TY - JOUR
T1 - Research on resources optimisation deployment model and algorithm for collaborative manufacturing process
AU - Changfeng, Y.
AU - Dinghua, Z.
AU - Wenli, P.
AU - Kun, B.
PY - 2006/8/15
Y1 - 2006/8/15
N2 - Agility is the competitive advantage in the global manufacturing environment. It is believed that agility can be realised by networked manufacturing resource optimisation deployment. However, this is a challenge to us now. To solve this question, logical manufacturing unit and logical manufacturing process are proposed to decompose and model the networked manufacturing task, and networked manufacturing resources are organised and modelled based on physical manufacturing unit. During the deployment of manufacturing resources to the task, many factors should be taken into consideration. Of these, manufacturing cost, time and quality are the most important factors. In this paper, before these factors are considered, networked manufacturing resources pre-deployment is carried out to find the candidate manufacturing resources on the basis of manufacturing abilities. Then, resources optimisation deployment is modelled as a multi-objectives optimisation. This optimisation problem is solved based on genetic algorithm after transforming the multi-objectives optimisation problem to a single objectives optimisation problem. Although we may not find the optimal solution for the problem by genetic algorithm, the better and feasible solution is produced. Thus, this algorithm is efficient and can be applicable to practical problem. At last, an illustrative example is presented to show the application of the proposed algorithm.
AB - Agility is the competitive advantage in the global manufacturing environment. It is believed that agility can be realised by networked manufacturing resource optimisation deployment. However, this is a challenge to us now. To solve this question, logical manufacturing unit and logical manufacturing process are proposed to decompose and model the networked manufacturing task, and networked manufacturing resources are organised and modelled based on physical manufacturing unit. During the deployment of manufacturing resources to the task, many factors should be taken into consideration. Of these, manufacturing cost, time and quality are the most important factors. In this paper, before these factors are considered, networked manufacturing resources pre-deployment is carried out to find the candidate manufacturing resources on the basis of manufacturing abilities. Then, resources optimisation deployment is modelled as a multi-objectives optimisation. This optimisation problem is solved based on genetic algorithm after transforming the multi-objectives optimisation problem to a single objectives optimisation problem. Although we may not find the optimal solution for the problem by genetic algorithm, the better and feasible solution is produced. Thus, this algorithm is efficient and can be applicable to practical problem. At last, an illustrative example is presented to show the application of the proposed algorithm.
KW - Executive manufacturing process
KW - Genetic algorithm
KW - Logical manufacturing process
KW - Logical manufacturing unit
KW - Physical manufacturing unit
KW - Resources optimising deployment
UR - http://www.scopus.com/inward/record.url?scp=33745123677&partnerID=8YFLogxK
U2 - 10.1080/00207540500478520
DO - 10.1080/00207540500478520
M3 - 文章
AN - SCOPUS:33745123677
SN - 0020-7543
VL - 44
SP - 3279
EP - 3301
JO - International Journal of Production Research
JF - International Journal of Production Research
IS - 16
ER -