Lean management requires identifying and eliminating the sources of waste throughout the entire value chain of your operations. Waiting in queues, excessive transportation and material handling, excessive inventory levels, defective products, reprocessing, and lack of employee involvement are the most significant types of waste in organizations.
Excess inventory is one of the most critical because it not only impacts the firm’s cash flow but also increases cycle times and customer lead times. The process of managing, purchasing, and locating objects or materials is usually referred to as Inventory Control Management (ICM).
Before linking excess inventory with cost and cycle times, let us review why ICM is so important for companies that hold inventory. The primary goal of ICM is to know when and how much raw material to buy. Manufacturing industries have access to a large variety of different ICM models that vary in complexity. Some of the simpler ICM models only require basic data on pricing and historical demand for their calculations. Other models are a little bit more complicated because they need to consider the behavior of data besides the average cost and demand.
The simplest and most largely used model in ICM is known as the Economic Order Quantity (EOQ) model. The goal of the EOQ model is to minimize inventory cost. Thus, managers only need to know the holding cost per unit, the cost of ordering and the historic or forecasted demand1. The EOQ calculations will yield the amount of inventory to be ordered each time to minimize costs. Although the model is easy to use and implement, one of the main disadvantages of the simpler EOQ model is that it does not consider fluctuations in demand rates, which could lead to raw material shortages. Nonetheless, the implementation of even a simple EOQ model is a strong step towards the elimination of excess inventory in any industry. In pallet manufacturing, it is usually best that managers focus their attention on the top five raw materials and develop EOQ models for each one.
Understanding the connection of inventory levels with other process metrics such as cycle time and throughput will save your company thousands of dollars. A concept that is little explored and understood in manufacturing is the connection of inventory levels with other process metrics such as cycle time and throughput. Inventory is typically classified as raw material inventory, Work In Process inventory (WIP) and finished product inventory. In pallet manufacturing industries, lumber, stringers, deck boards or logs are considered raw materials. Pallets being fabricated as WIP, and finished pallets ready to be delivered are considered as finished product inventory. Cycle Time (CT) is the time that it takes from the moment that raw material is received at the dock until the final product is dispatched to the customer. Throughput (TH) is defined as the production speed of the system, and it is measured in parts per unit of time.
There are certain laws that apply to any manufacturing system just like physic laws apply to natural phenomena. For example, for any manufacturing system the speed of production (parts/time) cannot be higher than the bottleneck operation (rb), which is the slowest operation in the system. Also, once you reach a certain level of inventory or WIP in the process, your cycle time will continue to increase, but your throughput will remain flat. These relationships or laws are not new, but they continue to be largely ignored by an extremely high percentage of manufacturing industries, including forest products industries. Understanding them will help your company to decrease cycle times, decrease inventory, increase customer satisfaction levels, and in general; to decrease costs.
The relationship between CT, TH and WIP is known as Little’s Law, and it can be expressed as:
WIP = TH x CT
Figure 1 shows that as the inventory level increases (WIP), there is also an impact in cycle time and throughput. In the first case, notice that as the WIP grows, the TH also grows up to a certain point and then it remains flat. This point is called critical inventory level (Wo).
In the second case, as the WIP grows the CT remains constant up to a certain WIP level, W0. After this point, the CT continues to grow with no stopping. These relationships or laws are very important because they reflect that an excessive amount of inventory in the system not only increases inventory costs (holding and ordering costs) but also increases cycle times. The more time raw material, work in process, or finished inventory remains in the system, the more it costs for the firm. In addition, other hiding costs such as material handling, transportation and waiting in queues are added.
Recently at Virginia Tech, we were able to demonstrate the applicability of Little’s Law to hardwood lumber processing. Drying has the longest process time per unit in the industry particularly for slow drying species like red and white oak. An alternative technology to dry lumber at a faster rate without compromising quality is vacuum drying technology.
By using process simulation, lean thinking principles, and Little’s Law calculations we were able to compare different drying methods to meet the same demand for dried 4/4 oak lumber. We were interested in measuring the differences in WIP, CT and TH when using traditional air-drying then conventional kiln drying vs vacuum drying 4/4 red oak lumber. Our results indicate that by switching from traditional air-drying plus kiln drying to vacuum drying technology, a company with a daily demand of approximately 16 MBF of 4/4 red oak lumber can experience a WIP reduction of 52-57%, a CT reduction of 78-90% and would result into a cost savings of $ 7.3-13.5 million/year.
Our results demonstrate that controlling inventory levels is a key strategy to decreasing manufacturing costs, increasing positive cash flows, and decreasing cycle times thus positively impacting customer service levels. By better understanding the fundamental relationships among inventory levels, throughput and cycle time the pallet industry could make a huge leap towards the implementation of lean management.
In addition, managers need to understand the financial aspects of holding excess inventory and how overstocking sometimes could be beneficial to protect against supply chain shortages and market instabilities. For example, bad weather is a factor that could shorten the supply of logs and lumber. To prevent this from happening, managers might elect to overstock certain critical raw materials or to buy in bulk to access discounts or extended credit terms.
(Footnotes)
1 At Virginia Tech we have developed an extension publication to explain how to make these calculations. Please visit http://goo.gl/JLq3WW to access this publication:
