a factory called R.C. Hansen’s Factory receives raw materials and semi-assembled parts, then provides finished products that are sold for a net price of $100 each. Assume the factory process is a set of transformation steps in series, similar to a long assembly line with minimum or zero buffers between steps.
Assumptions: During the year, the factory manufactured full out, operating around the clock, 320 of 365 days (7680 scheduled hrs). The other 45 days were used for experiments, shutdowns and planned maintenance days, holidays, training days and headroom allowance. Headroom allowance is where an annual production plan purposely reserves manufacturing capacity for risk management (uncertainty). This can be in the form of unanticipated new orders (positive) or a buffer to accommodate unusual OEE losses (negative). Note that headroom is part of excluded time and addressed when computing Total Effective Equipment Performance (TEEP). It is addressed in OEE only when it is “cashed” and re-identified as planned production time.
For the base case, the factory manufactured 1 million units. The product mix and output schedules were relatively constant over the year. The units were sold for a net price of $100 each. Therefore, Net Sales = 1,000,000 × $100 = $100 million
Before jumping into the financial breakout, we will use the following definitions for this chapter.
“Direct material includes all of the important materials or component parts that physically comprise the product. Examples are sheets of steel, electric motors, and microprocessors. Incidental material items-such as glue and fasteners-are considered indirect materials and are included in factory overhead. Supply items-such as cleaning supplies and lubricants-are considered factory supplies and are included in factory overhead.
Direct labor includes the salary and wage costs of factory employees who work directly on the product. Machine operators, assemblers, and painters are examples of such workers. The salary and wage costs of factory employees who work indirectly on the product-such as supervisors, inspector, material handlers and maintenance workers are considered indirect labor costs and are included in factory overhead.
Factory overhead, sometimes called manufacturing overhead or factory burden, includes all other manufacturing cost not included in direct materials or direct labor. Examples of items included in factory overhead are indirect material, factory supplies used, indirect labor, factory payroll taxes and fringe benefits, factory utilities (natural gas and electricity), factory building and equipment costs (insurance, property taxes, repairs and maintenance and depreciation), and other factory costs.” 1
With these definitions, assume the following breakout of the financial figures: Categories and proportions are similar to page 928 of the reference book. (figures in millions)
Of the categories above, Direct Materials and Direct Labor vary almost directly with the amount of product made for sale. If productivity improvements are made but the same amount of product is produced, the Direct Labor expense will vary with the productivity improvement. Usually these expenses vary with scheduled operating days and are the direct labor number of the financial breakout. However, with fewer operating days, Sunday overtime is often the first reduction target that could increase the rate of expense reduction for direct labor.
In our case, the small amount of process materials and utility costs collected in the Factory Overhead will be considered negligible when examining costs that vary with sales. If these expenses are significant in your situation, you will need to proportion the variable amount in these categories similar to the approach used in sections 3.2 and 3.3.
Suppose that using the methodology outlined in chapter 2 to study the factory bottleneck, we find a combined OEE of 60 percent, (assume Availability = 65 percent, Speed Factor = 0.97, and Quality Factor = 0.95. OEE = 65 percent × 0.97 × 0.95 = 60.0 percent).
Now you can examine the value of improved OEE for your factory, answering the question “What could have been?” You should begin to see the linkage between changes in OEE and operating income before interest and taxes at your factory.
Given this approach, let us now compute the combined Ideal Speed Rate for the base case. The Ideal Speed Rate (R) for our current factory process is obviously influenced by the specific product and process mix. We will assume the same mix for the two scenarios that follow.
From section 2.5, OEE computation method #3, we know that
We also know OEE (60 percent or 0.6), Number of Good Units Made (1,000,000), and Scheduled Time (7680 hr). Therefore, we can solve for Ideal Speed Rate, R. Substituting terms, and we have
This single measure for Ideal Speed Rate combines the various ideal rates for the product mix. Recall that the product mix and schedules have been assumed to be relatively constant for the past 12 months and for the near future. Any difference in the financials will be the direct result due to OEE improvement.
Various “what if” scenarios could be reviewed. Two important financial investigations would be “What if we had achieved higher OEE and 1. Produced the same volume as the Base Case or 2. Operated the same number of days and sold everything we could make?”
Recognize that we operated full out in the Base Case and marketing and sales are constrained until the factory increases annual capacity. Without specific cause and effect projects, demonstrating higher capacity may take several years. With well documented, targeted OEE projects and using this metric real-time (at least daily), you can statistically demonstrate higher capability in a short time frame.
When increased sales are uncertain, I have often had long discussions with financial analysts over what value to assign improvement projects for developing higher capability that only provides for potential future sales. Future sales are uncertain and may not develop for a year or more. Without the capability, increased sales would require future (significant) investment. With the capability, sales can be generated with minor expense increases, which will be demonstrated with question 2.
The answer is left up to you, but it must be somewhere in between question 1 and question 2. Depending on time, if only one third of the sales develop, it may double the business case addressed in question 1.
3.2 Case B: Same Output, Improved OEE
Case B provides the same scenario as Case A, except OEE improves from 60 percent to 66 percent (OEE = 66 percent: Availability 71.6 percent × Speed Factor 0.97 × Quality Factor 0.95 = 66.0 percent). For this example, we have made gains only in availability perhaps resulting from reliability projects or faster changeovers. A discussion on project value for improved availability, is presented in section 5.1 and encourages the elimination of unplanned downtime. Equipment reliability projects such as Reliability Centered Maintenance2 or condition monitoring practices focused on bottlenecks may contribute to increased availability. They can be reviewed and presented using these examples.
In Cases B and C, the increase in OEE of 6 percentage points represents a 10 percent improvement:
As in the base case, the factory makes 1 million units and sells them for a net price of $100 each. Given OEE (66 percent), Ideal Rate R (217 units/hr), and Number of Good Units Made (1,000,000), we can solve for Scheduled Time, the number of hours needed to produce the units with the new OEE level. Adapting the formula from section 3.1,
The impact of improving OEE has been to reduce Scheduled Time from 7680 hours to 6982 hours, a savings of 698 hours.
Suppose