Manufacturing task data chain-driven production logistics trajectory analysis and optimization decision making method

Production logistics(PL)is considered as a critical factor that affects the efficiency and cost of production operations in discrete manufacturing systems.To effectively utilize manufacturing big data to improve PL efficiency and promote job shop floor economic benefits,this study proposes a PL trajectory analysis and optimization decision making method driven by a manufacturing task data chain(MTDC).First,the manufacturing task chain(MTC)is defined to characterize the discrete production process of a product.To handle manufacturing big data,the MTC data paradigm is designed,and the MTDC is established.Then,the logistics trajectory model is presented,where the various types of logistics trajectories are extracted using the MTC as the search engine for the MTDC.Based on this,a logistics efficiency evaluation indicator system is proposed to support the optimization decision making for the PL.Finally,a case study is applied to verify the proposed method,and the method determines the PL optimization decisions for PL efficiency without changing the layout and workshop equipment,which can assist managers in implementing the optimization decisions.

Scheduling optimization of task allocation in integrated manufacturing system based on task decomposition

How to deal with the collaboration between task decomposition and task scheduling is the key problem of the integrated manufacturing system for complex products. With the development of manufacturing technology, we can probe a new way to solve this problem. Firstly, a new method for task granularity quantitative analysis is put forward, which can precisely evaluate the task granularity of complex product cooperation workflow in the integrated manufacturing system, on the above basis; this method is used to guide the coarse-grained task decomposition and recombine the subtasks with low cohesion coefficient. Then, a multi-objective optimieation model and an algorithm are set up for the scheduling optimization of task scheduling. Finally, the application feasibility of the model and algorithm is ultimately validated through an application case study.

Multilevel manufacturing system of virtual enterprise based on manufacturing grid and strategies for member enterprise selection and task assignment

In order to improve efficiency of virtual enterprise, a manufacturing grid and multilevel manufacturing system of virtual enterprise is built up. When selecting member enterprises and task assignment based on the manufacturing grid, key activities are assigned to the suitable critical member enterprises by task decomposition, enterprise node searching and characteristic matching of manufacturing resources according to the characteristic matching strategy. By task merger, some ordinary activities are merged with corresponding key activities and assigned to corresponding critical member enterprises. However, the other ordinary activities are assigned to the related ordinary member enterprises with enterprise node searching and characteristic matching of manufacturing resources. Finally, an example of developing the artificial hip joint in the virtual enterprise is used to demonstrate that efficiency of the virtual enterprise is improved by using the manufacturing grid and the proposed strategies for member enterprise selection and task assignment.