Considering the increasingly stringent requirements that the market imposes on businesses and the ability to adapt in short times required for companies to remain competitive, it is necessary to consider approaches that simultaneously monitor key processes and seek optimization. Under this scenario, the objective of this study is to propose a model integrating statistical process control and experimentation for small enterprises. Therefore, we carry out a literature review to identify cases of applications of these tools in an integrated manner to provide the basis for constructing a framework. Sequentially, the proposed framework is applied for verification and validation, through a case study in a small company responsible for manufacturing of packaging in polypropylene fabric. In this context, we employ a factorial split-plot 2³ x 2² design with repetition and replication. For the analysis of the experiment, we use Minitab 17, which generates main effects and interaction plots. A proposal for monitoring via control charts is suggested to maintain the output variables in statistical control. Finally, the results show that the combined use of design of experiments and statistical process control, aligned with university-industry partnership, can optimize the quality improvement process in small businesses.
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