Mid Sweden University

Emphasis on quality improvement has been one of the most characteristic features of higher education policy in Nordic and other European countries during the 1990s. In Sweden, the universities’ work with quality management has been evaluated for several years. In January 2001, the National Agency of Higher Education in Sweden introduced a new comprehensive system for quality assessment. The Swedish assessment system stresses that the assessment should have as a corner-stone the specific prerequisites for each university and subject, e.g. business administration and their development strategy. The comprehensive quality assessments of Swedish higher education institutions are discussed together with stimulating innovation and continuous improvement of higher education.

Six Sigma has been established as an approach to improving organizational performance, and many manufacturing companies have reported on their successive work with Six Sigma programmes. Often, the focus of Six Sigma is put on only reducing defects and improving process capability. This paper discusses Six Sigma as a company-wide approach for organizational improvement incorporating organizational learning. Six Sigma programmes have been studied and the fundamental principles of organizational learning have been applied in order to improve the longterm implementation of the programmes. The paper also discusses factors associated with manufacturing work organization and leadership that are essential for improving organizational learning and for stimulating the competence development and motivation among personnel.

Unreplicated factorial designs are widely used for designed experimentation in industry. In the analysis of designed experiments, the experimental factors influencing the response must be identified and separated from those that do not. An abundance of procedures intended to perform this selection have been introduced in the literature. A recent study indicated that the procedure due to Box and Meyer outperforms the lot of the other selection procedures in terms of efficiency and robustness. The procedure of Box and Meyer rests on a quasi-Bayesian foundation and utilizes generic domain knowledge, in the form of a common-for-all-factors a priori probability, that a factor significantly influences the response, to calculate an a posteriori probability for each factor. This paper suggests a strategy for introducing more elaborate domain knowledge about the experimental factors in the procedure of Box and Meyer, aiming to further improve its performance.