The present work focuses on the Cell Formation Problem (CFP), which groups machines to get several benefits, including productivity improvement, reduced tooling needs, reduced setup time, and reduced manufacturing lead time. In modern manufacturing systems, equipment availability is an important requirement, as it ensures a higher possibility of utilizing productive resources, which are usually of high value. Therefore, the incorporation of reliability aspects into cell formation algorithms becomes necessary. Various researchers currently consider reliability based on individual machine failures. However, this overlooks a crucial factor, the systemic approach of clustering, in other words, the reliability of the entire production line. Since for the system to function correctly, all participating machines must be operational. So far, an approach considering the cell as a production line and taking its reliability as a whole into account has not been found. This work proposes an optimization model that incorporates machine reliability, considering the equipment as a production line. To demonstrate the effectiveness of our model, an example is given and compared with an existing model. The results show that there is a considerable cost difference between the new model and the old model. The latter will allow us to detect uncalculated costs that can be very detrimental to the correct formation of the cells.