Do small manufacturers need manufacturing resource planning (MRP) software to identify their ideal manufacturing cycle time within a given work cell? No, they don't. Even those companies with the most up-to-date software know that eliminating work stoppages involves seeing production in person.
Witnessing how individual work cells operate is the critical first step to lowering cycle times and increasing production throughput. It's up to you to see how the work operation functions in real time.
Here is a cycle time tracking Excel sheet that will help you define a work cell's average, median, and mode manufacturing cycle times.
Can Production Tracking Work in Excel?
While MRP systems can track cycle times and show you the variances between high and low cycle times, they can't provide insight into your ideal cycle time. This is why Excel is so helpful. Using an Excel sheet to establish your ideal manufacturing cycle time is the best way to develop a benchmark. You'll better understand why some cycle times are lower than others and why a particular work cell experiences higher-than-normal cycle times.
Go to Manufacturing Cycle Times in the Perfect Work Cell to learn how a lean manufacturing work cell should be structured. Otherwise, if you feel comfortable with your production set-ups and your shop floor layout has been optimized, you can proceed with the following three-step cycle time optimization process.
1. Capture Causes of Work Stoppages For Each Operation
This sample Excel sheet allows you to capture each operation's causes of work stoppages. Define the workstation you're analyzing, the work operation, and the assembled or manufactured product. You then input each cycle time into the Excel sheet. The "notes" section lets you itemize what happened during a given work operation. This is where you define what caused a work stoppage or delay.
2. Production Work Station Analysis
The table below outlines the cycle time analysis within a work cell. A total of twenty cycle times were captured. The table summarizes the initial trials. The twenty times are placed on a graph to establish the natural progression of times from each operation.
In this example, we've established the average ("mean") time while isolating all twenty operations' median and mode times. Future evaluations would be used as a comparison to this initial baseline. You would replicate this exercise daily to eliminate work stoppages within the work cell. Each day will provide more evidence of your ideal cycle time while helping you pinpoint exactly what's causing lost time.
Average ("mean") Times: Calculating the average involves totaling all twenty times and dividing 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 (two minutes and 55 seconds). The AQUA BLUE straight line represents the average.
Median Time: Calculating the median time involves rewriting the sequence of times in order and using the calculation below. While the median time is not represented in the graph, you could adjust it to show it alongside the other lines. The median is just another measurement of the average.
- 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: The mode time is the time that occurs the most often in the sequence. This might be particularly important when identifying work stoppages. If a work stoppage keeps happening, then it might account for the same repeated times. This example's most common cycle time is 2.3 (two minutes and 30 seconds). The mode time is the RED straight line on the graph.
3. Analyzing the Graph and Identifying Solutions
A few higher-than-normal results can easily skew the average cycle time. You must capture the causes of work stoppages to understand why some cycle times exceed the average. The four operations that took over three minutes would need further investigation. The purpose of the exercise is for you to identify your highest cycle times and answer the following three questions.
1. Why are these cycle times high?
Identify the causes of the high cycle times. Causes might include an incomplete bill of materials, an inaccurate work order, a confusing assembly outline, or any issues with equipment downtime.
2. How often does this happen in a shift, a day, a week, and a month?
It's not enough to define why cycle times are high. You need to understand how often these work stoppages occur within a shit, a day, a week, and a month. This helps to define the severity of the issue. Analyze results over several days to have a more accurate depiction of what's causing the work stoppages.
3. How can this be fixed?
Identifying the causes of interruptions is often much easier than finding a solution. Work instructions are pretty easy to resolve. They take time to fix but are often well worth the effort. Issues involving machine repairs are something else entirely. Sometimes, you must do a cost-benefit analysis on the cost of repairs versus the costs of doing nothing and living with high cycle times.
While it's not an exact step-by-step process to performing a cost-benefit analysis, the following article still provides insight into deciding on an equipment upgrade. What's Involved in Making a Decision on a Capital Expenditure?
Remember, no MRP software can provide a tailor-made solution to increasing your production throughput. These systems can only report data. They can't manipulate the data. Your production employees hold the keys to eliminating work stoppages. Use their invaluable input. Work with them to isolate why idle time occurs in a given production work cell. Making your employees active participants ensures this exercise is non-confrontational.
Track the incidence of lost time over a shift and repeat the process each day until you have a large enough sample portion. Here is the sample Excel sheet used in this article: Download Cycle Time Tracking Variance Analysis in Excel
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