Proceedings of The 3rd International Conference on Research in Science, Engineering and Technology
Stochastic Timed Petri Nets Applied to The Purchasing Process: A Case Study in A Large Cosmetics Retailer
Pedro Henrique O. Tocafundo, Gabriela Carline T. Ferreira, Raphael Augusto L. Cunha, Renata Duarte Mellim, Vladimir Alexei Rodrigues Rocha, Luiz Melk de Carvalho, Flávio Henrique Batista de Souza
The purchase process of a large cosmetic and perfumery company is one of the pillars of its existence. When this process is time consuming or has a high concentration of responsibilities on a single manager, the productivity curve of the process can be affected. This fact is aggravated by the new perspectives of work and production due to COVID-19, where a high rate of unemployment and concentration of activities has permeated companies. This work demonstrates the application of the concepts of modelling and simulation, with the application of Stochastic Timed Petri Nets (STPN) as a proposal for efficient management. The first stage of the research consisted of an evaluation of the process in two aspects: the sequence of activities and time and money resources involved. The purchasing processes of the company were evaluated for four months at this stage. The second stage demonstrates the application of STPNs to manage the evaluated process. As a result, it was found that the financial values that guide service orders are between R$ 5.00 to R$ 80,000.00 Brazilian reais (totalling approximately R$ 800,000.00 during the analysis period), with service orders that accumulated approximately 120 days of delay for their resolution. In addition, a complete flowchart of the purchase process was developed, which enabled the use of STPNs. A simulator was created with the ability to identify bottlenecks (demonstrating the sectors and managers that need readjustments) and demonstrated proposals with 20% increase in the operational efficiency.
Keywords: Purchasing Process, Stochastic Timed Petri Nets, Retail, Modelling and Simulation, Large Companies.