Proposed Production Layout Using Total Closeness Rating (Tcr) Method and Corelap Algorithm in Cv. Faris Collections


Usulan Layout Produksi dengan Menggunakan Metode Total Closeness Rating (Tcr) Dan Algoritma Corelap di Cv. Faris Collections


  • (1) * Muhammad Rizky Fauzi            Universitas Muhammadiyah Sidoarjo  
            Indonesia

  • (2)  Athika Sidhi Cahyana            Universitas Muhammadiyah Sidoarjo  
            Indonesia

    (*) Corresponding Author

Abstract

Unplanned layout of the facility and not paying attention to the distance will be able to experience an increase in time during the production process. From the results of observations that have been made at CV. Faris Collections needs to improve the facility layout in department E, namely the grouping of fabrics, due to frequent piling up of fabrics. Lack of utilization of area and distance of material transfer that is too long for department I, namely cloth embroidery. This proposed layout planning uses the TCR method, which is the calculation of the closest associated distance to each production department, which is described in the ARC which requires the relationship between each activity in the area of ​​production so that it fully refers to the TCR calculation results. This planning also uses the CORELAP Algorithm in order to obtain a proposed layout plan that is able to convert qualitative value data into quantitative data. The results of the CORELAP Algorithm are the main basis for knowing the initial lay-out coordinates and the proposed layout, and the coordinate values ​​will be entered into the WinQSB software to determine the level of efficiency. The efficiency level of the CORELAP Algorithm is 9%, and the efficiency of changes between departmental distances in the initial layout and proposed layout is 18%.

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References

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Published
2021-07-08
 
How to Cite
[1]
M. R. Fauzi and A. S. Cahyana, “Proposed Production Layout Using Total Closeness Rating (Tcr) Method and Corelap Algorithm in Cv. Faris Collections”, PELS, vol. 1, no. 2, Jul. 2021.