How a Converting Plant Cut Its Inventory by 33% and Reduced its processing waste by 14%
Pressure to become more competitive, cut costs, improve efficiencies, reduce waste, reduce inventories, and maintain or improve service are day to day activities for managers in today's marketplace. Sometimes these conflicting objectives can be satisfied through the use of advanced planning and scheduling technologies. This case study shows how Greycon's Roll Stock Optimiser can help managers satisfy these needs. The following case study documents the impact of RSO for an on-line converting operation with a two-sheet cutter running 3 shifts 5 days per week.
The plant management perceived that trim loss was too high. They believed that they could reduce the trim loss with a better selection of roll widths in inventory. The plant manager mandated the scheduling and inventory team to use a scientific approach to better understand the configuration of roll inventory and to identify opportunity to change the current choices of roll stock widths.
The number of widths and widths selection until then for each bases weight as well as the current inventory levels had been set and "refined" over years of tradition and constant scrutiny by senior analysts who relied on instincts and experience.
The plant manager heard from a peer located at another plant using Greycon's product that a simple optimiser was available via the Internet. He realised that the product was in fact a internet subscription that provides a few cents per calculation the ability for his small operation to use the latest and most advanced optimisation algorithms.
The utilisation of software like RSO was a bit controversial at first since most perceived that identifying the right size was more an art taught by experience rather than science.
Simplicity of Using RSO
The first step was to extract in a simple spreadsheet the customer order by grade/base weight. The data was then consolidated to obtain the total quantity for each roll size. The third step was to cut-and-paste the data into the web site of the RSO. The RSO calculation took a couple seconds and presented immediately the best roll widths, the quantity recommended to store and expected trim loss. The calculation were taking into consideration the unique parameters and constraints of the plant.
For each base weight, multiple numbers of size were typically analyzed. The system would then recommend for each number of rolls the ideal width and the estimated waste. For the products with up to 8-10 widths, the system immediately recommended better yields obtain with as low as 5 widths. For the products with 4-6 widths, the system typically continues to recommend the same number of width but recommended different width selection. In all cases, the system also recommended ideal quantities for each width on which, the operation based its replenishment policy.
At the beginning of the project, the plant with a roll inventory of about 2000 tons would typically sheet 1,000 tons of paper per month with an average trim of about 100 tons. While the demand remained typical after three months all the products were analysed and the roll width readjusted and inventory level reviewed, the plant had a roll inventory of about 1350 tons still sheeting the same amount of paper with an average trim loss of eighty-six tons.
$96,000 Trim Savings
In this context, using the lowest value per ton ($500), the trim reduction saved $8,300 per month or $96,000 per year (192 tons). The assumptions of the plant manager were vindicated: a better mix of roll width was able to minimize the waste. But the recommendations of RSO had other significant impact on inventory and customer services.
$63,400 Inventory Savings
Because the reduction of overall roll widths, the plant was able to lower the inventory quantities of the remaining roll widths. The overall inventory was reduced significantly after the period of transition from 2000 tons to 1350 or a total reduction of 33%. Using an average cost of carrying inventory of 18.5% as a base, the annual saving of reducing the inventory represent about $63,400.
Considering the low cost of the RSO subscription, the payback was obtained immediately and visible after only one week of utilising the application. The overall return on the investment was over 6000%. In the context of this case, customer services measurements were not affected by the changes in policy. In average, the product was delivered with the same lead-time than before and the overall customer satisfaction remains constant during the period. In other context we have noted that the application of RSO also improve customer services by anticipation better the roll stock demand, allowing a quicker turn around.