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This study aims to create an efficient approach to validate building energy simulation models amidst challenges from time-intensive data collection. Emphasizing precision in model calibration through strategic short-term data acquisition, the systematic framework targets critical adjustments using a strategically captured dataset. Leveraging metrics like Mean Bias Error (MBE) and Coefficient of Variation of Root Mean Square Error (CV(RMSE)), this methodology aims to heighten energy efficiency assessment accuracy without lengthy data collection periods.

A standalone school and a campus facility were selected as case studies. Field investigations enabled precise energy modeling, emphasizing user-dependent parameters and compliance with standards. Simulation outputs were compared to short-term actual measurements, utilizing MBE and CV(RMSE) metrics, focusing on internal temperature and CO₂ levels. Energy bills and consumption data were scrutinized to verify natural gas and electricity usage against uncertain parameters.

Discrepancies between initial simulations and measurements were observed. Following adjustments, the standalone school 1’s average internal temperature increased from 19.5 °C to 21.3 °C, with MBE and CV(RMSE) aiding validation. Campus facilities exhibited complex variations, addressed by accounting for CO₂ levels and occupancy patterns, with similar metrics aiding validation. Revisions in lighting and electrical equipment schedules improved electricity consumption predictions. Verification of natural gas usage and monthly error rate calculations refined the simulation model.

This paper tackles Building Energy Simulation validation challenges due to data scarcity and time constraints. It proposes a strategic, short-term data collection method. It uses MBE and CV(RMSE) metrics for a comprehensive evaluation to ensure reliable energy efficiency predictions without extensive data collection.

This study aims to investigate the contribution of higher education institutions (HEIs) to the sustainable development goals (SDGs) and propose strategies to cultivate a culture centred on the SDGs in HEIs.

The methodology used encompassed an integrative literature review, combining bibliographic analysis on how HEIs incorporate the SDGs into their practices, adopting a qualitative approach for the analysis and categorization of the results.

The multifaceted contributions of HEIs in promoting the SDGs stand out, through their roles in teaching, research, management and integration and communication between university and society.

While influencing policies at various levels, HEIs encounter challenges in the effective integration of SDGs into their strategies. This underscores the need for contextualized governance, understanding students’ perspectives on sustainability and active external collaboration in policy formulation.

There is an urgent need to integrate SDGs into academic programmes, emphasizing the importance of redesigning curricula, actively involving teachers, researchers and students, establishing partnerships and promoting research applied to SDGs.

The social relevance of the study lies in the emphasis on an SDG-centred culture, involving teaching, research, outreach, community engagement and governance practices.

The study’s uniqueness lies in identifying persistent challenges during the transition to an SDG-centred culture, necessitating multisectoral collaboration and educational programmes that integrate sustainability principles into the strategy of HEIs.

Overall equipment effectiveness (OEE) is a metric for estimating equipment effectiveness of the industrial systems. The purpose of this paper is to identify maintenance improvement potentials using an OEE assessment within the croissant production line.

The present work is carried out by analyzing the failure and repair data of the line. The failure data cover a period of 15 months. During this period the croissant production line usually operates over the entire day (24 h per day) in three 8-h shifts per day, and pauses at the weekends. Descriptive statistics of the failure and repair data for the line based on scheduled and unscheduled interruptions were carried. Moreover, the actual availability (A), performance efficiency (PE) and quality rate (Q) measures, together with the complete OEE for each working day for the croissant production line, were shown.

The main objectives are to understand the operation management of the croissant production line, and to measure the OEE characteristics in precise quantitative terms. OEE analysis can help the company to identify the primary problems concerning the A, PE and Q and acts immediately.

This paper presents a successful evaluation of OEE which will provide a useful guide to aspects of the production process, which identifies the critical points of the line that require further improvement through effective maintenance strategy (i.e. total productive maintenance). Moreover, the analysis provides a useful perspective and helps managers and engineers make better decisions on how to improve manufacturing productivity and quality.