SYNCHRONOUSMANAGEMENT

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CAPACITY-BASED LOT SIZING

INTRODUCTION

As US companies have evolved into lean manufacturers, many have become disillusioned with the "economies" of large batches. Most have abandoned economic lot sizing; but without a quantitative replacement, lot sizing in lean manufacturing is often empirical. Changeovers are reduced to justify smaller batches, but customers still refuse to order EOQ's.

To resolve the lot sizing dilemma, SYNCHRONOUS MANAGEMENT has developed a breakthrough approach to determining run quantities. CAPACITY-BASED LOT SIZING (CLS) is not a cost-reduction technique - rather it is a tool to help you make more money - to increase your sales, to reduce your investment in inventory and to reduce total operating costs. So, CLS provides you with the minimum producible lot size, given the demonstrated capabilities of your manufacturing resources.

ECONOMIC ORDER QUANTITY (EOQ)

The basic assumption of EOQ is that as the lot size increases, the setup cost per unit decreases, since setup costs can be amortized over a larger quantity of parts. Conversely, as the lot size increases, the inventory carrying cost per unit increases, because parts are carried in inventory for a longer period of time. The EOQ is determined by the point at which the total of inventory and setup costs is at a minimum. Thus EOQ drives to minimize unit cost, but not total operating cost.

CAPACITY-BASED LOT SIZING (CLS)

CLS is based on the assumption that the path to making more money in the manufacturing business is by simultaneously increasing THROUGHPUT (rate of sales), reducing INVENTORY (lead times), and reducing OPERATING EXPENSE (total conversion cost). In addition to reducing inventory, CLS increases throughput by the labor content of the inventory reduction, and reduces operating expense by the carrying cost of the inventory reduction. CLS does not increase the operating expense associated with machine and labor capacity, because CLS uses only existing capacity. Unlike EOQ, CLS is resource-specific, based on the total capacity of the resource, and how that capacity is consumed.

LOT SIZE CALCULATION

The lot sizes on a resource are determined by a multi-step process (Figure 1).

1. First, calculate the total capacity for the resource. For example, if a machine is manned for one eight-hour shift, five days per week, its annual capacity will be 2080 hours (40 hours per week times 52 weeks). If, say, 10% of its capacity is lost to maintenance downtime, absenteeism and vacations, the total annual capacity available to setup the machine and to run parts would be 1872 hours (2080 times 90%).
2. Next, the total amount of capacity required to run parts for the year is calculated. Each part's historical or forecasted annual requirement is multiplied by its run time per piece, and the results are totaled for all parts on the machine. If, in our example, twelve parts are run on the machine, the forecast for each is 1000 per year, and the run time per piece is one-tenth of an hour, the total annual run time on the machine would be 1200 hours (12 parts times 1000 each per year times .1 run hours each).
3. By subtracting the 1200 hours of run capacity required from the 1872 hours available capacity, we find that the amount of capacity available to do setups is 672 hours (1872 setup & run hours available minus 1200 run hours required).
4. Finally, the amount of setup time required to cycle through one setup on each part is calculated. For our example, let's assume that it takes one hour to set up each part, or twelve hours total to cycle through all of the setups one time (12 parts times 1 setup hour each).
5. When we divide the available setup capacity of 672 hours by 12 setup hours per cycle, we find that each part could be set up 56 times per year (672 hours of setup capacity available divided by 12 hours per setup cycle). Thus, the lot size on each part is about one week's worth.

CLS invariably results in smaller batches than EOQ - without reducing changeover times, implementing manufacturing cells, or improving efficiencies. It does so simply by abandoning EOQ theory, and by recognizing the existing capabilities of your manufacturing resources. As a consequence, lot size inventories can be dramatically reduced, with a corresponding carrying cost reduction- as close as you will get to a free lunch!

Of course, this is a simplified example. The real world is fraught with complications. For example:

• To take advantage of common tooling, it is often advisable to run parts in families; when this is the case, CLS still applies by using the reduced setup per cycle, but your scheduling pull system should be designed to run the parts in families.
• Some parts may have long setups relative to the per-piece run time, which might establish a floor on the lot size, regardless of the CLS calculation.
• Any startup scrap should be considered as a cost tradeoff to reduced batches.
• Where dedicated setup people are employed, the available setup capacity should be adjusted to reflect setup labor capacity, not just machine capacity.
• CLS may use forecasted requirements, and we all know how inaccurate forecasts can be. However, we also know that it is a forecast of total mix is more accurate than for individual items. Since CLS is based on the total mix and total capacity, the results are still valid.
• When demand rates are unstable for any reason, the horizon for the CLS calculation may have to be shortened from a year to perhaps a quarter, or even a month.

CONCLUSION

The intent of this discussion has been to provide the reader with a step-by-step quantitative approach to determining your minimum lot sizes, given your manufacturing constraints. In using your data, CLS also provides you with a model for determining the lot size inventory impact of changes in those constraints. Of course, your results will differ from those shown above. In any event, it is important that your CLS's be modeled based on realistic expectations of your production capabilities, and that any results be tempered with common sense. If so, major reductions in inventory and lead times can result, helping you to position your manufacturing function as a true strategic weapon for your company.