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Unveiling undergraduate production engineering students' comprehension of process flow measures
Abstract Paper aims This study analyzes the comprehension of production engineering students about the influence of some key variables on the process performance measures in a service process. Originality This paper points out the need for educators to re-evaluate their approaches to teaching the Op...
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Published in: | Produção : uma publicação da Associação Brasileira de Engenharia de Produção 2022, Vol.32 |
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Main Authors: | , , , , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites |
Online Access: | Get full text |
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Summary: | Abstract Paper aims This study analyzes the comprehension of production engineering students about the influence of some key variables on the process performance measures in a service process. Originality This paper points out the need for educators to re-evaluate their approaches to teaching the Operations Management (OM) principles related to process flow measures. Research method This study used scenario-based role-playing experiments with 2×2×2 between-subject factorial design with three independent variables (variability of activities, capacity utilization, and resource pooling) and four dependent variables related to key internal process performance measures (Flow Time, Overall Quality of service, Quality of service employees, and Queue Size). The sample was composed of 178 undergraduate production engineering students from a large university in Brazil from various institution units. Main findings These results show that students perceived the use of resource pooling as an impactful practice. However, the students did not correctly identify the effects of increasing resource utilization and the variability on flow time and queue size when activities are pooled. Implications for theory and practice The teaching of basic concepts of OM requires the support of computational tools. Undergraduate courses that contemplate subjects in the field of OM should work more intensely on simulation-based learning. |
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ISSN: | 0103-6513 1980-5411 1980-5411 |
DOI: | 10.1590/0103-6513.20220020 |