scholarly journals Layout Design in Group Technology Using Cellular Manufacturing System

2020 ◽  
Vol 1569 ◽  
pp. 032012
Author(s):  
D Ernawati ◽  
N Rahmawati ◽  
E Pudji ◽  
NK Sari ◽  
A Wianto
Keyword(s):  
Manufacturing System ◽  
Group Technology ◽  
Cellular Manufacturing ◽  
Layout Design ◽  
Cellular Manufacturing System

Two-Stage Design for Cellular Manufacturing System

2012 ◽  
Vol 220-223 ◽  
pp. 137-140
Author(s):  
Ling Gou ◽  
Cong Lu ◽  
Jun Feng Fei
Keyword(s):  
Genetic Algorithm ◽  
Manufacturing System ◽  
Cellular Manufacturing ◽  
Cell Formation ◽  
Layout Design ◽  
Cellular Manufacturing System ◽  
Two Stage ◽  
Stage Design ◽  
Second Stage ◽  
Handling Cost

Cell formation（CF）and cellular layout design are the two main steps in designing a cellular manufacturing system (CMS). Efficient grouping is the prerequisite of a successful Cellular Manufacturing, and it is too hard to obtain a perfect consequence of CF and layout simultaneously. In this paper, a two-stage strategy is used to solve CF problem and layout sequentially. At the first stage, the cells are formed based on the part-machine clustering results obtained through the genetic algorithm, to get the initial inter-cell layout. At the second stage, the genetic algorithm is used to improve the solution obtained, to minimize the handling cost and maximize the utility of the machines.

scholarly journals Plant layout design and assessment consideration of cellular manufacturing system via G.A

2017 ◽  
Vol 9 (2) ◽  
Author(s):  
Dhurgham Aiham Kadhim Alshakarchi ◽  
Maytham Salman azeez
Keyword(s):  
Genetic Algorithms ◽  
Life Cycle ◽  
Product Life Cycle ◽  
Manufacturing System ◽  
Cellular Manufacturing ◽  
Layout Design ◽  
Cellular Manufacturing System ◽  
Plant Layout ◽  
Product Life ◽  
Fast Change

           Cellular manufacturing  is a wide world and many study and researches discussed are concerning  with  it because of the large demand in market and wheel technology push the scientist to find tools that can stand with this fast change in demand according specific market , so that they invent the best way to deal with optimization purpose. In this research the dealing with cellular  optimization in such a way that can be manageable by AI and using  type of AI that named natural optimization .  The applying of genetic algorithms  was carried out on factory of electrical motor also all data was taken from the factory which is depend on the position and sequence of operations took place in the factory . The theory  in this field were also taking in  consideration and the applications was carried out . the research deals with problem in two way  theoretically  that can take in consideration  the positions of machines inside the plant and its equations that covers with some constraints   and the secondly  the routing of part during product life cycle and execute results and applying it on factory configuration . There are multi solutions (results ) in the research for the problem that can achieve the flexibility , simplicity  and also desired distance

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