## 2 Literature Review and Research Gap
[42] developed a multiobjective planning model for expansion of a network with distributed energy using the immune genetic algorithm (I-GA) to minimize cost and carbon emission. [PERSON] et al. [43] determined the best alternative among renewable energy resources using a fuzzy-based multi-criteria tool and an analytical hierarchical process (AHP). [PERSON] et al. [44] determined the electrical attributes of photovoltaic solar cells to obtain the corresponding maximum power point using GA. [PERSON] et al. [45] used optimization techniques to maximize the profit of water replenishment. A few researchers considered carbon footprint in supply chain models for manufacturers. [PERSON] et al. [46] optimized a supply chain to minimize the carbon footprint of the manufacturer and retailer. In this direction, [PERSON] and [PERSON] [47] projected a grey theory model that considers environmental impact in terms of tax in production planning to make decisions in uncertain conditions. [PERSON] et al. [48] develop a multiobjective model for evaluating the association of costs with environmental guidelines in green supply chain. [PERSON] et al. (2016) [49] proposed an electricity monitoring system considering multiobjective linear programming and carbon footprint and using electricity as a source of energy. The authors studied on automobile parts manufacturing to minimize the cost of manufacturing, carbon footprint from production and cost of electricity. The major sources of energy were electricity, diesel, and gasoline. Table 2 shows the contribution of previous authors to provide an opportunity for policy makers to save energy and minimize carbon footprint. \begin{table}
\begin{tabular}{c c c c c c c} \hline \hline
**Authors** & **Energy** & **Cost** & **Greenhouse Gases** & **Minimum Quantity** & **Mathematical** & **Imperfect** \\  & **Resources** & **Function** & **Emissions** & **Lubrication** & **Techniques** & **Items** \\ \hline [PERSON] et al. & Non-renewable & Total cost & Emission from & & Non-dominated sorting & \\ (2005) [42] & energy & of system & grid & & genetic algorithm & \\ [PERSON] et al. & Renewable & & & & Fuzzy analytical & \\ (2009) [43] & energy & & & & hierarchical process & \\ [PERSON] et al. & Renewable & Cost of & & Genetic & \\ (2010) [44] & energy & energy & & algorithm & \\ [PERSON] and & & Profit & & Analytical & \\ [PERSON] (2011) [40] & & & technique & & \\ [PERSON] et al. & & Total cost of & CO\({}_{2}\) & & Normalized & \\ (2011) [48] & & production & & constraint method & \\ [PERSON] et al. & Non-renewable & Total cost of & CO\({}_{2}\) & & Fuzzy multiobjective & \\ (2016) [49] & energy & production & & goal programming & \\ This paper & Renewable & Cost of Photovoltaic & CO\({}_{2}\) & Yes & Weighted goal & \\  & (PV technology) & technology & & & programming & and scrap \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Author contribution table. However, previous studies did not quantify the effect of renewable energy on total cost and carbon emissions in a manufacturing system. This paper extends the model of [PERSON] et al. [49] to develop a multiobjective goal-oriented model. The main contribution of the paper is the incorporation of renewable solar energy, carbon cost (tax), and minimum quantity lubrication at process level in the production of the automobile part industry integrated with suppliers in supply chain. The concept of the carbon tax and levelized cost (LCOE) of solar energy showed positive economic advantages to industry experts and practitioners to provide a sustainable life in supply chain management. The tangible results are generated to trade off the cost of production in favor of minimum carbon emissions for a sustainable manufacturing. Such a sustainable manufacturing environment requires efforts/optimization in product design, manufacturing, and supply chain. A scenario is also considered where imperfect items are produced by the suppliers in the supply chain to make the given model more realistic.