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This paper presents and discusses a research applied to an industrial group in Altamira, Tamaulipas, Mexico, and the inception of a labor productivity improvement program for the construction and maintenance of industrial group Águila. This industrial group offers its services to industrial plants such as Mexichem, Basf, Dupont, M.G., INSA, NHumo, Temex and Indelpro, among others. The basis of this study is founded on the principles stated by lean manufacturing and work sampling. The formulation and a methodology is develop towards the improvement productivity for the construction and maintenance of industrial projects, with which it is intended, optimize employees’ performance by increasing this enterprise’s competitiveness. The results obtained at the start of this project of research show the viability of the proposed methodology. The work sampling is an indirect measuring method, which by means of instantaneous observations; this allows to determine the active and inactive amount of time within a productive process. This methodology is applied considering that this enterprise carries out different kind of works every day. 336 instantaneous and random observations have been calculated within a group of workers. The sizes of the studied population include a group of 686 workers on a weekly average basis, which has provided a statistical confidence level of 95% with an error of 5%. The construction and maintenance industry is one of the areas that present a lower degree of develop in most Latin-American countries, which becomes an activity characterized by great deficiencies and lack of effectiveness, all of this caused mainly for the lack of education in workers and bad knowledge management The sector of construction shows particular characteristics that explain the development degree it presents such as: influence of weather conditions, working under pressure, project fragmentation, small amount of training, lack of research and development, among others. However, the need for improvement due to constant change of scenarios where the activity develops has been detected.