The design of experiments (DoE) methodology is a technique that has been applied for many years in industry to improve quality. In this study, a summary of 77 cases of practical DoE application in the field of engineering is presented. All of the cases were published in important scientific journals between 2001 and 2005. The type of design that is applied, the size of the experiment, the number of factors that influence the response variable, and the sector of application of the design are analyzed. In addition, the increasing use of these designs over time is demonstrated. Copyright

Although design of experiments (DoE) is a common feature of statistics and quality literature, it is insufficiently used in industry. Surveys and numerous articles alike have verified that a gap exists between theoretical development and its effective application in industry. Therefore, we have developed a complete, friendly and easy-to use methodology, from an engineering point of view, to ease the implementation of DoE in companies. Our approach presents a framework for the experimentation process that follows the traditional DMAIC steps of 'Six Sigma' as a generic problem solving methodology. We aim to present a complete overview of the experimentation process useful for those engineers, statisticians and scientists who are not experts in DoE. IMPLEMENTATION OF DoE PROJECTS IN INDUSTRY 479 methodology. Furthermore, 76% of the respondents believed that a methodology is truly needed and that the absence of a clear methodology was one of the main barriers in the application of DoE. Similar results were obtained in other European Regions [6]. In Tay and Butler's [7] research of the existing methodologies for experimental design, they reached the conclusion that two types of DoE methodologies are in use today, namely: • Classical techniques: Developed in the U.K. and U.S. in the 1920s, with the introduction of full factorial designs and fractional designs some years later. In the 1950s, Box-Wilson developed what was later called RSM. Finally, optimal design has been under development since the 1960s. Since then, many have contributed to the development and expansion of this technique. The research of Box et al. [8], Myers and Montgomery [9] and Atkinson and Donev [10] is considered to be fundamental in their fields, respectively. • Taguchi methods: Developed by Genechi Taguchi in Japan in the 1950s, promoting statistical techniques for quality from an engineering perspective. The original work of Taguchi is documented in his own two-volume book [11]. Other books that present the method include Taguchi et al. [12] and Roy [13].After a thorough analysis of their characteristics, Tay and Butler [7] concluded that there was a need to shape an experimental design methodology to develop the information necessary for good planning, design and analysis. Since the majority of those who apply DoE are not statisticians, it is necessary to develop simple methodologies to solve the problems faced in the industry. The Tanco et al. [5] survey echoes this need, showing that 76% of the respondents believed that a methodology is truly needed.Starting from these premises, we developed a complete methodology to make the implementation of DoE in companies easier. We aim to present to industries a simple methodology from an engineering point of view, without ignoring either the statistical or the overall complexity of this task. This methodology will be useful as a complete overview for those who are not experts in DoE and need to carry out an experimentation process. Moreover, it will also be useful for trainers and consultants when it...

An extensive literature review was carried out to detect why design of experiments (DoE) is not widely used among engineers in Europe. Once 16 main barriers were identified, a survey was carried out to obtain first-hand information about the significance of each. We obtained 101 responses from academics, consultants and practitioners interested in DoE. A statistical analysis of the survey is introduced, including: (a) a ranking of the barriers, (b) grouping of barriers using factorial analysis, (c) differences between characteristics of respondents. This exploratory analysis showed that the main barriers that hinder the widespread use of DoE are low managerial commitment and engineers' general weakness in statistics. Once the barriers were classified, the most important resultant group was that related to business barriers.barriers, design of experiments, engineers, industry, survey,

A survey was carried out to characterize experimentation in three different European regions: the Baden-Wurttemberg region, The Basque Country and the rest of Spain. Results of the survey show that even though experimentation is a frequent activity, almost 95% of companies conduct experiments; the strategies used to carry them out are primitive. The one-factor-at-a-time strategy is used by 75% of companies far more than the 23%, which apply design of experiments (DoE). Results show that this may be due to the current lack of knowledge of DoE in these regions, where only 33% are familiar with the technique. Finally, the rate of applications of DoE among Six Sigma users is 40%, twice that of non-users, which stands at 19%.

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