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Milling is a flexible creation process for the manufacturing of dies and aeronautical parts. While machining thin-walled parts, heat generation during machining essentially affects the accuracy. The workpiece temperature (WT), as well as the responses like material removal rate (MRR) and surface roughness (SR) for input parameters like cutting speed (CS), feed rate (F), depth-of-cut (DOC), step over (SO) and tool diameter (TD), becomes critical for sustaining the accuracy of the thin walls.

Response surface methodology was used to make 46 tests. To convert the multi-character problem into a single-character problem, the weightage was assessed using the entropy approach and the grey relational coefficient (GRC) was determined. To investigate the connection among input parameters and single-objective (GRC), a fuzzy mathematical modelling technique was used. The optimal performance of process parameters was estimated by grey relational entropy grade (GREG)-fuzzy and genetic algorithm (GA) optimization.

SR was found to be a significant process parameter, with CS, feed and DOC, respectively. Similarly, F, DOC and TD were found to be significant process parameters with MRR, respectively, and F, DOC, SO and TD were found to be significant process parameters with WT, respectively. GREG-fuzzy-GA found more suitable for minimizing the WT with the constraint s of SR and MRR and provide maximum desirability of 0.665. The projected and experimental values have a good agreement, with a standard error of 5.85%, and so the responses predicted by the suggested method are better optimized.

The GREG-fuzzy-GA is a new hybrid technique for analysing Inconel625 behaviour during machining in a 2.5D milling process.

There is a lack of clarity about how lecturer collaboration in light of learning and (professional) development fits within the framework of a quality culture in higher education institutions (HEIs). More specifically, it is unclear how collaboration is present or stimulated in the organisational context, triggering working mechanisms leading to quality-related outcomes. Therefore, the purpose of this study is to relate HEIs' quality culture to lecturer collaboration.

This exploratory study relates institutions’ quality culture to lecturer collaboration via semi-structured interviews and document analysis at the institutional level in four Flemish HEIs.

The results demonstrate collaboration as a working mechanism driven by the institutional strategy. In this way, lecturers’ professional development (PD) is stimulated. The results also indicate that collaboration is present within lecturers’ PD: working together during or sharing experiences after PD initiatives is considered useful for quality teaching and learning.

Following the growing attention in research and practice to lecturer collaboration, this study incorporates lecturer collaboration in the framework of quality culture within HEIs.