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The purpose of this paper is to address misconceptions about the design of experiments (DoE) usefulness, avoid bad practices and foster processes’ efficiency and products’ quality in a timely and cost-effective manner with this tool.

To revisit and discuss the hindrances to DoE usage as well as bad practices in using this tool supported on the selective literature from Web of Science and Scopus indexed journals.

A set of recommendations and guidelines to mitigate DoE hindrances and avoid common errors or wrong decisions at the planning, running and data analysis phases of DoE are provided.

Errors or wrong decisions in planning, running and analyzing data from statistically designed experiments are always possible so the expected results from DoE usage are not always 100 percent guaranteed.

Novice and intermediate DoE users have another perspective for developing and improving their “test and learn” capability and be successful with DoE. To appropriately plan and run statistically designed experiments not only save the user of DoE from incorrect decisions and depreciation of their technical competencies as they can optimize processes’ efficiency and products’ quality (reliability, durability, performance, robustness, etc.) in a structured, faster and cheaper way at the design and manufacturing stages.

DoE usefulness will be increasingly recognized in industry and academy and, as consequence, better products can be made available for consumers, business performance can improve, and the link between industry and academy can be strengthened.

A supplemental perspective on how to succeed with DoE and foster its usage among managers, engineers and other technical staff is presented.

The purpose of this study is to develop a practical method for training students how to conduct statistical analysis and do a course project in design of experiments (DOEs) course through the Web-based virtual catapult simulation.

A step-by-step sequential DOE process for investigating the effects of controllable factors on quality characteristic responses was presented as a guideline for conducting a DOE course project. Each team was assigned to create an innovative teaching material and work on the term report by following the recommended guidelines for designing experiments through the Web-based virtual catapult simulation. Hypothesis was defined to test whether doing a course project based on this approach would impact students’ learning outcome.

The Web-based virtual material was an alternative technique for interactive teaching that could improve students’ understanding and achievement in DOE course projects. There was a significant difference in student learning and understanding before and after doing on the course project through the Web-based virtual catapult simulation. The students had improved communication and teamwork skills after following the recommended procedure for practicing DOEs.

Most students could effectively conduct designing experiments, carry out designed experiments, analyze data and gain valuable teamwork experience. After learning the DOE approach based on the catapult simulation, they enjoyed working on their course projects deploying to the innovative toys and other real-life situations with real measurements.

The use of Web-based virtual material, including catapult simulation, was an alternative technique for interactive DOE teaching to improve the students’ understanding and achievement in DOE course projects.

The purpose of this paper is to present some fundamental and critical differences between the two methods of experimental design (i.e. Taguchi and classical design of experiments (DOE)). It also aims to present an application of Taguchi method of experimental design for the development of an optical fiber sensor in a cost effective and timely manner.

The first part of the paper shows the differences between classical DOE and Taguchi methods from a practitioner's perspective. The second part of the paper illustrates a simple framework which provides guidance in the selection of a suitable DOE strategy. The last part is focused on a simple case study demonstrating the power of Taguchi methods of experimental design.

One of the key questions from many quality and production related personnel in organisations are “when to use Taguchi and Classical DOE?”. The purpose of this paper is to make an attempt to address the above question from a practitioner's perspective.

The case study is based on Taguchi method of experimental design. It would be great to see the results of the study if classical DOE is performed to this study.

The paper will be an excellent resource for both research and industrial fraternities who are involved in DOE projects.

Case study and frame work.

The purpose of the article is to present the results of a critical literature review (CLR) on Design of experiments (DoE) in the service industry.

A critical review of existing literature review across various databases including Scopus, Web of Science, Google Scholar and Emerald Insight were searched for the identification of relevant papers. The authors searched relevant journal articles for a time period of 25 years (1994–2019).

A total of 29 industry case studies of DoE applications were identified spanning healthcare, retail, logistics, education, marketing, after sales and catering business. The industrial experimentation strategies adopted by the case study organisations were screening, factorial designs, Taguchi, response surface method and split-plot. It was apparent that there are only a handful number of papers showing the applications of DoE across the service sector and this motivates for pursuing further research into this topic by the authors.

The findings of the study can be very useful for middle and senior managers to understand the benefits of implementing this powerful technique for increased understanding of service processes, as well as for optimising service performance. Moreover, the paper presents some of the fundamental challenges, as well as skills needed for the successful application of DoE.

To the best of our knowledge, this is the first CLR on DoE and its applications in the service sector. The findings of the study can be beneficial to both academic and industrial communities to understand some of the challenges and fundamental gaps which need to be tackled in the future.

The purpose of this study is to critically evaluate the current status of Design of experiments (DoE) in the service industry or non-manufacturing processes in the manufacturing sector. This involves the identification of critical success factors and challenges in the use of DoE in the context of the service industry as well as the key skills needed for its successful applications.

In order to identify the critical success factors and challenges, an online survey instrument was developed and distributed across Six Sigma Black Belts (SSBB), Six Sigma Master Black Belts (SSMBB), process improvement champions, continuous improvement professionals, DoE experts and specialists as well as academics who are involved in DoE research and applications.

A total of 109 participants from over 20 countries responded to the study. One of the first findings of the study is that over 40% of the process improvement professionals in the service sector do not have any hands-on experience with the application of DoE. Further, this study highlights the following critical factors for successful DoE applications: dedicating adequate resources in terms of time, budget and people for the experiment; getting a clear understanding of the problem at hand; securing a reliable and validated measurement system for measuring the response or quality characteristics of interest; and identifying input independent variables, which influence the quality characteristics during the brainstorming stage. Some respondents also mention the importance of having training or education in DoE as a critical success factor. At the same time, the lack of adequate planning to experimentation, mathematical knowledge and statistical reasoning remains as challenge to be solved.

As data were collected at an individual level, inter-reliability, which measures the consistency of judgements on a particular survey item, could not be gauged. Moreover, due to low sample size across some continents, an intercontinental comparative study on the extent of the application of DoE across various continents could not be performed.

To the best of the authors’ knowledge, this is the first global survey carried out to understand the status of DoE in the service industry. The results of the global study can be used to encourage quality, continuous improvement and process improvement professionals in the service sector to drive wider acceptance of one of the most powerful tools in the Six Sigma toolkit for problem-solving scenarios. Moreover, senior managers in the service industry can take away some of the key benefits, challenges and success factors in the implementation of DoE.

This article presents a novel case study that analyzes the applicability of DoE in the curling sport in order to improve their own performance and the performance of its athletes. Specifically, this study analyzes the most important factors to increase accuracy and precision in the draw game with curlers' opinions. It was decided to use the “Last Stone Draw (LSD)’ as an appropriate play situation.

Specifically, this study analyzes most important factors to increase accuracy and precision in the draw game with curlers opinions from the German Curling association. Three research techniques were used in this study: case study, interviews and a well-designed experiment. The analysis through the use of DoE includes a measurement system analysis, an initial variance test between two players, a screening and a characterization experiment.

The results obtained from DoE suggest that the factors routine, stress, release, balance, and the previous play situation have a substantial impact on the score of the player's draw game. However, no factor has a statistically significant impact on the average distance to the center of the target. Moreover, the DoE analysis also concludes that the accuracy and precision of the player's performance is not affected equally by all analyzed factors, but they turn into highly significant when examining their relationship to the other factors.

The findings of this study can be beneficial to other sports events in improving the performance. Moreover, DoE has proved to be an invaluable tool for many people in the German Curling Association in understanding the factors which influence the curlers performance and also factors which do not affect the curlers performance.

This research attempts to contribute to the existing sports management literature by identifying a way in which DoE can be an effective tool in non-manufacturing settings for identification of most important factors which influence the curling performance.

The purpose of this paper is to focus the application of design of experiments (DOE) using industrial equipments, reinforcing idea that non‐statistical aspects in planning and conducting experiments are so important as formal design and analysis.

Two case studies are presented to illustrate typical industrial applications and difficulties. Supported on these case studies and literature, this paper presents guidelines to planning, conducting and analysis involving technical and organizational aspects.

Solving problems in industry, including in companies recognized as competent in the respective industrial sector, is not just a question of applying the right technique. Ceramic industry case study illustrates how important are non‐statistical issues in DOE application. Paint industry case study illustrates the strong relationship of the results with incorporating presented guidelines into practice. Moreover, both case studies consolidating a fundamental advantage of DOE: experimentation provides more knowledge about products, processes and technologies, even in unsuccessful case studies.

Unsuccessful cases studies are very useful for identifying pitfalls and others limitations. This paper highlight difficulties aroused from non‐statistical aspects, although it is possible to find unsuccessful case studies due to statistical issues also. So, papers illustrating inadequate application of statistical techniques are welcome.

Successful DOE implementation depends on statistical and non‐statistical aspects. Although none of them shall be neglected, technical skills and technological knowledge about processes and products, management understanding of potential possibilities of statistical techniques and statistical fundamentals and knowledge about techniques of DOE must be ensuring to successful case studies in industrial setting.

This paper highlights non‐statistical aspects instead of the statistical ones. Tob overcome difficulties structured guidelines were designed to support DOE application in industrial setting.

The purpose of this article is to provide an extensive review of the barriers faced by engineers when applying design of experiments (DoE). The aim is to help new practitioners learn from the past and avoid possible barriers that they may encounter when applying DoE in industry.

An exhaustive literary review was carried out to find articles in which hindrances to the application of DoE were mentioned. The information is organised and grouped into 16 barriers with this end in mind.

The 16 barriers can be classified into three different groups: business barriers; educational barriers; and technical barriers. It is shown that DoE can be successfully applied without overcoming every barrier, although it is inconvenient to do so.

Although DoE is commonly found in statistics and quality literature, it is clearly underused in industry. The paper brings together ideas from those with experience in DoE to detect the reasons behind this anomaly.

Very little material has been published regarding the difficulty of applying DoE. Unfortunately, what is available is repetitive, unstructured and incomplete. The paper is intended to encourage discussion between practitioners and experts, in order to find a way to define, categorise and eventually overcome the most problematic barriers.

The purpose of this paper is to highlight potential issues that often arise during the planning, execution or interpretation of design of experiments (DOE) experiences.

Issues are enumerated and analyzed and sources are presented with practical arguments using DOE texts and papers published in peer‐reviewed journals.

The findings are discussed in relation not only with statistical aspects, but also with how it is critical for paying attention to its methodological and managerial aspects impacting the potential advantages as a continuous improvement tool.

The paper is of interest to DOE practitioners trying to understand potential pitfalls with tips on how to avoid the risk of failures.

This study responds to calls from industry and the literature to cope with the enormous challenges faced by companies operating in competitive business sectors. The main objective of this paper is to investigate how managers can optimise product quality and process efficiency of complex systems.

In this paper, a design of experiments (DoE) method was used to improve the development of complex products and manufacturing processes in the industry of automotive audio components. To identify the optimal combination that minimises quality problems occurring with subwoofer speakers in the marketing, this study proposed a full Factorial experiment 24 with three replications in a single block summarised in an analysis of the interaction among the factors.

The research findings revealed the factors and levels regarding both the product development and manufacturing processes that significantly impact the quality and reliability performance of the subwoofer speaker analysed. The findings from the article allowed the company to prioritise internal improvements to enhance product quality and process efficiency. Other automotive firms will benefit from the research findings obtained.

From a managerial perspective, this research presented the DoE methodology as a real opportunity to deal with the inherent complexity of the manufacturing process in the automotive audio components sector. This research assist managers with insights into how they can improve the quality performance in production systems and in the market.

This study is an original contribution to the advance of theory and empirical implementation of DoE in competitive industrial sectors.