The Perrego algorithm: a flexible machine-component grouping algorithm based on group technology techniques

1995 ◽  
Vol 33 (6) ◽  
pp. 1709-1721 ◽  
Author(s):  
T. A. PERREGO ◽  
H. C. PETERSEN ◽  
W. F. HAHN
2014 ◽  
Vol 933 ◽  
pp. 97-105
Author(s):  
Hassan Mroue ◽  
Thien My Dao

A new algorithm is presented in order to search for the optimal solution of the manufacturing and fractional cell formation problem. In addition, this paper introduces a new toolkit, which is used to search for the various candidate solutions in a periodic and a waving (diversified) manner. The toolkit consists of 15 tools that play a major role in speeding up the obtainment of the final solution as well as in increasing its efficiency. The application of the binary digit grouping algorithm leads to the creation of manufacturing cells according to the concept of group technology. The nonzero entries, which remain outside the manufacturing cells, are called exceptional elements. When a lot of such elements is obtained, an additional cell called fractional (or remainder) cell may be formed; the aim of which is to reduce their number. This algorithm was tested by using illustrative examples taken from the literature and succeeded to give better or at least similar results when compared to those of other well-known algorithms.


2014 ◽  
Vol 1 (2) ◽  
pp. 140-151 ◽  
Author(s):  
Youn-Kyoung Joung ◽  
Sang Do Noh

Abstract Storing, and the loading and unloading of materials at production sites in the manufacturing sector for mass production is a critical problem that affects various aspects: the layout of the factory, line-side space, logistics, workers' work paths and ease of work, automatic procurement of components, and transfer and supply. Traditionally, the nesting problem has been an issue to improve the efficiency of raw materials; further, research into mainly 2D optimization has progressed. Also, recently, research into the expanded usage of 3D models to implement packing optimization has been actively carried out. Nevertheless, packing algorithms using 3D models are not widely used in practice, due to the large decrease in efficiency, owing to the complexity and excessive computational time. In this paper, the problem of efficiently loading and unloading freeform 3D objects into a given container has been solved, by considering the 3D form, ease of loading and unloading, and packing density. For this reason, a Group Packing Approach for workers has been developed, by using analyzed truck packing work patterns and Group Technology, which is to enhance the efficiency of storage in the manufacturing sector. Also, an algorithm for 3D packing has been developed, and implemented in a commercial 3D CAD modeling system. The 3D packing method consists of a grouping algorithm, a sequencing algorithm, an orientating algorithm, and a loading algorithm. These algorithms concern the respective aspects: the packing order, orientation decisions of parts, collision checking among parts and processing, position decisions of parts, efficiency verification, and loading and unloading simulation. Storage optimization and examination of the ease of loading and unloading are possible, and various kinds of engineering analysis, such as work performance analysis, are facilitated through the intelligent 3D packing method developed in this paper, by using the results of the 3D model.


1973 ◽  
Vol 52 (3) ◽  
pp. 81 ◽  
Author(s):  
W.T. Whitfield
Keyword(s):  

1980 ◽  
Vol 59 (2) ◽  
pp. 51 ◽  
Author(s):  
Barry Dale ◽  
Philip Willey
Keyword(s):  

Sign in / Sign up

Export Citation Format

Share Document