Physics Maths Engineering
Hamed Gholami
Peer Reviewed
Key Questions
1. What are sustainable reconfigurable manufacturing systems?
Sustainable reconfigurable manufacturing systems (SRMSs) are designed to quickly adapt to changes in product types and volumes through the modular and flexible arrangement of resources, while simultaneously ensuring that operations are conducted in an environmentally responsible and socially beneficial manner[1]. 2. What AI techniques are most promising for SRMSs?
The study finds that machine learning, big data analytics, fuzzy logic, and programming are the most promising AI techniques for sustainable reconfigurable manufacturing systems[1]. 3. How does the study evaluate AI techniques for SRMSs?
The study develops an AI-enabled methodological approach in Python, integrating fuzzy logic to navigate uncertainties in evaluating technique performance. It also incorporates sensitivity analysis and uses an AI-powered decision-making application with large language models for assessment[1]. 4. What are the benefits of using fuzzy logic programming in Python for SRMSs?
Using fuzzy logic programming in Python as the computational foundation significantly enhances precision, efficiency, and execution time, offering critical insights that enable more timely and informed decision-making in the field of sustainable reconfigurable manufacturing systems[1].
