Aplicação de um framework baseado nos conceitos de Workload Control para identificação dos problemas relacionados à confiabilidade de entrega em uma empresa do setor de manutenção aeronáutica

Abstract

The improvement in the delivery reliability performance in Make-To-Order (MTO) companies has been becoming an important competitive criterion in the recent market context. Thus, it gets clear the importance of researches able to present tools to help the identification of enhancement opportunities in the matter of delivery reliability. The identification of opportunities requires a structure of diagnosis of the recent situation. However, depending on the performance problem to be diagnosed, a theoretical understructure based on specific scientific knowledge is needed. This work presents the framework developed by Soepenberg et al. (2012c) based on Workload Control (WLC) concepts. Such framework is composed by a structure for the diagnosis process of the reliability performance that allows browsing from the obtained performance to the subjacent causes related to Production Planning and Control (PPC). The aim of the present work is to present the WLC as well as the diagnostic tools with the purpose of elucidating their applicability through the framework developed by Soepenberg et al. (2012c) in a real context through a case study. The results of the case study indicated that the framework is a key instrument for diagnosis due to the accuracy by which it defines the causes of delays of the orders related to the PPC decisions. The application of the framework indicated that the lack of spare parts is the most impacting factor on delays, however this is not a cause only related to the company PPC decisions, but to external factors that are out of the company’s reach. Another result obtained is the verification that most of the orders are concluded before the date set. This is due to the lack of accuracy in the definition of the delivery dates and to the estimative mistakes of the capacity to be used for the maintenance of each part number, whose responsibilities rely on PPC.