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Researchers have promoted statistical improvement methods as essential for product and process improvement for decades. However, studies show that their use has been moderate at best. This study aims to assess the use of statistical process control (SPC), process capability analysis, and design of experiments (DoE) over time. The study also highlights important barriers for the wider use of these methods in Sweden as a follow-up study of a similar Swedish study performed in 2005 and of two Basque-based studies performed in 2009 and 2010. While the survey includes open-ended questions, the results are mainly descriptive and confirm results of previous studies. This study shows that the use of the methods has become more frequent compared to the 2005 study. Larger organisations (>250 employees) use the methods more frequently than smaller organisations, and the methods are more widely utilised in the industry than in the service sector. SPC is the most commonly used of the three methods while DoE is least used. Finally, the greatest barriers to increasing the use of statistical methods were: insufficient resources regarding time and money, low commitment of middle and senior managers, inadequate statistical knowledge, and lack of methods to guide the user through experimentations. [ABSTRACT FROM AUTHOR]

Engineering process control and high-dimensional, time-dependent data present great methodological challenges when applying statistical process control (SPC) and design of experiments (DoE) in continuous industrial processes. Process simulators with an ability to mimic these challenges are instrumental in research and education. This article focuses on the revised Tennessee Eastman process simulator providing guidelines for its use as a testbed for SPC and DoE methods. We provide flowcharts that can support new users to get started in the Simulink/Matlab framework, and illustrate how to run stochastic simulations for SPC and DoE applications using the Tennessee Eastman process. [ABSTRACT FROM AUTHOR]

This paper presents a tentative analysis method for unreplicated factorial designs where regular statistical experimental analysis cannot be used. The methodology is demonstrated through the analysis of an unreplicated two-level, two-factor factorial experiment performed in a continuous production process where the process was not in statistical control and where changes in the experimental design made conventional experimental analysis impossible. The first step of the analyses included screening of the sampled data. Principal component analysis and factor analysis were then used to create an overview of how the various responses and experimental factors were related. Carbon monoxide efficiency was selected as the most important parameter to be analysed further. Elastic net regression was used as a screening tool to remove non-significant factors, interaction, and covariates. Finally, the carbon monoxide efficiency variation was modelled using an intervention analysis. Two experimental factors were found to actively influence the response. The experiment that from other perspectives can be considered to be unanalysable, did thus reveal causal effects. The results imply that for processes where the process dynamics may be monitored, observations of the process dynamics may reduce the needs for repeated experimental runs, thus reducing the experimental costs. [ABSTRACT FROM AUTHOR]

This paper presents ideas and observations about the infrequent use of factorial experimental designs; although the ideas presented are inspired by a case study, the paper is also conceptual in nature. The ideas build on the experimental practices at a large Swedish process industry manufacturer, where these practices were discussed with engineers using in-depth interviews. Factorial design is not used because, for example, statistical rigor is seldom required and because designs of experimental methods are seen as too restrictive to accommodate and adjust to events occurring during long experimental campaigns. The interview results indicate that, while the scepticism of many respondents may be justified, lack of training, interest, and learning time are major obstacles to applying improved methodologies. Some ideas for overcoming these obstacles are suggested. [ABSTRACT FROM AUTHOR]

This paper aims to develop a conceptual framework for testing the motivation to engage in improvement work. The framework is based on Ajzen's theory of planned behavior (TPB), that we suggest can be used to facilitate the implementation of improvement programmes. By using the model and probing intentions, attitudes, norms and perceived ability related to improvement work, we believe hindrances for implementation of improvement programmes will be exposed. When operationalising the framework we developed a survey instrument based on TPB and then made an initial empirical test by distributing it to 124 employees (response rate 67%) of three manufacturing small- and medium-sized enterprises. Factor analysis and regression were used to analyse the survey and follow-up interviews with employees and managers were used to validate the results. This initial test of the instrument showed that it has sound measurement properties, indicated by clear factor structure and good internal consistency. Interview data also validated that the instrument was able to capture important aspects related to implementation of improvement work. Based on the result, we conclude that TPB may be useful for guiding management actions. However, since our study only draws on a limited empirical sample, future research is needed to test the contextual validity. [ABSTRACT FROM PUBLISHER]

Traceability is normally difficult to achieve in continuous processes, since there are no natural batch structures. In this article, we demonstrate flow-based simulation using process data to improve traceability in a continuous pelletising process. Using the simulation model, the engineers could test the impacts of process disturbances, identify cause and effect relations and aid control in case of process disturbances. In a field trial where the chemistry of an additive was varied during production of a special product, the simulation forecasts predicted the level of the chemical content after the plant within the errors that the engineers found acceptable. [ABSTRACT FROM PUBLISHER]

Traceability is important for identifying the root causes of production-related quality problems. Traceability can often be reached by adding identification markers on products, but this is not a solution when the value of the individual product is much lower than the incurred cost of a marking system. This is the case for continuous production of granular media. The use of radio frequency identification (RFID) techniques to achieve traceability in continuous granular flows has been proposed in the literature. We study through experiments different methods to improve the performance of such an RFID system. For example, larger transponders and multiple readers are shown to improve the RFID system performance. [ABSTRACT FROM AUTHOR]

This article proposes a Bayesian procedure to calculate posterior probabilities of active effects for unreplicated two-level factorials. The results from a literature survey are used to specify individual prior probabilities for the activity of effects and the posterior probabilities are then calculated in a three-step procedure where the principles of effects sparsity, hierarchy, and heredity are successively considered. We illustrate our approach by reanalyzing experiments found in the literature. [ABSTRACT FROM AUTHOR]

Process dynamics is an important consideration during the planning phase of designed experiments in dynamic processes. After changes of experimental factors, dynamic processes undergo a transition time before reaching a new steady state. To minimize experimental time and reduce costs and for experimental design and analysis, knowledge about this transition time is important. In this article, we propose a method to analyze process dynamics and estimate the transition time by combining principal component analysis and transfer function-noise modeling or intervention analysis. We illustrate the method by estimating transition times for a planned experiment in an experimental blast furnace. [ABSTRACT FROM AUTHOR]

This paper describes a joint project started by citizens, trade life and local government of the Swedish municipality of Jokkmokk to create a positive societal development based on the tenets of Total Quality Management. The project had a duration of two years, and also included a parallel effort made in Mansfield in the United Kingdom, although this paper describes the Jokkmokk part of the project. The evaluation was based on surveys and interviews analysed using Soft Systems Methodology. The analysis shows that most respondents thought that the project was successful in changing attitudes of the people of Jokkmokk and of creating valuable networks. The project also had an aim to create involvement of ordinary citizens and many activities were addressed to let citizens develop and generate ideas and participate in societal activities and decision making. The evaluation showed that the leaders and politicians of Jokkmokk were not ready for the used bottom-up approach. The analysis also underlines the importance of communicating the mission and goals of the project. We consider the achievements, due to the short duration of the project, substantial and both the positive and the negative outcomes present valuable lessons from a societal development perspective. [ABSTRACT FROM AUTHOR]

Discontinuous processes dominate experimental applications in practice as well as in literature. Continuous processes constitute a significant part of goods production, and the need to gain knowledge using experiments are as relevant in such environments as in, for example, parts production. We argue that the characteristics of continuous processes affect the prerequisites for experimental efforts to such an extent that they need special attention. To describe considerations when planning experiments in a continuous process, experiments performed in a blast furnace process are studied. We propose a tentative list of special considerations, which are discussed and summarized in a thirteen-step check list. [ABSTRACT FROM AUTHOR]

Students taking courses in quality management at Luleå University of Technology receive extensive education in statistical methods. To improve the education and to understand what kind of competence students need when they graduate, a survey was preformed examining how and to what extent the methods Statistical Process Control, Capability Analysis and Design of Experiments are used by organisations hiring the alumni. The result shows that the students employed in the Swedish industrial sector witness a modest use of statistical methods, while use of statistical methods in other sectors hiring the alumni is uncommon. Lack of competence and resources within the organizations are stated as hindrances to expanded use. Conclusions from the study are that implementation techniques must be emphasized in the curriculum and that different types of courses should be given – practical, hands-on courses for engineers, managers and others working in organizations. Furthermore, courses offered at universities must have a strong focus on practical problems such as difficulties randomizing experiments and that graphical methods should be favoured. [ABSTRACT FROM AUTHOR]

As teachers, the authors are eager to confirm that what they teach is correct and that their topics are both fun and worth studying further. How they make their propositions attractive is, of course, context dependent. This article describes how a one-hour introductory course in design of experiments (DOE) can be used to attract high school students to study science and engineering in general and quality management in particular. The course is based on a 2² factorial design inspired by the Pepsi Challenge and is evaluated in the light of the "Seven Good Principles to Achieve Good Learning." Results of the course show that it is possible to teach DOE to students in high school and at the same time provide a fun experience. Many of the statistical concepts appear to have been grasped up to the level of comprehension of effects and statistical significant effects compared to random error effects. [ABSTRACT FROM AUTHOR]