Aggregate planning determines production levels, inventory levels, and capacity levels over a multi-period time horizon, such as 3-18 months. The goal is to maximize profit by balancing costs of capacity, inventory, and stockouts. Key strategies include chase, which varies capacity; time flexibility, which varies workforce hours; and level, which maintains stable capacity and output. An aggregate plan specifies parameters like production rates and inventory levels to optimize supply chain performance over the planning horizon.
Aggregate planning is an operational activity that does an aggregate plan for the production process, in advance of 6 to 18 months, to give an idea to management as to what quantity of materials and other resources are to be procured and when, so that the total cost of operations of the organization is kept to the minimum over that period.
This presentation is originally created by me when I reported Aggregate Planning during my Production and Operations Management class. I hope this can help you. :))
Aggregate planning is an operational activity that does an aggregate plan for the production process, in advance of 6 to 18 months, to give an idea to management as to what quantity of materials and other resources are to be procured and when, so that the total cost of operations of the organization is kept to the minimum over that period.
This presentation is originally created by me when I reported Aggregate Planning during my Production and Operations Management class. I hope this can help you. :))
Aggregate planning using transportation method a case study in cable industryijmvsc
Aggregate planning is an analytical tool that proposes a strategy to meet demand according to the
capacity constraints. In this paper, aggregate planning strategies are discussed and a special structure of
transportation model is investigated for the aggregate planning purpose of “Bangladesh Cable Shilpa
Ltd, Khulna”. For this transportation problem, all the unit costs, supplies, demands & other values are
taken from a case study. The forecasting demand values are determined using Single Exponential
Smoothing Forecasting technique. Transportation model & the Transportation algorithm is discussed in
this paper. A real life unbalanced transportation problem is discussed and solved to bring the most
efficient technique of reducing transportation and storage cost. Vogel Approximation Method (VAM)
algorithm is also discussed & used to determine the starting solution of the transportation model. Finally,
TORA software is used to find the optimum cost by using transportation method.
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