Arrangement of Machines Under Spatial Constraint by Using a Novel Algorithm

Abstract

Sustainable operations is one of the goals of a company manager. Cost is a major consideration. Plant space and material handling greatly affect cost. Factories reduce material handling and part movement times by using traditional group technology or cellular manufacturing to sort parts into part families and machines into machine cells. Machines have different work space requirements, and this constraint must be considered in the plant layout. However, studies in this field have seldom included spatial constraints when considering machine work spaces. In a real factory, space is often limited, especially in countries where land is expensive. Therefore, it is vital to effectively use the available space. Most cell formation algorithms focus on part families, but a robust cluster algorithm is proposed in this study to solve the spatial constraint problem. The algorithm forms machine cells and determines part families simultaneously. Three numerical examples are given to demonstrate the implementation of the algorithm, and the proposed algorithm is compared with other algorithms. While traditional GT cannot solve the presented problem, the proposed algorithm works.

Keywords

• Group technology
• cellular manufacturing
• spatial constraint
• machine layout
• modified closeness matrix