forrester’s Industrial Dynamics, through the definition of a model structured in six flow systems that interact among them transmission of the information, materials, orders, money, labor, and capital [1]. Forrester developed one of the first related models, in which he considered the chain as part of an industrial system in terms of policy design [2]. Current trends and the transition to industry 4.0 and technological impact issues require support from system dynamics to respond to the behavior of variables influenced by breakthroughs, such as big data, cybersecurity, augmented reality, cloud computing, the Internet of Things (IoT), and additive manufacturing in SC management. Regardless of the industry where they are analyzed, the supply chains are still considered complex and dynamic systems that involve different participants (stakeholders) Understanding them as value chain networks, where the resources and activities necessary to create and deliver services/products are involved to satisfy the customer’s needs [4].

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Discussion

Conclusion