An assignment model for the part-families problem in group technology

Purpose Reconfigurable machines tools (RMTs) are gaining momentum as the new solutions to customised products in the manufacturing world. The driving force, among others, behind these machines is the part envelope and the part family of products that they can produce. The purpose of this paper is to propose a new class of RMT known as a reconfigurable guillotine shear and bending press machine (RGS&BPM). A part family of products that this machine can produce is developed using hierarchical clustering methodologies. The development of these part families is guided by the relationship of the parts in the family in terms of complexity and geometry. Design/methodology/approach Part families cannot be developed in isolation, but that process has to incorporate the machine modules used in the reconfiguration process for producing the parts. Literature was reviewed, and group technology principles explored, to develop a concept that can be used to develop the part families. Matrices were manipulated to generate part families, and this resulted in the development of a dendrogram of six possible part families. A software with a graphic user interface for manipulation was also developed to help generate part families and machine modules. The developed concept will assist in the development of a machine by first developing the part family of products and machine modules required in the variable production process. Findings The developed concepts assist in the development of a machine by first developing the part family of products and machine modules required in the variable production process. The development of part families for the RGS&BPM is key to developing the machine work envelope and modules to carry out the work. This work has been presented to demonstrate the importance of machine development in conjunction with a part family of products that the machine will produce. The paper develops an approach to manufacturing where part families of products are developed prior to developing the machine. The families of products are then used to develop modules that enable the manufacture of the parts and subsequently the size of the machine. Research limitations/implications The research was limited to the development of part families for a new RGS&BPM, which is still under development. Practical implications The study reflects the development of reconfigurable machines as a solution to manufacturing challenges in terms of group technology approaches adopted in the design phase. It also highlights the significance of the concepts in the reconfigurable machine tool design. The part families define the machine work envelop and its reconfiguration capability. Social implications The success of the research will usher an alternative to smaller players in sheet metal work. It will contribute to the easy development of the machine that will bridge the high cost of machine tools. Originality/value The study contributes to the new approach in sheet metal manufacturing where dedicated machines may be substituted by a highly flexible reconfigurable machine that has a dual operation, making the investment for small to medium enterprises affordable. It also contributes to the body of knowledge in reconfigurable machine development and the framework for such activities, especially in developing countries.

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A New Approach of Group Technology Part Families Optimization

CIRP Annals ◽

10.1016/s0007-8506(07)62245-8 ◽

1994 ◽

Vol 43 (1) ◽

pp. 425-428 ◽

Cited By ~ 16

Author(s):

K.K.B. Hon ◽

H. Chi

Keyword(s):

Group Technology ◽

New Approach ◽

Part Families

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Learning group-technology part families from solid models by parallel distributed processing

The International Journal of Advanced Manufacturing Technology ◽

10.1007/bf02601577 ◽

1992 ◽

Vol 7 (2) ◽

pp. 109-118 ◽

Cited By ~ 15

Author(s):

Y. B. Moon ◽

U. Roy

Keyword(s):

Group Technology ◽

Distributed Processing ◽

Parallel Distributed Processing ◽

Learning Group ◽

Part Families ◽

Solid Models

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School bus routing problem considering affinity among children

Decision Science Letters ◽

10.5267/j.dsl.2021.5.002 ◽

2021 ◽

Vol 10 (4) ◽

pp. 535-548 ◽

Cited By ~ 1

Author(s):

Juan Pablo Orejuela Cabrera ◽

Milton Alexander Londoño ◽

Vivian Lorena Chud Pantoja

Keyword(s):

Assignment Problem ◽

Group Technology ◽

Quadratic Assignment Problem ◽

Point Of View ◽

Quadratic Assignment ◽

School Bus ◽

Routing Problem ◽

Bus Routing ◽

Assignment Model ◽

Two Stages

School bus routing problem is widely studied, however, social elements such as the interaction between children traveling on the same route have not been considered so far. In this way, this article has as its main objective to propose a methodology to solve the school bus routing problem, including affinity as a strategy to increase positive interrelationships between children, and with this, support in bullying situations during school trips. The methodology includes two stages, assigning children to vehicles considering affinities and defining vehicle routes. The main contribution is the consideration of affinity in the process of forming the groups of children that will be taken on the bus, evidencing a balance in the affinity of the groups. Additionally, from the methodological point of view, the integration of a modified group technology algorithm and a new assignment model are proposed that simplify the classic quadratic assignment problem. Consideration of affinity in school bus routing generates benefits from a social point of view.

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A Neural Network-Based Algorithm for Group Technology

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.717.533 ◽

2013 ◽

Vol 717 ◽

pp. 533-537

Author(s):

Ki Seok Choi

Keyword(s):

Neural Network ◽

Group Technology ◽

Cellular Manufacturing ◽

Similarity Coefficients ◽

Part Families ◽

Grouping Efficiency ◽

Machine Cell ◽

Grouping Efficacy

In this paper, we propose a neural network-based algorithm for grouping machine and parts in cellular manufacturing. For grouping machines, we develop similarity coefficients which take into account both similarity and dissimilarity between machines. The machine cells are formed by an algorithm which is based on the maximum neural network. Another algorithm is used to find the part families associated with each machine cell. When compared with an existing algorithm, our algorithm shows better performance in terms of grouping efficiency and grouping efficacy.

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