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This involves identification of machine cells and part families.
By identifying possible machine cells and part families, it attempts to minimize inter cellular movements.
The first stage is to identify machine cells and part families, which is the essential part of MPGP.
Cell formation (CF) problem is one of the most important decision problems in designing a cellular manufacturing system includes grouping machines into machine cells and parts into part families.
Construction of part families and machine cells, and assignment of part families to respective machine cells is done by optimizing a selected set of performance measures such as material handling cost, machine setup cost, grouping efficacy and exceptional elements (Deep and Singh 2015; Bagheri and Bashiri 2014; Rafiei and Ghodsi 2013).
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Development of a knowledge-based system to support the decision making process is justified by the inability of decision makers to diagnose efficiently many of the malfunctions that arise at machine, cell, and entire system levels during manufacturing.
It promises to reveal the relationships among elements of systems that may include just a few proteins that together perform a defined task or more complex molecular machines, cells and groups of cells, with the goal of understanding their emergent properties [ 3].
This paper presents a linear assignment algorithm for machine-cell and part-family formation for the design of cellular manufacturing systems.
They involve the identification of part families and machine cells so that intercellular movement is minimized and the utilization of the machines within a cell is maximized.
Clustering parts and machines into part families and machine cells is a major decision in the design of cellular manufacturing systems which is defined as cell formation.
Most of them concentrated on distinguishing the part families and machine cells either simultaneously or individually with the objective of minimizing intercellular and intracellular part movements.
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