Design technology for layout

الملخص EN

Layout decisions entail determining the placement of departments, work groups within the departments, workstations, machines, and stock-holding points within a production facility.

The objective is to arrange these elements in a way that ensures a smooth work flow (in a factory) or a particular traffic pattern (in a service organization).

In our treatment of layout, we examine how layouts are developed under various formats (or work-flow structures).

Our emphasis is on quantitative techniques, but we also show Examples (case study in The General Company For Cars Industry In Hilla) of how qualitative factors are important in the design of the layout.

In manufacturing facilities are covered in this technical research.

Design Technology will be employed to assist operation technology management in computer-aided process factory layout design.

In this research we deal Design Technology Systems or (Techniques) are "Craft-Aldep-and Corelap) In the past, there were many techniques to design industrial plant layout.

The most popular was CRAFT Computerize Relative Allocation Facilities Technique.

However, the result from CRAFT was limited.

The result of design showed only minimum total transfer cost between departments.

As a result, the simulation technique is added to plant layout design to show more information about the design such as total time in system, waiting time, and utilization.

And focus in research on the CRAFT that gives a heuristic method that uses a trip matrix including materials flow, transportation costs, and an initial block layout, and make a series of paired exchange of departments to find a better block plan with latest costs, to a chive strategic importance of factory layout through.

In this research we have proposed a semi-heuristic optimization algorithm for designing optimal plant layouts in process-focused manufacturing / service facilities.

Our proposed algorithm marries the wellknown CRAFT with the Hungarian assignment algorithm.

Being a semi-heuristic search, our algorithm is likely to be more efficient in terms of computer CPU engagement time as it tends to converge on the global optimum faster than the traditional CRAFT algorithm-a pure heuristic.

We also present a numerical illustration of our algorithm.