Predictive and Prescriptive Analytics in Identifying Opportunities for Improving Sustainable Manufacturing
Abstract
:1. Introduction
2. Literature Review
2.1. Sustainable Manufacturing
2.2. Data-Driven Approaches and Business Analytics
3. A Method for Supporting Sustainable Manufacturing
3.1. Data Collection
3.2. Predictive Analytics
3.3. Prescriptive Analytics
- What is the number of defective products predicted during the production process?
- Is there a possibility for incorporating changes during the design process to increase sustainability performance, and if so, what changes are admissible?
4. An Example of Applying the Proposed Method
4.1. Model Specification
- V1—the total time of material processing (in minutes);
- V2—the size of components for material processing (in cm3);
- V3—the material density (in g/cm3);
- V4—the number of defective products;
- V5—the unit cost related to defective products (in EUR);
- V6—the unit production cost (in EUR);
- V7—the material cost per product (in EUR);
- V8—the labor cost per product (in EUR);
- V9—the energy cost per product (in EUR);
- V10—the overhead cost per product (in EUR).
4.2. Predictive Analytics
4.3. Prescriptive Analytics
5. Discussion
6. Conclusions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
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Prediction Model | Learning Set | Testing Set |
---|---|---|
LR | 13.11 | 14.97 |
PR | 11.84 | 12.73 |
NN-GD | 12.04 | 10.83 |
NN-LM | 6.59 | 12.31 |
AV | 19.71 | 23.08 |
Variables | V4 | V5 | V7 | V6 |
---|---|---|---|---|
V1 = 85, V3 = 7.3 | 21 | 63.1 | 148.1 | 246.9 |
… | … | … | … | … |
V1 = 94, V3 = 7.3 | 26 | 73.8 | 148.9 | 254.8 |
… | … | … | … | … |
V1 = 85, V3 = 7.4 | 20 | 62.5 | 150.2 | 248.8 |
… | … | … | … | … |
V1 = 94, V3 = 7.4 | 25 | 73.2 | 151.0 | 256.7 |
… | … | … | … | … |
V1 = 85, V3 = 8.2 | 17 | 55.6 | 166.8 | 263.6 |
… | … | … | … | … |
V1 = 94, V3 = 8.2 | 22 | 65.8 | 172.0 | 271.5 |
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Relich, M. Predictive and Prescriptive Analytics in Identifying Opportunities for Improving Sustainable Manufacturing. Sustainability 2023, 15, 7667. https://doi.org/10.3390/su15097667
Relich M. Predictive and Prescriptive Analytics in Identifying Opportunities for Improving Sustainable Manufacturing. Sustainability. 2023; 15(9):7667. https://doi.org/10.3390/su15097667
Chicago/Turabian StyleRelich, Marcin. 2023. "Predictive and Prescriptive Analytics in Identifying Opportunities for Improving Sustainable Manufacturing" Sustainability 15, no. 9: 7667. https://doi.org/10.3390/su15097667