Lot Size
The lot size is the quantity of identical parts that is combined into a single production or procurement run and manufactured or ordered together without any intermediate changeover. It determines how often you have to set up or reorder and how much stock this builds up in the warehouse.
The lot size is the quantity of identical products or parts that is combined into a single production or procurement run and manufactured or ordered together without any intermediate changeover. A "lot" is thus the smallest coherent batch: instead of making each unit individually, a company bundles several units into one lot and produces or procures them in a single pass. The lot size therefore answers the question "How much at once?" — as opposed to the requirement quantity, which only states how much is needed in total.
Setting the lot size is an economic decision with opposing costs: large lots lower the proportional setup or ordering costs per unit but drive up tied-up capital and inventory costs, because many units are produced before they are needed. Small lots keep stock low and increase flexibility but cause frequent setups. The "optimal lot size" is the point at which the sum of both cost types is lowest. In ERP and PPC systems, the lot-sizing methods stored in the system control how requirements are turned into concrete production and order quantities.
At a glance
- Quantity manufactured or ordered together in one lot without changeover
- Trade-off: high setup/ordering costs per lot vs. high inventory and capital-tie-up costs
- Optimal lot size = minimum of total costs (classically: the EOQ / Andler formula)
- Lot-sizing methods in ERP/MRP translate requirements into concrete order quantities
- Small lots increase flexibility (lot size 1 as the ideal of lean and just-in-time)
How the optimal lot size is determined
The optimal lot size results from balancing two opposing cost types. On one side are the batch-fixed costs — for in-house production the setup costs for preparing the machine, for purchasing the ordering costs for procurement and goods receipt. These costs arise once per lot, regardless of quantity; spread over many units they become smaller per unit. On the other side are the inventory holding costs: the larger the lot, the longer and the higher the stock sits, tying up capital and causing interest, space and handling costs. The goal is the quantity at which the sum of both cost curves reaches its minimum.
Classically, this minimum is calculated with the Andler lot-size formula (also known as the Economic Order Quantity, EOQ). It relates annual demand, the setup or ordering costs per order and the inventory cost rate to one another and delivers a statically optimal quantity. The model is heavily simplified: it assumes constant, known demand, unlimited capacity, no quantity discounts and no fluctuations. In practice the results therefore serve more as guidance; they are supplemented by constraints such as minimum lot sizes, packaging units, shelf lives or available capacity.
Setup costs versus inventory costs
The entire trade-off of the lot size can be condensed into one image: setup costs pull the quantity up, inventory costs pull it down. If setup costs fall — for example through faster changeover using the SMED method — the optimum shifts toward smaller lots. This is exactly where the lean philosophy comes in: anyone who drastically reduces setup times can economically produce in ever smaller lots, in the limiting case in "lot size 1", i.e. order-based single-unit production with no stock build-up.
Lot-sizing methods in material planning
In day-to-day operation the lot size is rarely recalculated for every order; instead it is controlled via lot-sizing methods stored in the system. These define how material requirements planning forms concrete production or order quantities from a series of net requirements. Roughly three families are distinguished: static, period-based and optimizing methods — each with a different balance of computational effort, stock level and flexibility.
Static methods work with fixed rules: the exact requirement quantity (lot-for-lot, lot size = requirement, minimum stock), a fixed lot size, or replenishing up to a maximum stock level. Period-based methods combine all requirements of a time span — say a week or a month — into one lot and thus reduce the number of orders. Optimizing methods such as the part-period balancing method or the Groff method try to determine the cost-minimal grouping dynamically for fluctuating requirements, and are therefore closer to the real demand structure than the rigid Andler formula.
Constraints: minimum, maximum and rounding values
Calculated optima meet hard limits in practice. A minimum lot size ensures that a setup is worthwhile at all; a maximum lot size limits the lot to what a machine, batch or warehouse can hold. Rounding values adjust the quantity to container, pallet or packaging units — what is then ordered or produced is not the awkward optimal quantity, but the next whole multiple. These parameters are maintained per item in the ERP system and are taken into account automatically by the lot-sizing method.
Why the lot size matters economically
The lot size is one of the most effective levers between costs, inventory and delivery capability. It directly determines tied-up capital: large lots fill the warehouse with stock that is only sold or consumed over weeks, while small lots keep capital free and increase inventory turnover. At the same time it determines the utilization of production — every additional lot means another setup and thus time during which the machine is not producing.
The lot size likewise influences flexibility and responsiveness. Anyone producing in large lots is sluggish when it comes to short-term range changes, discontinued variants or design changes, and risks slow-moving stock and write-downs. Small lots make it possible to react faster to changes in demand, shorten throughput time and reduce the risk of obsolete stock — the reason why lean production and just-in-time consistently rely on small lots and low setup times.
The right lot size is therefore never a purely technical figure, but a business one. It has to fit the demand structure, the cost structure and the strategy of the company: a series manufacturer with stable quantities optimizes differently than a make-to-order manufacturer with high variant diversity. Wrongly set lot sizes show up sooner or later in overfilled warehouses, frequent missing parts or overloaded machines.
Lot size in ERP and PPC systems
In ERP systems with a production module, the lot size is a planning parameter in the item or material master. There the lot-sizing method, minimum, maximum and rounding values as well as the setup and ordering costs are stored. When material requirements planning (MRP) runs, it nets requirements against stock to net requirements and converts these into lot sizes according to the chosen method. The lots become production orders for in-house manufacturing or purchase requisitions for procurement — both carry the calculated quantity as the order quantity.
The lot size then feeds into the entire planning chain: it enters capacity planning, because setup and processing times from the routing are scaled up to the lot quantity, and it shapes scheduling, since larger lots occupy a machine longer. For multi-level products, lot formation propagates through the bill-of-materials explosion: the lot of the final level generates secondary requirements, which in turn are combined into their own lots according to the lot-sizing methods of the components.
Distinguishing lot size, order quantity and production order
The terms are closely related but mean different things. The lot size is the planned quantity of a lot — the result of the planning method. The order quantity is the concrete lot size in the procurement case, i.e. the quantity ordered from a supplier; the optimal order quantity is its economic counterpart to the optimal lot size. The production order, finally, is the triggered manufacturing order that actually brings a lot to the shop floor. In short: the lot size is the quantity, while order quantity and production order are the documents in which this quantity sets procurement or production in motion.
Example
Example: cosmetics manufacturer with setup effort
A mid-sized cosmetics manufacturer produces a hand cream of which 48,000 tubes are sold per year — an average of 4,000 units per month. Each batch requires an elaborate cleaning and changeover of the mixing vessel, costing around 600 euros. If the company ran a monthly lot of 4,000 units, twelve setups would arise per year; a single annual lot of 48,000 units saves setup costs but fills the warehouse for twelve months and ties up capital while the cream ages.
In the ERP system the item has the lot-sizing method "period-based grouping" with a minimum lot size stored, along with setup costs and the inventory cost rate. From this, material requirements planning calculates an economical lot of around 8,000 units and proposes a production order roughly every two months. If later a SMED optimization reduces the setup time and thus the setup costs per batch, the optimum shifts: the system can propose smaller lots, stock falls and the hand cream reaches retail fresher.
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