CAPACITY PLANNING MODEL BASED ON CRITICAL RESOURCES
In term of production planning and control system based on MRP II (Manufacturing Resource Planning), MPS validation is doing by RCCP (Rough Cut Capacity Planning) before the process continue to MRP (Material Requirement Planning). If MPS is unfeasible, then Management should increase capacity or...
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Format: | Theses |
Language: | Indonesia |
Online Access: | https://digilib.itb.ac.id/gdl/view/39686 |
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Institution: | Institut Teknologi Bandung |
Language: | Indonesia |
Summary: | In term of production planning and control system based on MRP II
(Manufacturing Resource Planning), MPS validation is doing by RCCP (Rough Cut
Capacity Planning) before the process continue to MRP (Material Requirement
Planning). If MPS is unfeasible, then Management should increase capacity or
decrease workload that will lead to decreasing demands. In aircraft manufacturing
company, option to decline demand is difficult decision beacause it will not only
impact to the revenue but also to the the company’s credibility.
This research is concerned to capacity planning model based on the critical
resources with study case in PT X, because in accordance with the result of RCCP
in component manufacturing line and the result of critical path analysis in assembly
line show that work station CNC Router, Rolling, rear fuselage assembly for
Product 1, and center fuselage structure assembly for Product 2 are critical in
aircraft manufacturing process. Model developed by using mathematical model
which objective functions is to minimize total cost, consisting cost of process in
critical resources in component manufacturing line, cost of outsourcing, and
penalty cost caused by delay in delivery. The decision variable in the model is the
number of capacity allocation for each aircraft to the critical resources in
component manufacturing line. Solution is produced by using software Lingo and
shows that the MPS is valid by increasing capacity through outsourcing process
543,92 hours for Product 1 and 2.638,58 hours for Product 2. |
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