All businesses have process flows in which a product is designed or manufactured or in which a service is rendered. An on-going goal is to achieve the maximum possible throughput at the lowest possible cost while meeting all the requirements of the product or service.
A certain minimum amount of in-process inventory is always necessary. This level is defined by Little’s Law:
I = R x T
where I = inventory, R = flow rate, and T = flow time, all of which are average values.
The actual amount of inventory in the process will be greater than the theoretical amount because some inventory always will be in-transit between different locations. Furthermore, the actual levels usually are planned to be even higher.
There are four possible reasons that firms intentionally plan excess inventory levels:
1. Economies of scale
2. Production and capacity smoothing
3. Protection against supply disruptions and demand surges
4. Profiting from price changes
Inventory Costs (Disadvantages of a large inventory)
When counting average inventory in a process, the steps prior to the process bottleneck will be full, and those afterwards will be occupied by a ratio of the throughput rate of those steps to that of the bottleneck.
When changing a production system from a long conveyor belt to a production cell system, with each cell producing the full product with fewer workers, one method to determine the optimal place to break the line is:
Inventory in Queue with Variable Arrival
II = [ ρ x ρsqrt(2(c+1)) – 1 / 1 – ρ ] x ( Ci2 + Cp2 ) / 2
where II = inventory
ρ = capacity utilization
C = std. dev / mean
When calculating average wait time, divide average inventory in the queue by the arrival rate, not by the processing rate. This is because the system throughput is determined by the incoming rate, not the processing rate (capacity utilization < 1).
Some Quality Experts
Deming: statistical process control
Juran: modeled cost of quality as U-shaped curve
Crosby: quality is free