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Aggregate planning is a method for developing an overall manufacturing plan that ensures uninterrupted production at a facility. Aggregate production planning typically is applied to a 3- to 18-month period. Aggregate planning covers all production activities at a facility (or for large enterprises, across several facilities), not just individual production runs or the manufacture of individual products. Because of this, aggregate production planning helps manufacturers optimize resource utilization despite significant variations in demand for individual products, which arise from changes in customer orders, supply chain dynamics, and other elements.
For manufacturers that are using digital systems in a manufacturing operations management (MOM) ecosystem, aggregate planning is a capability of an advanced planning and scheduling (APS) system. As a methodology, aggregate production planning can be performed using paper-based, spreadsheet or homegrown software solutions. However, the growing complexity of products, production operations, and supply chains have substantially increased the variety and volume of information to be considered in aggregate planning. Therefore, manufacturers are trending toward greater employment of APS systems for their aggregate planning needs.
The goal of aggregate planning is to minimize operating costs by matching production demand with production capacity. An aggregate plan specifies what materials and other resources are needed and when they should be procured to minimize cost. The ideal outcome of aggregate planning is to maximize a facility’s productivity at the lowest possible cost to the manufacturer.
With the primary goals of minimizing costs and maximizing profits, the strategic objectives of aggregate planning include:
Minimize inventory investment – Aggregate planning software optimally balances efforts to minimize the cost of inventory management and storage with efforts to ensure sufficient inventory to meet both independent and dependent demands through material resource planning.
Minimize workforce demand and fluctuation – Aggregate planning software uses data from demand forecasts and material resource planning to calculate an optimal workforce plan – one that balances the cost of onboarding/layoffs due to workforce fluctuation with the cost of worker idle time and/or overtime.
Maximize production rates while minimizing fluctuation – Aggregate planning software analyzes production capacity versus demand forecasts to maximize the overall production rate while avoiding periods of idle capacity.
Maximize facility and production equipment utilization – Aggregate planning software accounts for available production equipment and facilities, and targets maximum utilization over the aggregate planning period.
To achieve these objectives, aggregate planning software may employ one of two approaches, or a combination of both. The chase approach attempts to match production capacity with demand. With this approach, a manufacturer adjusts resource procurement and availability to keep up with fluctuations in customer (or make-to-stock) orders. This approach enables a manufacturer to minimize inventory levels and maximize resource utilization, but the manufacturer must contend with costs associated with adjustments to capacity: workforce onboarding and layoffs or underutilized floor space, for example.
The level approach to aggregate production planning, on the other hand, avoids the cost of adjustments by keeping production rates steady. This means that the manufacturer builds up inventory at times of lower demand to be able to fulfill orders during periods of peak demand. Alternatively, the manufacturer may maintain a steady level of workforce and production capacity and ramp up productivity during periods of high demand. In either case, the level approach encounters costs associated with inventory management, idle capacity, workforce idle time and/or overtime, and other expenses associated with fluctuating utilization of resources.
By fulfilling the strategic objectives of aggregate planning, a manufacturer can balance short- and long-term production demands and optimize productivity and profits.