Ecological Design with the Use of Selected Inventive Methods including AI-Based
Source abstract
Abstract
Creative thinking is an inherent process in the creation of innovations. Imagination is employed to seek creative solutions. This article presents research results on the use of inventive methods to develop an eco-friendly product. A household appliance was selected as the object of research. The article deals with issues relating to eco-design, eco-innovation, and inventory. The process of selecting inventive methods was presented. Selected inventive methods used to develop the product concept were briefly characterized. Creativity sessions were conducted using the methods of brainstorming, stimulating, reverse brainstorming, word games, and superpositions. The effect of these activities is the concept for an eco-innovative product. A product design was developed that is highly recyclable and environmentally friendly. An ecological analysis of the designed product, including AI-based (artificial neural networks), was carried out, which showed the legitimacy of the actions taken to develop an environmentally friendly product. The novelty of the proposed approach consists of combining the use of research data, with new methods for their analysis using both traditional and artificial intelligent tools, to create a transparent and scalable product design. To date, this approach is unique and has no equivalent in the literature. Despite higher manufacturing costs, the more environmentally friendly refrigerator is cheaper in operation (consumes less energy) due to the ecological solutions incorporated into its design.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Sustainable Supply Chain Management · Additive Manufacturing and 3D Printing Technologies · Surface Treatment and Coatings
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Faculty of Mechanical Engineering, Poznan University of Technology, 60-965 Poznan, Poland
Institute of Computer Science, Kazimierz Wielki University, 85-064 Bydgoszcz, Poland
Funding
Poznan University of Technology
References (66)
Show source-provided references
1. Eco-Design and Sustainability in Packaging: A Survey10.1016/j.promfg.2020.01.097 ↗
2. A life-cycle integrated model for product eco-design in the conceptual design phase10.1016/j.jclepro.2022.132516 ↗
3. Eco-tool-seeker: A new and unique business guide for choosing ecodesigntools10.1016/j.jclepro.2017.03.089 ↗
4. Do we share an understanding of transdisciplinarity in environmental sustainability research?10.1016/j.jclepro.2017.09.226 ↗
5. Effective ecodesign implementation with the support of a lifecycle engineer10.1016/j.jclepro.2020.123520 ↗
6. Environmental impacts of household appliances in Europe and scenarios for their impact reduction10.1016/j.jclepro.2020.121952 ↗
7. (2022, January 24). Global consumption value of household appliances from 2013 to 2020. Available online: https://www.statista.com/statistics/270868/forecast-of-global-market-demand-of-electrical-appliances-and-houseware/.
8. Castellani, V., Hidalgo, C., Gelabert, L., Riera, M.R., Escamilla, M., SanyeMengual, E., and Sala, S. (2019). Consumer Footprint: Basket of Products Indicator on Household Goods, Publications Office of the European Union. Technical Report EUR 29710 EN.
9. Reale, F., Castellani, V., Hischier, R., and Sala, S. (2019). Consumer Footprint: Basket of Products Indicator on Household Appliances, European Commission, Joint Research Center. Technical Report EUR 29758 EN.
10. (2022, January 24). Directive 2009/125/EC of the European Parliament and of the Council Establishing a Framework for the Setting of Ecodesign Requirements for Energy-Related Products. Available online: https://eur-lex.europa.eu/LexUriServ/LexUriServ.do?uri=OJ:L:2009:285:0010:0035:en:PDF.
11. Eco-innovation in process engineering: Contradictions, inventive principles and methods10.1016/j.tsep.2018.10.012 ↗
12. Cavallucci, D. (2017). Optimization Methods for Inventive Design. TRIZ—The Theory of Inventive Problem Solving, Springer.10.1007/978-3-319-56593-4 ↗
13. Nyffenegger, F., Ríos, J., Rivest, L., and Bouras, A. (2020, January 5–8). A Method to Formulate Problem in Initial Analysis of Inventive Design. Proceedings of the IFIP International Conference on Product Lifecycle Management, Rapperswil, Switzerland.10.1007/978-3-030-62807-9 ↗
14. Roucoules, L., Paredes, M., Eynard, B., Morer Camo, P., and Rizzi, C. (2020, January 2–4). State of the Art for Evaluation of Inventive Design Solution Concepts. Proceedings of the International Joint Conference on Mechanics, Design Engineering & Advanced Manufacturing, Aix en Provence, France.10.1007/978-3-030-70566-4 ↗
15. Ecodesign methods focused on remanufacturing10.1016/j.jclepro.2009.09.005 ↗
16. Multi-agent System to Support Decision-Making Process in Ecodesign
17. Estimating the cost of product recycling with the use of ecodesign support system
18. Dostatni, E., Rojek, I., and Hamrol, A. (2018). The Use of Machine Learning Method in Concurrent Ecodesign of Products and Technological Processes. Advances in Manufacturing, Springer.10.1007/978-3-319-68619-6_31 ↗
19. Ecodesign field of research throughout the world: Mapping the territory by using an evolutionary lens10.1007/s11192-016-2043-x ↗
20. Economic input-output models for environmental lifecycle assessment10.1021/es983471i ↗
21. Product environmental life-cycle assessment using input-output techniques10.1162/108819899569449 ↗
22. Transitions in sustainable product design research10.1504/IJPD.2009.027475 ↗
23. Mapping the green product development field: Engineering, policy and business perspectives10.1016/S0959-6526(02)00015-X ↗
24. Design for environment: A state-of-the-art review10.1007/s10098-010-0320-6 ↗
25. EcoDesign: What’s happening? An overview of the subject area of EcoDesign and of the papers in this special issue10.1016/j.jclepro.2005.11.010 ↗
26. Ecodesign of Technological Processes with the Use of Decision Trees Method
27. Development capabilities for smart products10.1016/j.cirp.2019.05.010 ↗
28. O’Brien, M., Bleischwitz, R., Steger, S., and Fischer, S. (2013). Europe in Transition: Paving the Way to a Green Economy through Eco-Innovation, European Commission.
29. Resource management practice through eco-innovation toward sustainable development using qualitative information and quantitative data10.1016/j.jclepro.2018.08.058 ↗
30. An ARIZ-based life cycle engineering model for eco-design10.1016/j.jclepro.2013.11.037 ↗
31. Schischke, K., Hagelüken, M., and Steffenhagen, G. (2020, November 06). An Introduction to the Eco-Design Strategy. Why, What and How?. Available online: https://docplayer.pl/2284947-Wprowadzenie-do-strategii-ekoprojektowania-dlaczego-co-i-jak.html.
32. Antoszkiewicz, J. (1990). Heuristic Methods. Creative Problem Solving, PWE.
33. The relationship between innovation and sustainability: A meta-analytic study10.1016/j.jclepro.2020.120745 ↗
34. Creativity: Intrapersonal and Interpersonal Selection of Creative Ideas10.1002/jocb.397 ↗
35. (2021, December 16). Brainstorm—8 Rules. Available online: https://public-media.interaction-design.org/pdf/Brainstorm.pdf.
36. Jagoda-Sobalak, D., and Knosala, R. (2013). Implementation of inventive methods in designing an innovative product. Innovations in Management and Production Engineering, Publishing House of the Polish Society of Production Management. Available online: http://www.ptzp.org.pl/files/konferencje/kzz/artyk_pdf_2013/p007.pdf.
37. Lapunka, I., Jagoda-Sobalak, D., and Marek-Kolodziej, K. (2017). Innovation Project Machine in a Systems Approach to Engineering Management. CBU International Conference Proceedings, ISE Research Institute.10.12955/cbup.v5.936 ↗
38. Searching outside the box in creative problem solving: The role of creative thinking skills and domain knowledge10.1016/j.jbusres.2017.07.021 ↗
39. FAO, and FAOLEX (2022, August 04). Act on Waste Electrical and Electronic Equipment. Available online: https://www.ecolex.org/details/legislation/act-on-waste-electrical-and-electronic-equipment-lex-faoc113636/.
40. (2021, December 27). Industrial Gases. Available online: http://www.linde-gaz.pl.
41. (2021, December 20). Smart Glass. Available online: http://smartglasspolska.pl.
42. Kruszyńska, A. (2014). The Method of Ecological Quality Assessment of Products. [Master’s Thesis, Poznan University of Technology].
43. Ganesapillai, M., Sinha, A., Mehta, R., Tiwari, A., Chellappa, V., and Drewnowski, J. (2022). Design and Analysis of Artificial Neural Network (ANN) Models for Achieving Self-Sustainability in Sanitation. Appl. Sci., 12.10.3390/app12073384 ↗
44. Liu, Y., Zhang, S., Zhang, J., Tang, L., and Bai, Y. (2021). Using Artificial Neural Network Algorithm and Remote Sensing Vegetation Index Improves the Accuracy of the Penman-Monteith Equation to Estimate Cropland Evapotranspiration. Appl. Sci., 11.10.3390/app11188649 ↗
45. Fernández-López, A., Marín-Sánchez, D., García-Mateos, G., Ruiz-Canales, A., Ferrández-Villena-García, M., and Molina-Martínez, J.M. (2020). A Machine Learning Method to Estimate Reference Evapotranspiration Using Soil Moisture Sensors. Appl. Sci., 10.10.3390/app10061912 ↗
46. Menapace, A., Zanfei, A., and Righetti, M. (2021). Tuning ANN Hyperparameters for Forecasting Drinking Water Demand. Appl. Sci., 11.10.3390/app11094290 ↗
47. Chen, Y., Song, L., Liu, Y., Yang, L., and Li, D. (2020). A Review of the Artificial Neural Network Models for Water Quality Prediction. Appl. Sci., 10.10.3390/app10175776 ↗
48. Ma, Y.-J., and Zhai, M.-Y. (2019). A Dual-Step Integrated Machine Learning Model for 24h-Ahead Wind Energy Generation Prediction Based on Actual Measurement Data and Environmental Factors. Appl. Sci., 9.10.3390/app9102125 ↗
49. Faraji, J., Abazari, A., Babaei, M., Muyeen, S.M., and Benbouzid, M. (2020). Day-Ahead Optimization of Prosumer Considering Battery Depreciation and Weather Prediction for Renewable Energy Sources. Appl. Sci., 10.10.3390/app10082774 ↗
50. Rojek, I., Mikołajewski, D., Dostatni, E., and Macko, M. (2020). AI-optimized technological aspects of the material used in 3D printing processes for selected medical applications. Materials, 13.10.3390/ma13235437 ↗
51. Rojek, I., Mikołajewski, D., Macko, M., Szczepański, Z., and Dostatni, E. (2021). Optimization of extrusion-based 3D printing process using neural networks for sustainable development. Materials, 14.10.3390/ma14112737 ↗
52. Computational gait analysis for post-stroke rehabilitation purposes using fuzzy numbers, fractal dimension and neural networks
53. Prokopowicz, P., and Mikołajewski, D. (2022). Fuzzy Approach to Computational Classification of Burnout—Preliminary Findings. Appl. Sci., 12.10.3390/app12083767 ↗
54. Artificial neural networks for small dataset analysis
55. Using deep neural network with small dataset to predict material defects10.1016/j.matdes.2018.11.060 ↗
56. Michałowski, T., and Zieliński, K. (2022, January 25). Glass with Variable Translucency. Available online: https://www.swiat-szkla.pl/kontakt/7236-szklo-o-zmiennej-przeziernosci.html.
57. (2022, January 25). Profiglass. Available online: http://www.profiglass.com.pl/.
58. Sustainable product development and service approach for application in industrial lighting products10.1016/j.spc.2021.04.003 ↗
59. Novelty metrics in engineering design10.1080/09544828.2021.1928024 ↗
60. User-centred design approach with misidentified end-users: Case study for smart composite structures10.1080/09544828.2021.1951686 ↗
61. Design creativity: Refined method for novelty assessment
62. Refined metrics for measuring ideation effectiveness10.1016/j.destud.2009.07.002 ↗
63. Unlocking employees’ green creativity: The effects of green transformational leadership, green intrinsic, and extrinsic motivation10.1016/j.jclepro.2020.120229 ↗
64. The creative imperative: The role of creativity, creative problem solving and insight as key drivers for sustainability10.1016/j.jclepro.2016.09.162 ↗
65. (2022, January 25). Media Expert. Available online: http://www.mediaexpert.pl/.
66. Neural networks as performance improvement models in intelligent CAPP systems