Subtasks scheduling of tasks with different structures in cloud manufacturing systems under maintenance policy and focusing on logistics, tardiness, and earliness aspects

Cloud manufacturing as an emerging trend has benefited from information technologies such as cloud computing to achieve a customer-oriented paradigm. Over time, factory machines tend to deteriorate slowly, and maintenance planning is implemented to ensure that the machines remain in acceptable condition. When it comes to managing production and maintenance in a system, it’s important to consider them simultaneously. This study presents three models that integrate subtask scheduling and logistics with maintenance policies for three types of task structures (sequential, loop, and parallel) on a cloud platform. These models aim to reduce costs imposed on the cloud manufacturing system, including subtask implementation, logistics between factories in different geographical locations, logistics to the delivery point, preventive maintenance, minimal repairs, and earliness/tardiness. Due to the complexity of the models, a genetic algorithm is developed to solve them. To demonstrate the importance of the main characteristics of the models, three similar models are proposed, in each of which one of the features is removed. Moreover, a sensitivity analysis is conducted to design effective guidelines for cloud manufacturing managers.