The Factory of the Future: An analysis on buildings, HVAC, and heat recovery systems in order to reduce energy consumption
Bibliographic record
Abstract
The industrial sector in Sweden accounted for 38 percent of the country’s total energy consumption in 2019. As the world’s focus has shifted drastically on energy consumption, the industry sector’s has as well due to energy initiatives and government-driven regulations. The energy issue is currently of great relevance for energy-intensive industries where enormous potential remains due to factors e.g., lack of energy-efficiency policies and insufficient investments in sustainable buildings. This paper presents an analysis of energy consumption for active and passive building envelopes, focusing on buildings and heating, ventilation, and airconditioning systems (HVAC-systems). The focus on buildings and HVAC-systems enabled an analysis that highlighted key areas for energy-savings solutions outside the scope of production processes. The project was carried out at three different production facilities within Alfa Laval: Lund, Sweden; Ronneby, Sweden; Kolding, Denmark. The methodology for this project provided for the use of literature, benchmarking with energy-intensive industries, a regression analysis of heating degree days, data analysis for energy consumption from sub-meters as well as the participation during Energy Mapping of two of the sites. The analysis investigated the three production facilities’ building structures, lighting solutions, district heating systems, ventilation systems and heat recovery possibilities. The work developed presented an indicative assessment of the overall potential for certain energy measures to contribute to minimizing each production site’s energy consumption. The greatest potential in terms of saving energy for reusing waste heat from major energy users was found to be recovery at low temperatures (< 50 C) by utilizing heat pumps and heat exchangers. Current ventilation systems at all sites are outdated in regards to how the majority of ventilation units not having been upgraded since the initial builds and the incompatibility with new control systems. The modernization of ventilation units to enable recovery at low temperatures was seen as a key area and highly profitable for optimal energy consumption. Implementing a building management system for controlling and monitoring the HVAC-system was also regarded as vital for maximizing regulating capabilities, allowing for energy savings during off-peak hours as well as removing manual labor. In addition to common measures for all three production facilities, a variation of alternative energy measures were discussed for each site separately.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".