Técnicas estadísticas en Manufacturing Intelligence

Abstract

"Manufacturing intelligence" is a term linked to a research area focused on taking advantage of improvement in the production process of manufacturing industries due to ICT development. The main goal is to take advantage of the value of the data obtained from various sources, specially ICT, in order to transform this data to useful information that generate practical knowledge to improve operational systems as well as management. In an industrial context, it is common to optimize production processes from previous experiments. However, it is needed to invest a lot of time and resources. The point of view selected for this academic task is using simulation techniques not only to reduce costs and time to process optimization but taking advantage of the opportunities offered by the simulation in management of untreatable problems via ‘Integer linear programming'. This is the main reason to bet for simulation as a support tool for improve scheduling in a Job Shop environment. This academic task has had two different phases. First, manufacturing industries identification and definition. How? Analyzing the different components of a manufacturing system attending to process, structure, sequencing rules and implementation proposals.Second, a 'R-application' has been developed for an industry of manufacturing corrugated cardboard boxes. The application is useful for the description of the industry situation and to perform simulations that help to identify options for the process improvement. In this research, it has been very important to find a link or interaction between input variables: planned production schedules, manufacturing times, number of colors, types of processes used, equipment for manufacturing. The commitment was to find the best operational sequence in order to reduce manufacturing timing, operational 5 timing (Makespan) and increasing the period of time while using equipments, cutting down non-profitable working time (idle) in Job Shop contexts.