# Review of Responsiveness and Sustainable Concepts in Cellular Manufacturing Systems
## 4 Energy Consumption  
The goal of reducing CO2 emissions and energy costs drives the production systems to improve their energy efficiency and to adopt renewable energy sources. Therefore, it is necessary to adopt new models and approaches in manufacturing systems to include the energy issues. The energy efficiency in manufacturing systems has been deeply analyzed in a recent work by [PERSON] and [PERSON] [40]. In their work, the authors proposed a review of the literature on energy efficiency and sustainability deepening the different typologies of manufacturing systems. They focused also on cellular manufacturing; the most significant works analyzed by the authors are reported herein. The layout designs of cellular manufacturing systems has been studied by [PERSON] et al. [41; 42]; in their first work, they presented a mathematical model considering as objective functions the total cost and the total energy loss minimization; in the second work proposed, the authors considered the minimization of total production waste as a second objective, which included several typologies of waste, such as chemical, energy, raw material, and greenhouse gas emission. In the context of cellular manufacturing systems, the energy issue has been considered also in [43]. Indeed, the authors evaluated the machines and the material handling electricity costs, and assumed it as value adding cost to the work in process. The cell formation has been obtained, in order to minimize the value-added work in process, using a genetic algorithm and discrete event simulation. [PERSON] and [PERSON] [44] proposed a nonlinear mathematical model to minimize the energy consumed in the operation of the machines and the energy for the transportation of the parts in cellular manufacturing systems. An algorithm based on a simulated annealing metaheuristic algorithm was developed for the solution of the mathematical model. [PERSON] and [PERSON] [45] studied a virtual cellular manufacturing system integrated with the energy consumption levels. The model proposed allowed the managers to choose the consumption energy level considering the back orders of the manufacturing system. Then, the trade-off between energy and backorder cost is pursued. [PERSON] and [PERSON] [46] proposed a NSGA based algorithm for minimizing the makespan and flowtime, as well as energy, for cellular manufacturing systems. The numerical results highlighted that there is a significant potential for improving the schedule of operations by considering energy consumption and reducing the idle time of the machines. [PERSON] et al. [47] developed a model to support virtual reconfiguration in cellular manufacturing systems that includes the group workstations, scheduling virtual cells, and selecting energy consumption levels. The complexity of the mathematical model developed needed a metaheuristics algorithm to solve this problem. A mathematical model that minimizes the costs linked to material handling and machine rearrangement and minimizes electricity consumption of the automated guided vehicles has been provided by [PERSON] et al. [48]. A cellular manufacturing layout, that allows the reduction of material handling cost and energy consumption, has been provided,solving the proposed mathematical model with a simulated annealing-based solution methodology. [PERSON] et al. [49] developed a mixed-integer program to design cellular manufacturing systems considering energy consumption. The machines are assumed to be capable of processing operations with different energy consumption rates and processing times. To solve the mathematical problem, they proposed the combination of a genetic algorithm and a simulated annealing algorithm. [PERSON] et al. [50] studied the scheduling problem in cellular manufacturing systems to maximize the profit, considering the revenues earned from sales, as well as energy consumption costs and order tardiness penalties.