Multivariate Statistical Process Control (MSPC) seeks to monitor several quality characteristics simultaneously. However, it has limitations derived from its inability to identify the source of special variation in the process. In this research, a proposed model that does not have this limitation is presented. In this paper, data from two scenarios were used: (A) data created by simulation and (B) random variable data obtained from the analysed product, which in this case corresponds to cheese production slicing process in the dairy industry. The model includes a dimensional reduction procedure based on the centrality and data dispersion. The goal is to recognise a multivariate pattern from the conjunction of univariate variables with variation patterns so that the model indicates the univariate patterns from the multivariate pattern. The model consists of two stages. The first stage is concerned with the identification process and uses Moving Windows (MWs) for data segmentation and pattern analysis. The second stage uses Bayesian Inference techniques such as conditional probabilities and Bayesian Networks. By using these techniques, the univariate variable that contributed to the pattern found in the multivariate variable is obtained. Furthermore, the model evaluates the probability of the patterns of the individual variables generating a specific pattern in the multivariate variable. This probability is interpreted as a signal of the performance of the process that allows to identify in the process a multivariate out-of-control state and the univariate variable that causes the failure. The efficiency results of the proposed model compared favourably with respect to the results obtained using the Hotelling’s T2 chart, which validates our model.

Within the automotive industry one of the most used materials for user comfort is animal skin, this material is used to coat pieces that will have contact with the consumer. One of the most important problems that arise with the handling of the skin in operations of coating and assembly within plants of the automotive sector is the lack of resistance. A treatment that must be applied to the skin to improve its conditions of resistance to mechanical tension, is in function of two factors: percentage of moisture in the skin and amount of surfactant applied. In the present investigation, optimal operating conditions are established for the handling of the skin used in processes of the automotive sector based on a 3k factorial experimental design. The application case was carried out in a company dedicated to manufacture armrests for high-end cars. The results of the investigation show an improvement of 97% in operations where the resistance of the skin is required to meet the quality standards established in the automotive industry.

Nowadays, companies face scale or production volume margins accelerated to respond and meet the needs of international markets, logistics and supply chain is then a key strategy to add value and competitive advantage. Through an investigation of observation and data collection, it was determined that there is no capacity for response and control before the increase in production, it is then that the objective of this work is to establish an order in the internal flow of materials, by medium of the implementation of an internal logistics process in a company that produces aluminum parts. For which a model was created that considered variables such as: the determination of spaces, control of documented information, creation of traceability and training record formats, which produced the following results: improvement in internal flows by 80%, a correct traceability in the handling of the materials that reduced the times by 50%, in addition to the incorporation of programs of administrative platforms. Therefore, the appropriate elements that make up the adoption of the strategy and its measurement in performance indices were determined.

Social responsibility is a duty of organizations, in the same way, Universities have participated in the flow of Social Responsibility, as part of their very essence. González (2014) the University Social Responsibility (RSU) guarantees the quality of higher education as a whole. This research analyzes the Polytechnic University of Pénjamo (UPPE) as an educational institution, to visualize the options to implement a model of University Social Responsibility. In particular, the Student Decalogue is presented, which is one of the results of the research carried out around the RSU. he research aims to determine the options to implement, within the Polytechnic University of Pénjamo, a model of University Social Responsibility, which was achieved through the results of the application of the instruments proposed by Vallaeys in the First Steps Manual for the RSU. The results contribute to learning through case studies to show that IES perform various actions from within to develop in students the sensitivity, awareness and co-responsibility in solving the problems of the Environment.

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