This is the first version of the article published by Taylor and Francis in Quality Engineering on December 2018, available at https://doi.org/10.1080/08982112.2018.1526302 Saving runs in fractional factorial designs Pere Grima, Lourdes Rodero, Xavier Tort-Martorell Department of Statistics and Operational Research Universitat Politècnica de Catalunya - BarcelonaTech, Spain ABSTRACT When it is known a priori that some contrasts are negligible in a factorial design, their expressions can be used to deduce the missing results. In this article we propose a method for using this procedure when, as in the case of fractional designs, it is not known which contrasts will be null. The method is based on first establishing an interval of possible values corresponding to each of the missing results, then identifying which contrasts are always null independently of the value of said results. KEYWORDS: Factorial designs, missing values, negligible interactions, saving runs, lean designs. 1. Introduction In industrial contexts, conducting experiments is usually costly and the resources for carrying out experimental designs are often scarce. The seed idea for this paper came about when two of the authors were giving training and advice on DEO to a company from the aeronautic sector. In it, as part of the optimization of a welding process of a complicated component of a turbine it was decided to conduct some experiments. Runs were expensive, the material was an expensive titanium alloy and slow, something that interfered the normal production process (some experiences of our work with this company were published in Lluís Marco-Almagro et al., 2014). The first step in a sequential experimentation process was to conduct a two level fractional factorial that unfortunately could not be completed. The last two runs could not be executed. Among other ways of analyzing the data, we asked the technicians the range of values