The impact of safety climate on human-technology interaction and sustainable development: Evidence from Indonesian oil and gas industry

Masudin, Ilyas; Tsamarah, Nisrina; Restuputri, Dian Palupi; Trireksani, Terri; Djajadikerta, Hadrian Geri

doi:10.1016/j.jclepro.2023.140211

Cited by 6 publications

(1 citation statement)

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“…Additionally, incorporating Condition-Based Maintenance and Reliability Centered Maintenance methods can help identify failure causes, prioritize critical components, and implement timely maintenance actions to prevent downtime and enhance equipment reliability [7]. Transitioning towards proactive maintenance strategies is crucial for achieving sustainable, safe, and reliable operations in the Indonesian energy landscape [8]- [10].…”

Section: Introductionmentioning

confidence: 99%

The Influence of Business Analytics and Big Data on Predictive Maintenance and Asset Management

Judijanto,

Uhai,

Suri

2024

ESISCS

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This study investigates the impact of business analytics and big data on predictive maintenance and asset management practices within the energy industry in Indonesia. A quantitative research approach, utilizing a survey methodology, was employed to gather data from stakeholders representing various sectors of the energy industry. The study analyzed the relationships between business analytics, big data, predictive maintenance, and asset management using structural equation modeling (SEM) with Partial Least Squares (PLS) regression. The results indicate significant positive relationships between the utilization of business analytics and big data and various performance metrics, including asset reliability, operational efficiency, and cost savings. Furthermore, organizational factors such as leadership support and data quality were found to play a crucial role in facilitating the adoption and implementation of predictive maintenance strategies. The findings underscore the transformative potential of data-driven maintenance strategies in enhancing operational efficiency, reducing downtime, and improving asset reliability within the Indonesian energy industry.

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Section: Introductionmentioning

confidence: 99%