Widespread recognition of the strategic imperative posed by a turbulent external environment has brought into focus a key challenge for firms – that of increasing involvement in innovation by the staff in the organisation. Much research has suggested that organisations that mobilise a large proportion of their staff to participate in innovation can make significant gains. Achieving this depends on a systematic process of organisational development in which the facilitative patterns of behavioural routines are extended and reinforced, so that they become a major culture change. This paper reports on progress with this organisational development methodology using a detailed case study of its use within a major mining company in South Africa. It makes use of a reference model framework to help structure and direct the change process towards enabling higher involvement in innovation. In particular it explores practical issues involved in moving a large organisation along a path of high involvement innovation

This study commences a process of developing a scale for the measurement of service quality in higher education in South Africa and also examines the relationship between the measures of service quality on the one hand and some other related variables such as intention to leave the university, trust in management of the university and the overall satisfaction with the university. Using structured questionnaires, survey data was collected from students (n = 391) in two South African universities. Findings indicate that the 52-item measure of service quality in higher education is a multidimensional construct loading on 13 factors with a high reliability coefficient (0.93) and some construct validity. Significant relationships were also found between service quality in HE and other study variables-intention to leave university, trust in management of the university and overall satisfaction with the university. Some further research directions were suggested and policy implications of findings discussed.

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The particle size distribution produced in particulate processes generally has a large impact on process economics, and the crystal size distribution produced in industrial crystallizers is no exception. Crystal Size Distribution (CSD) control is therefore desirable. Its establishment is the main objective of a joint research program between three research groups within the Delft University of Technology and several industrial participants. This paper presents a review of this project and intends (1) to illustrate the development of an on-line crystal size measuring technique, (2) to illustrate how information on CSD can be used to derive a dynamic process model and (3) to emphasize the need for effective process inputs and to make suitable suggestions in that direction.

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Experimental measurements of the crystal-size distribution ( CSD) clearly indicate a pronounced difference in the dynamic behavior of a 20-and 970-L continuous crystallizer that produces ammonium sulfate. The difference in their circulation time offers a probable explanation for this phenomenon. It causes different supersaturation profiles in the two crystallizers, which leads to internal fines dissolution in the large crystallizer. This contributes to the observed oscillations in the 970-L crystallizer as opposed to the first-order responses in the 20-L crystallizer. To numerically study the effect of the supersaturation profile a dynamic model, from which the MSMPR (mixed suspension mixed product removal) assumption is omitted, is developed. Calculated supersaturation profiles differ considerably for the 20-L, the 970-L and an imaginary 50,000-L continuous evaporative crystallizer. Coincident with changes in the supersaturation profiles, the numerical solution of the model indicates the tendency of large crystallizers to oscillate and supports this suggested explanation. I. Experimental IntroductionIndustrial crystallizers are known to exhibit large variations in the crystal-size distribution (CSD) they produce. These variations most probably result from unstable behavior of the crystallization process itself, although the influence of unwanted changes in process conditions cannot be fully excluded. Laboratory crystallizers, on the other hand, usually demonstrate stable operation that is illustrated by rapidly decaying CSD-transients (Randolph and Larson, 1988). Relatively few experimental studies have been devoted to the dynamic behavior of crystallizers in general, particularly to the difference in dynamic behavior between the crystallizers of different scale.It was shown previously (Jager et al., 1990a,b) that CSD transients in a 20-L crystallizer rapidly approach steady-state conditions. These results can be simulated well with an MSMPR model including secondary nucleation kinetics combined with attrition. In this article, this analysis is made to a larger-scale of operation. Also discussed are CSD transients measured in a 970-L crystallizer, which was operated with and without fines removal and whose results are compared with CSD transients measured in the 20-L crystallizer, operated at the same con- 182February 1991 ditions using the same ammonium sulfate solur ion. Finally, differences between the two crystallizers are explained. Experimental ProcedureThe 20-L crystallizer is a continuous, evaporative, drafttube crystallizer, operated at 50°C. The crystalliier has a propeller stirrer of 100-mm-diameter operated at 700 rpm. Other dimensions, together with a process scheme, are given by . The slurry circulation time is approximately 2 seconds, equally divided between the inner and the outer tube. In this article, the crystallizer startup, at the operating conditions of the 970-L crystallizer, will be discussed. Sieve analysis of filtered and dried samples, using 20 Veco microprecision sieves, was used to ...

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