Snowy Rides and Short Run Charts

Improvement Insights Blog

Snowy Rides and Short Run Charts

cyclist-snowy-forest 560x310.jpg
I had just finished clearing the snow from my front walk and come inside when I heard the text alert tone from my computer. After kicking off my shoes and hanging up my coat, I checked my phone and found a text from a past client.

“Need help. Would you be available some time for a video call? – Andrew Joseph”

I sent him a message that I was available now if he’d like, and a few minutes later I was sitting in front of my computer with a steeping mug of Earl Grey tea connecting with Andrew.

“Hey there! ” I greeted him. “I didn’t imagine you’d be too busy now in your business, with the weather being so cold and snowy.”

“Are you kidding? It’s been a great year at Namkcits Cycle Gear. This past summer, lots of people realized that cycling is the perfect socially-distanced activity. And right now it’s the height of summer in Australia, so we’re seeing lots of internet orders for the same reason. Of course, we sell gear to Brazil, Indonesia and the Philippines all year long.”

“Really? Well, I’m certainly glad it’s nice enough weather in some parts of the world to ride a bicycle.”

Andrew leaned back and I could tell he was still at his office. I could also see his  bike behind him. “Well, I rode here today in the snowstorm.”

I nodded. “I stand corrected. Glad things are going so well. So how can I help?”

“Well, we had such a good year that I invested in a couple new machines that allowed us to expand production. With these machines, we can set up for new specifications quickly, so we are able to do short runs of saddles and make it cost effective,” Andrew began.

“And from what I remember, ‘saddles’ are what you call bicycle seats, right?” I asked.

“Right,” he replied. “We used to produce dozens of one saddle with its own specifications, then produce dozens of another saddle with its own specifications. With those quantities, I could use the histograms that you showed me when you were here last.”

“Yes, I remember. So what’s the issue?”

“Well, since we’re only producing 5 or 10 of each saddle, the histograms don’t tell me much, and the control charts you showed me don’t work because we don’t have enough data points. How can I approach quality control with short runs like this?” he asked, clearly frustrated.

“Got it. This may be easier than you think,” I offered. “I can see your screen. Can you give me control over your mouse?”

“Done. I’ve got the data in the spreadsheet that’s open,” Andrew said. “Like you taught me last time, I’ve kept track of the order each piece want through our process.”

This is what I saw on his screen:

01 Cycle Saddles Raw Data.jpg

“All right, so I’m assuming that each of these particular models of bicycle saddle has a target weight, but that the target weight varies from model to model, is that right?” I asked.

“That’s exactly right.”

“Okay, so think about this: If you’re making 100 of the same model, you want to be sure that you’re both accurate and consistent, right? If the model should be 200 grams, you want the average to be as close to 200 grams as possible – that’s accuracy. You also want to make sure that each piece doesn’t vary from the other pieces by very much – that’s consistency. Are you with me so far?”

“I’m with you,” replied Andrew.

“In this case, you don’t have enough data on each model to do a control chart on accuracy, but you can compare consistency. One of the tools we can use for this is called a ZmR chart. Some companies use ZmR to track multiple characteristics of a part on the same chart; for instance, hardness, finish, etc. Other companies use the ZmR to track short production runs like this.

“This chart converts all your data into a standardized value that compares the data point to the average of other units of the same model. You can then look at your consistency by looking at deviation of each part against the average. Let me show you.

“First, we highlight the column with the model name of each part as well as the column with the weight. Then we select the ZmR chart from the QI Macros menu.”

02 Cycle Saddles Highlight and select.jpg

The software worked through the calculations for a moment and displayed the finished ZmR chart:

03 Cycle Saddles ZmR chart.jpg

“If you look at the chart, it looks pretty good. The r chart shows a short period where you didn’t have very much variation from the average; the chart flagged that red as particularly unusual. If you look to the right of the charts, the software lists the actual weight in column S and the average and standard deviation of all parts of that model in columns T and U.”

“Sweet!” exclaimed Andrew. “I thought this would be WAY harder.”

“Everything’s easier if you have a great tool and know how to use it. Now, understand it wouldn’t be proper statistics if there were only one, undisputed way to do things. You could use QI Macros’ Short Run charts to look at your data if you wanted to. I just wanted to show you this tool to keep things as easy as possible.”

“I appreciate that. I might do some research on that, just to compare. But for now, you’ve sure earned your consulting fee.”

“Well, glad to help,” I replied. “And even more glad that my tea is still warm. Have a good evening.”

“You too. Keep the rubber side down!” he exclaimed, signing off.
If you’d like to learn more about the QI Macros ZmR chart, click THIS LINK to learn more. If you’d like to see the Short Run control chart that we hinted at but didn’t demonstrate for Andrew, click HERE to learn more.

This entry was posted by Jay Arthur in QI Macros Monthly Newsletters. Bookmark the permalink.