Capacity planning for scheduling problems.

I visited a client recently who had a severe problem. I was puzzled by this because his product lines were fairly simple, and he had only a dozen or so work stations to contend with. Scheduling such a shop should be simple. But the factory personnel were each working 20 to 30 hours a week overtime for weeks on end, followed by periods when there was not enough work to keep everyone busy The overtime still did not yield timely deliveries to his customers. Further investigation revealed the client's suppliers were being harassed to expedite deliveries at times, while at other times they were directed to slow things down. The end result of this exercise in futility was demoralized employees, disgruntled suppliers, and unhappy customers. In order to teach this client how to generate schedules, it was necessary to get back to basics.

There are two fundamental ingredients for any schedule, whether it is a simple hand drawn Gantt chart or a computer-generated production schedule:

1. A thorough understanding of shop capacity

2. A list of delivery dates by product type.

Other factors enter into scheduling to be sure, but without an understanding of shop capacity, the production schedule is little more than a wish list.

Our problem was that our client didn't recognize that simple fact. He generated his schedule based strictly on customer demand, without regard for his ability to meet those demands. He wrote off the excessive overtime as part of the price he had to pay to achieve customer satisfaction. We had to explain to him that an understanding of the factory's capacity is an essential ingredient for scheduling. Without it, management cannot balance market place demands against the shop's ability to efficiently satisfy those demands.

We persuaded our client that a clear understanding of shop capacity would enable him to efficiently schedule personnel, optimize scarce resources (machining centers, personnel, etc), smooth the peaks and valleys of an irregular demand schedule, and enable him to plan and control his business.

Until now, companies like our client's had only two choices:

1. Purchase a sophisticated manufacturing resource planning (MRP) II program which usually contains shopfloor capacity planning as a subset, or,

2. Plan by the "seat of the pants" method. The first approach usually requires a relatively large initial capital outlay and an even larger implementation investment. Additional personnel may be required to set up and run the program. It is frequently many months before the sophisticated approach is useable and often the results fall far short of the expectation.

Our client was using the second approach with all of the attendant problems listed below:

* Increasing overtime

* Higher premium time charges from supplies

* Growing number of backorders

* Decreasing profits

* Low productivity (high costs) during slow periods

* Late shipments to customers

* Irate customers

* Cancellation of orders

* Declining market share

But we offered him a third choice. We showed him how to quickly calculate the shop load and immediately identify bottlenecks using his existing spreadsheet program.

Here's how this simple approach to shopfloor capacity planning works: All that is required is a spreadsheet program such as Excel, Quatropro, or Lotus 123, labor or machine [TABULAR DATA OMITTED] time estimates for the various operations, and a demand schedule for the number of units to be produced per week. Note: management should have an estimate of the labor and machine time required per operation in order to properly price the job in the first place.

The table emulates a spreadsheet that would be used to calculate weekly demand by workstation for a fictitious family of products. A separate spreadsheet must be used for each week, but if the demand does not vary the projections will be the same. The products in this example are generic in nature but this approach is useful for any product line that shares resources.

This table would be used as follows:

Column A is a list of sequential operations. If a given operation such as shear has different time standards for different products, list each one as a subheading under the main heading. The number in parenthesis represents the number of workstations or personnel available for that operation. Some operations such as operation I (shear) and operation 2 (brake) are running on two shifts.

Column B is the standard time estimated for a given operation in hours. For example, the estimated time it will take to shear a piece of sheet metal that is a specific thickness for Part A is 0.6 hours while 0.95 and 1.2 hours respectively are required to shear Part B and C respectively. The time to accomplish this should be known for any given size (thickness, length, and width) for a particular alloy. Enter these estimates in column B in the three rows titled "1a) Part A; 1b) Part B; 1c) Part C." These standards should be estimated only once for each part. If there are additional thicknesses or other alloys that require different time for the shear operation, insert additional rows. Be sure to enter the weekly availability (column G) only once for any given operation and calculate the shortfall/surplus by subtracting the sum of all requirements from the availability figure.

Column C, quantity per unit, is also estimated only once for any given product and entered in the appropriate row.

Column D, hours require per unit per workstation, is calculated as D = B x C. This column is shaded to indicate it is a calculation. Columns F and H are shaded for the same reason.

Column E represents the number of units per week required for that particular product.

Column F, weekly demand, is automatically calculated as F = D x E.

Column G is the number of hours available for that particular workstation per week, usually in increments of 40 hours.

Column H is the difference between the demand, column F, and the availability, column G. H = G-F. A negative answer projected demand exceeds projected supply for any given workstation in any given week. For those rows where there are subheadings, such as row 1, the demand for that operation must be summed for all parts, then subtracted from the single availability estimate. In this example, the demand for rows 1a, 1b, and 1c are summed, then subtracted from the availability in row 1. 120 - (28.8 + 22.8 + 86.4) = -18

A separate spreadsheet must be prepared for each week. This can be done as far in advance as the situation permits so that workloads and delivery schedules can be adjusted to accommodate the demand without additional costs.

Note that three operations are short of the required resources, operation 1 - shear; operation 5 - weld main beams; and operation 11 - final inspection. Several others, operation 6 - fabricate set of subassemblies; and operation 10 - paint, are almost in saturation. If any more products are scheduled through these operations, they will be driven into saturation.

The total manpower required for this product is within the available manpower total, but not in the proper skill mix. For example, the workers required for two of the operations that are short handed are skilled workers - welders and inspectors - and are therefore not easily augmented by workers with another skill set. The third operation that is short handed - shear - requires a semiskilled operator, but there are two stations so another worker can be hired and trained to fill the second slot on second shift.

Even if welders are moved from operation 4 - weld X members, to operation 5, weld main beams, there will still be a short fall of 24 hours: (32 - 56 = -24).

There are several ways to resolve this problem:

1. Schedule overtime for those stations in saturation. This should only be a short time fix.

2. Review several weeks in a row and reschedule work to smooth out peaks and valleys.

3. Hire and train additional personnel to fill in the resources that are at or near saturation.

4. Subcontract some work.

5. Look for ways to streamline the effort at those stations that are at or near saturation.

Consistent application of this program will give management visibility of a pending problem, well in advance. Management may then take corrective action before the problem causes a bottleneck.

Mr Culhane is the Chief of Quality Systems Consultant for the George S May Int'l Co firm. With 35 years in the industry, his consulting has included technical advice, as well as hands-on participation in analyzing and solving production/quality problems. He has performed numerous ISO/QS 9000 audits as well as audits to other standards.