The storage of historical information consists of the registration of large concentrations of data based on samples of information issued by a given system. Historical databases play a key role in industrial control systems that process and provide the information needed for the tasks of supervision, event records, management, and maintenance in the industrial sector. The purpose of the present research is to analyze the current state of monitoring and control systems, recognizing their advantages and disadvantages, and reaching the state of the art about the selection of a NoSQL database for the recording of time series. The development of the work focused on the comparison of columnoriented storage managers as HBase, Cassandra, and Big Table. After designing and implementing two cases of tests for comparing the behavior of both managers in the scenarios of Intensive Readings and Reading/Writing, it was concluded that both of them present excellent performance for storing historic records.

Production in large quantities of different varieties of products creates issues in finding an optimal planning solution. Adhesive tapes companies face that challenge. A multi-phased methodology is proposed to minimize production costs. In this it is considered different production variables. First phase divided a problem into subproblems to minimize computational complexity through an incidence matrix. Second phase formulated a linear programming model to determine production optimal batch sizes. Consequently, model is applied in a real company. Results showed a decrease in production costs in a range of 14%-43% for the different manufactured groups of components. In this way it is expected that more companies can apply similar models to improve their production indicators.