University of Twente Student Theses
Data-driven Priority Setting for Improvements on Service Procedures and Sequences
Santen, J.J. van (2024) Data-driven Priority Setting for Improvements on Service Procedures and Sequences.
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| Abstract: | This research, conducted within ASML's Customer Support EUV Service Engineering Department, focuses on enhancing the prioritisation of procedure and sequence improvements for the TWINSCAN NXE machines. The department processes approximately 14,000 feedback items annually, including procedure and sequence comments, auto-comments, and de-nesting tasks. With the introduction of new machine types, workload increases while engineering capacity remains constant. Current feedback prioritisation relies on intuition, despite the availability of global data on service activities. A prioritisation model was developed using the Analytical Hierarchy Process (AHP), incorporating five factors: frequency, comments, execution time, New Product Introduction (NPI) relevance, and the number of Field Service Engineers involved. The model evaluates ticket impact and combines it with feedback type weights to determine ticket value. The Advanced Impact method, which uses all five factors, achieves a 59% higher cumulative ticket value after 13 weeks compared to the historical approach. Cluster-specific analysis revealed imbalanced resource allocation, with rising backlogs under limited capacity scenarios. The model effectively prioritises resources, supports de-nesting, and accelerates ticket processing by nearly a month. This data-driven approach is vital as workloads increase, ensuring resources are allocated efficiently. |
| Item Type: | Essay (Master) |
| Faculty: | BMS: Behavioural, Management and Social Sciences |
| Subject: | 01 general works, 85 business administration, organizational science |
| Programme: | Industrial Engineering and Management MSc (60029) |
| Link to this item: | https://purl.utwente.nl/essays/104642 |
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