State of The Art of Machine Learning for Product Sustainability

Nowadays, the feasibility and life-time for every business venture is dependent on the generation of sustainable products and services. Almost all businesses and industries have endorsed Machine Learning (ML) technologies. The application of Machine Learning in determining the sustainability aspects is quite a challenging process. ML models can help in capturing the decision-making processes or predict the sustainability evaluation metrics assuming some key aspects such as triple bottom line and life-cycle factors are provided to the models. The main aim of this paper is to present a systematic review of studies related to the product sustainability assessments, framework development using Machine Learning techniques. Search strategies are applied to the most common computer science digital database libraries from 2010 to 2020 in the field of product sustainability using machine learning techniques. 15 out of 23 papers are shortlisted as was considered suitable for this research. A set of the research queries are defined and addressed by the review process. Based on the findings obtained in this literature review, future outlook in the field of Machine Learning for sustainable production is represented.