Planning Problem In Flexible Manufacturing Systems

Flexible manufacturing systems or FMSs aim to combine the flow line's productivity along with the flow line's productivity along with the job's flexibility shops to attain extremely versatile manufacturing units realizing high operational efficiencies. The decision making in Flexible manufacturing systems has been characterized into four stages that are control, scheduling, planning and design. The planning stage of FMS is categorized into five sub-problems as:

(a)    Part allocation or part type selection

(b)   Machine grouping

(c)    Production ratio resolve

(d)   Pallet-fixture allocation

(e)   Machine loading

If there is no machine's grouping, the pallet fixture assigned is avoided, and the production volume is fixed as like non-split Table lot sizes. Planning after that only requires addressing the given two problems as:

(a)    Part Allocation or Type Selection,

(b)   Machine Loading.

The part type selection problem occupies the choice of a subset of part type for immediate production whereas the machine loading assigned the required and operation tools of the chosen part types in between the machine groups objected to the technological and capability constraints of the Flexible manufacturing systems. In general, be on the neural network's applications to decision making problems in Flexible manufacturing systems and mainly on machine loading problem in Flexible manufacturing systems. Loading decisions acts like an important link in among the strategic and operational stage decisions in manufacturing. The solution and formulation methodologies for different scenarios and parameters combinations concerning to the loading problem in Flexible manufacturing systems have been extensively studied by the researchers and practitioners because of its inherent complexity and numerous solution methodologies have been planned for efficiently solving it.