Proceedings of The 10th International Conference on Research in Engineering, Science and Technology
Mobile Applications and Discrete Event Systems: Low-Cost Technology to Assist Stock Management in an Orthopedic Clinic
Daniela Trindade Batista, Thiago Augusto Santos Ferreira, Renata Duarte Mellim, Luiz Melk de Carvalho, Flávio Henrique Batista de Souza and Vladimir Alexei Rodrigues Rocha
This paper presents a case study of an inventory management in a medical orthopedic clinic in Belo Horizonte, a 3,000,000 inhabitants city from Brazil. The main objective is to help on the management of supplies to avoid a lack and/or an excess of resources, to eliminate additional costs to the company. The proposed method was based on three steps: firstly, an organizational study of the materials and people involved in the inventory process was made, based on the statistical analysis of material inputs and outputs; secondly, the requirements analysis was executed for the development of a mobile application, responsible for the consolidation and standardization of inventory data; then, a system based on Stochastic Petri Nets (SPN) was developed to simulate scenarios of material availability. As result, the statistical analysis of the scenario of a set of materials commonly used found a lack of inventory data standardization, which justifies the demand for an easy and accessible management tools. Thus, a mobile application for data collection and standardization was developed. The data consolidation is performed through cloud computing, in .csv format, making analysis available in software such as R®, Matlab® and Excel®. Such dataset was used as the reference for SPN transitions firing process. Through SPN it was simulated scenarios for material availability prediction. Several experiments were performed and they predicted the excess and lack of materials such as Xylocaine, Neocain and compresses. Savings of thousands of Brazilian reais were recorded, as well as prevention of stockouts.
Keywords: Health care; Mobile Application; Orthopedic Clinic; Stochastic Petri Nets; Stock Management.