Sustainability and Resilience : Improving Energy Efficiency at a Beverage Manufacturing Plant / Ioannis Koliousis, Abhishek Singh.

Format:

Book

Author/Creator:

Koliousis, Ioannis, author.

Singh, Abhishek, author.

Language:

English

Subjects (All):

Energy consumption.

Physical Description:

1 online resource

Other Title:

Sustainability and Resilience

Place of Publication:

Los Angeles, California : SAGE Publications, Inc, 2024.

Summary:

This Data Challenge focuses on analyzing energy consumption within a fast-moving consumer goods (FMCG) manufacturing plant. Students are provided with detailed data on the power ratings, usage patterns, energy consumption metrics, and environmental impact of various machines. The goal is to conduct qualitative and quantitative analyses to understand the diversity in energy demands across different equipment. Through this analysis, students can understand the implications of energy consumption on sustainability by identifying high-usage machines and their carbon footprint. They will be able to evaluate the relationship between power ratings and operational hours for a comprehensive assessment of resource utilization. Additionally, students will synthesize insights from the data analysis into practical recommendations for enhancing efficiency and develop an interdisciplinary perspective by connecting technical data points to broader environmental and regulatory factors. The dataset offers a real-world scenario for students to apply analytical approaches such as benchmarking, data visualization, and predictive modeling. They are prompted to formulate strategies focused on adopting energy-efficient technology alternatives, optimizing operational hours, and tracking sustainability metrics over time. Discussion questions facilitate critical thinking on striking the right balance between economic and environmental factors. Overall, this Challenge provides a rich foundation for honing the data interpretation, decision-making, and communication skills of upper-division undergraduates and graduate students. No specialized prior knowledge is required to complete the Data Challenge; however, a working understanding of quantitative and qualitative analysis, including statistical analysis and introductory decision-making, is necessary.

Notes:

Description based on publisher supplied metadata and other sources.

ISBN:

1-0719-7455-6

9781071974551

OCLC:

1463993191