1. Introduction

2. Methodological procedure

3. Case study

4. Conclusion

References

The growth of the productive sector has driven the evolution of supply chains into highly complex, dynamic and concurrent systems. Consequently, emerging structures have been developed through the integration of advances in information and hardware technologies with the aim of increasing effectiveness and efficiency, as Industry 4.0. In this context, although several works use a multi-agent approach, they offer limited information on the use of formal models to specification the system. Considering the potentially serious consequences of inaccurate integration specification, the use of formal tools to design the processes for these types of system is recommended. Considering supply chains as a system of discrete events, techniques derived from Petri Nets can be used for modelling purposes. Such techniques include Colored Petri Nets, which have been effectively tested in hierarchical modelling, analysis and control of distributed systems, characteristics suitable for the specification of a supply chain management system in an industry 4.0 scenario. In this context, this article presents a systematic procedure that integrates a group of guides, methods and techniques, to develop a representation of a system with problem solving abilities, thereby facilitating the construction of a supply chain management model with a multi-agent structure, which incorporates progressive refinements and permits specification of the desired level of detail. Finally, the advantages of the proposed model are presented via its application to a product assembly case study.

Introduction

A Supply Chain Management (SCM) is a transformation and distribution system of products or services, provided to satisfy customer needs [1]. Considering market openings and the continued growth of the productive sector, this type of system has evolved from a sequential system to one with a distributed structure characterized by highly complex, dynamic and concurrent systems integrating advancements in information technology in an efficient and effective way [2]. Actually, the collaboration between suppliers, manufacturers and customers is crucial to increase the transparency of all the steps from when the order is dispatched until the end-of-life of the product [3]. This scenery promotes the adoption of industry 4.0 that use of big data, IoT and Artificial Intelligence (AI) as one . [3], [4] . In other words, The emergence of the Industry Internet of Things (IIoT) promoted new challenges in logistic domain, which might require technological changes such as: high need for transparency (supply chain visibility); integrity control (right products, at the right time, place, quantity condition and at the right cost) in the supply chains [4]. Although this scenery create opportunities to meet the needs of customers and also contribute to the development of logistics and SCM [5], according to [6] is necessary measurement the impacts of this approach.