Job Scheduling Management Research of Intelligent Manufacturing Based on the Internet of Things

In-depth and detailed requirements of intelligent manufacturing are analyzed for the virtual cloud enterprise, and it is explained that the process of the main task of job scheduling about intelligent manufacturing based on Internet of things. It is concluded that the relationship and associations among parameters after the research of the physical model and object model based on Internet of things. Parameters include the process of production and basic information data. Different orders are analyzed and compared for job scheduling condition, then it is concluded that to get the specific process of qualified products. The detailed analysis and disassemble program are carried on back business of work ticket and splitting business, which makes the management more rationalization and improves the efficiency of intelligent manufacturing. Finally the scheduling of query is carried on and other business query functions have been implemented, which is the solar panels of a factory production. The system of job scheduling is more reasonable and more efficient in scheduling management, which saves time and resources for the enterprise. This research could be applied in the job scheduling of cloud virtual enterprise.

[1]  Chao Li,et al.  Fuxi: a Fault-Tolerant Resource Management and Job Scheduling System at Internet Scale , 2014, Proc. VLDB Endow..

[2]  Khaled Ghédira,et al.  A Holonic Multiagent Model Based on a Combined Genetic Algorithm─Tabu Search for the Flexible Job Shop Scheduling Problem , 2015, PAAMS.

[3]  Javad Akbari Torkestani.  A new approach to the job scheduling problem in computational grids , 2011, Cluster Computing.

[4]  Marco Taisch,et al.  Multi-objective genetic algorithm for energy-efficient job shop scheduling , 2015 .

[5]  Kuan Yew Wong,et al.  An imperialist competitive algorithm for the job shop scheduling problems , 2014, 2014 IEEE International Conference on Industrial Engineering and Engineering Management.

[6]  Ming Xu.  Research of Task Scheduling of Ad hoc Cluster Computing Based on Genetic Algorithm , 2009, 2009 International Conference on Wireless Networks and Information Systems.

[7]  Gaurav Sharma,et al.  Modified min-min heuristic for job scheduling based on QoS in Grid environment , 2014, 2013 2nd International Conference on Information Management in the Knowledge Economy.

[8]  Giuseppe Paletta,et al.  Partial Solutions and MultiFit Algorithm for Multiprocessor Scheduling , 2015, J. Math. Model. Algorithms Oper. Res..

[9]  Yuanguo Zhu,et al.  Chance-constrained model for uncertain job shop scheduling problem , 2016, Soft Comput..

[10]  Pruet Boonma,et al.  A trail-based approach for job scheduling in distributed systems with workflows , 2014, Ninth International Conference on Digital Information Management (ICDIM 2014).

[11]  Lucio Grandinetti,et al.  A multi-dimensional job scheduling , 2016, Future Gener. Comput. Syst..

[12]  Sateesh Kumar Pradhan,et al.  A heuristic job scheduling algorithm for minimizing the waiting time variance , 2015, 2015 International Conference on Futuristic Trends on Computational Analysis and Knowledge Management (ABLAZE).

[13]  Donald K. Friesen,et al.  Scheduling on uniform processors with at most one downtime on each machine , 2015, Discret. Optim..