Diverse task scheduling for individualized requirements in cloud manufacturing

ABSTRACT

Cloud manufacturing (CMfg) has emerged as a new manufacturing paradigm that provides ubiquitous, on-demand manufacturing services to customers through network and CMfg platforms. In CMfg system, task scheduling as an important means of finding suitable services for specific manufacturing tasks plays a key role in enhancing the system performance. Customers’ requirements in CMfg are highly individualized, which leads to diverse manufacturing tasks in terms of execution flows and users’ preferences. We focus on diverse manufacturing tasks and aim to address their scheduling issue in CMfg. First of all, a mathematical model of task scheduling is built based on analysis of the scheduling process in CMfg. To solve this scheduling problem, we propose a scheduling method aiming for diverse tasks, which enables each service demander to obtain desired manufacturing services. The candidate service sets are generated according to subtask directed graphs. An improved genetic algorithm is applied to searching for optimal task scheduling solutions. The effectiveness of the scheduling method proposed is verified by a case study with individualized customers’ requirements. The results indicate that the proposed task scheduling method is able to achieve better performance than some usual algorithms such as simulated annealing and pattern search.

KEYWORDS:

• Cloud manufacturing
• individualized requirement
• diverse task
• scheduling
• genetic algorithm

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

The research is supported by the National High-Tech Research and Development Plan of China under Grant No. 2015AA042101, the National Natural Science Foundation of China under Grant No. 61374199, the Natural Science Foundation of Beijing Municipality No. 4142031, and the Fund of State Key Laboratory of Intelligent Manufacturing System Technology in China.