Pia Sandvik Wiklund

Widening the Six Sigma concept: An approach to improve organizational learning

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 long-term 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.

Student focused design and improvement of university courses

Customer satisfaction has become a key factor in the strategic work of many universities towards the increasing competition regarding student recruitment. This paper presents a systematic approach to the course development process where focus is put on student satisfaction and learning. The approach consists of a combined usage of several methods, such as quality function deployment and conjoint analysis, that together transform student needs into quantified course attributes. In the paper, a two‐semester graduate course has been developed where the combined usage of the applied methods has shown itself to be very powerful when designing services from student satisfaction and learning perspectives. The outcome of the study is a university course where pedagogical and learning aspects have been combined with contents and work approaches with substantial interest for the industry.

Innovation and TQM in Swedish higher education institutions : possibilities and pitfalls

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.

Finding Active Factors from Unreplicated Fractional Factorials Utilizing the Total Time on Test (TTT) Technique

Much research has been devoted to improving the process of identifying active factors from designed experiments. Generally, the proposed methods rely on an estimate of the experimental error. Here we present a method based on the TTT (total time on test) plot, where the scaled TTT transform enables an evaluation of the contrasts independently of the experimental error. The method can be separated into two parts. The first part consists of a transformed TTT plot for a visual evaluation of data. The second part is more formal and utilizes the cumulative TTT statistic for testing the significance of contrasts. A simulation study shows the power of the method compared with competing methods. Five data sets are used to show that the conclusions drawn are consistent with those obtained using other suggested methods. Copyright

INTRODUCING DOMAIN KNOWLEDGE FOR SELECTION OF ACTIVE FACTORS IN DESIGNED EXPERIMENTS

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.