With the burgeoning transition toward electrified automobile fleets, electric-vehicle batteries (EVBs) have become one of the critical aspects to be considered to avoid resources issues while achieving necessary climate goals. This paper compiles and syntheses reported barriers, enablers, involved stakeholders, and business models of Circular Economy (CE) implementation of the EVBs based on a systematic literature review (SLR). Findings indicate that inefficient and inadequate government policy, lack of safety standards, and high recycling costs are the three most reported barriers. The barriers have interconnections with each other, implying the necessity for simultaneous strategies. Based on the barriers-enablers analysis, the key strategies establishing the CE for the EVBs are innovative business models, economic incentives, EVB standards, legal environmental responsibilities, and certification, whereas the optimized supply-chain operations can be realized through eco-design of the EVBs, battery modularization, proper technology for checking, diagnosing, tracking, information sharing, extensive collaboration, alignment of supply-chain stakeholders, innovative business model, and certification. A conceptual framework presenting the required strategies for both establishing the CE and optimizing the circular supply chain system of the EVBs was then proposed. Potential future research directions are also discussed.

In the response surface methodology (RSM), the designed experiment helps create interfactor orthogonality and interpretable response models for the purpose of process and design optimization. However, along with the development of data-recording technology, observational data have emerged as an alternative to experimental data, and they contain potential information on design/process parameters (as factors) and product characteristics that are useful for RSM analysis. Recent studies in various fields have proposed modifications to the standard RSM procedures to adopt observational data and attain considerable results despite some limitations. This paper aims to explore various methods to incorporate observational data in the RSM through a systematic literature review. More than 400 papers were retrieved from the Scopus database, and 83 were selected and carefully reviewed. To adopt observational data, modifications to the procedures of RSM analysis include the design of the experiment (DoE), response modeling, and design/process optimization. The proposed approaches were then mapped to capture the sequence of the modified RSM analysis. The findings highlight the novelty of observational-data-based RSM (RSM-OD) for generating reproducible results involving the discussion of the treatments for observational data as an alternative to the DoE, the refinement of the RSM model to fit the data, and the adaptation of the optimization technique. Future potential research, such as the improvement of factor orthogonality and RSM model modifications, is also discussed.