It can be incredibly frustrating trying to define the costs of lost time in manufacturing. The questions about how to address idle time, as well as the true costs of these work stoppages, always seem to be up for discussion. The following four step process should help you determine the productivity rate in a given work cell, help you track cycle time variances in that cell, and finally, help you define the true costs of work stoppages.

** 1. Assess Work Cell Productivity Rate**

This first step is rather simple. Determine the amount of actual work time, while accounting for lost time in the work cell. Next, use a simple and straightforward calculation to determine the productivity rate emerging from that cell. Focusing on an individual work cell helps to get at the root causes of work stoppages. However, that means you must define how much time the operator actually has available to work.

Even though a company pays an employee for 8 hours, they don’t work a full 8 hours. Take away lunch and breaks and you’re often left with 6.5 hours. This is the amount available to work, but nobody is 100% efficient. Therefore, to determine the productivity rate, you must find out how much time the operator works from this 6.5 hours. Here’s a quick summary of what the productivity rate might look like.

- 1 hour = 60 minutes, so 6 & ½ hours = 390 minutes
- Lost time during analysis: 135 minutes (this time is captured throughout the day)
- Available work time in minutes: 390 – 135 = 255 minutes
- Productivity rate% = 255 minutes divided by 390 minutes is 65%

The video above explains proper work cell layout and design. It includes a portion about how to determine manufacturing productivity rates in a given work cell and is from the post: Manufacturing Work Cell Optimization: Design, Layout and Analysis

**2. ****Account for Miscellaneous Down Time**

While the calculation from the first step shows how to determine the productivity rate in a work cell, it doesn’t show how to manage and lower the cycle times emerging from that cell. Its purpose is simply to document the total amount of idle time. This second step is where your company begins the process of tracking its cycle time variances and identifying the impact of work stoppages.

Remember, nobody is capable of being 100% efficient. People need to go to the bathroom, take a breather, say hello to co-workers, get a drink etc. Once you’ve determined your productivity rate in a given work cell, and have properly documented lost time, be sure to summarize the time employees needed for these miscellaneous breaks.

Let’s assume that from the 6 & ½ hours (390 minutes) of available work time, those miscellaneous breaks amounted to 45 minutes during the day. On average, you notice that about 45 minutes is the norm each day. It's up to you to define whether this time is acceptable or not. Continuing on with our example, you’ll base your cycle time analysis on the assumption that from the 390 minutes, an employee can work for 345 minutes, if not interrupted.** **

**3. ****Analyzing Cycle Times**** Variances**

The table below shows a cycle time variance analysis done for a customer of mine where we focused on the times emerging from a particular work cell. We took a series of 20 cycle times during a single shift. We then repeated the process over a couple of days before getting a true indication of the mean, median and mode cycle times. The table and graph below shows the variances in cycle times and how to calculate all three averages. The idea is to isolate high production times and itemize the reasons for these high times.

The excel sheet can be downloaded from the link provided just below the second video.

*Average (“mean”) Time:* Determining the average includes totaling up all the twenty cycle times and dividing it by the number of operations. In this case, it’s 51 minutes divided by 20 operations. This gives us an average cycle time of 2.55. This is shown as the straight blue line across the graph.

*Median Time:* Calculating the median includes writing the entire sequence of cycle times in order and then using the following calculation described below.

- Median: {(n+1) / 2}
- N= sample size: which in our case is 20 operations
- Median: {(20+1) / 2} = 10.5

2.15, 2.15, 2.25, 2.3, 2.3, 2.3, 2.3, 2.3, 2.45, 2.45, **2.45**, 2.5, 2.5, 2.5, 2.5, 2.55, 3.25, 3.25, 3.25, 3.3

*Mode time:* This is simply the time that occurs the most often in the sequence. In this particular analysis, the most common time is 2.3. The mode time is the **RED **straight line on the graph.

The purpose of the exercise is to isolate high cycle times in a given work cell and define the root causes of these high times. Next, you can then use the mode time as the ideal cycle time - as long as it is the one that occurs with the least amount of down time. Mode times are the ones that occur the most often in a sequence, so you'll have to review why these times are so common. If they are the "ideal" times because of minimal downtime, then these are the benchmark cycle times emerging from this cell. Again, the excel sheet can be downloaded from the link below the video - so you can see how the graph would depict the cycle time variances in one of your own work cells.

You can access the same excel sheet as the one used to perform this analysis by visiting the post: Cycle Time Tracking & Variance Analysis in Excel for Small Manufacturers

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**4.**

**Assessing the Cost of Lost Time in Manufacturing**

This is where your company needs to put a dollar value on idle time. Unfortunately, it's common for companies to sometimes ignore the costs of work stoppages. This is ultimately why it's important to define the impact of delays in terms of lost gross profit. A simple example might include stating that lost time of 1/2 hour, with a product whose average cycle time is 2.5 minutes, means the company lost at least 11 units in production. Now, what is the gross profit on these units and how often does this lost time occur during a given shift, day, week and month?

To summarize, it’s all about understanding the productivity rate in a given work cell, the amount of down time emerging from that cell, the ideal benchmark cycle time you should track future performance against, and the costs of work stoppages. These costs must be understood by all in order to reduce their impact. Ultimately, it means finding the best possible cycle time and then trying as much as possible to duplicate those times.

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