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I'm looking for the information on the results of weighing cast bullets. I particularly need the results for heavier cast bullets, over 299 grains. Light is good too. Maybe 22 and 25 caliber bullets. The ideal information would have mold maker/number, and the weights, sort of like this: Lyman 457125 524.0 1 524.1 0 524.2 6 524.3 8 524.4 19 524.5 32 524.6 76 524.7 41 524.8 28 524.9 11 525.0 12 525.1 7 525.2 2 525.3 0 525.4 1 525.5 2 All responders will receive proper attribution. Thanks; joe b. joeb33050@yahoo.com | ||
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Hello Joe- Here is some data I collected a while back for three of my moulds. Each of these are double cavity, iron moulds. The weights include bullets from both cavities and from a continuous casting string out of the same batch of alloy. Ladle poured (RCBS ladle), approx 50lb alloy pot heated on coleman stove, Thermometer used in pot. Best regards- Sky C. Mould #1: "SAECO #018, 405-458-FP Mould #2: "RCBS 325-458-FP" Mould #3: "RCBS 150-357-SWC" Measurement is weight in grs. off a Dillion Precision Electronic scale. A small sample batch was check weighed on an RCBS balance beam scale with 100% agreement. #1 / #2 / #3 420.1 / 341.6 / 155.1 420.4 / 342.5 / 155.0 419.9 / 342.3 / 155.0 419.8 / 341.5 / 155.0 419.1 / 341.4 / 155.0 418.4 / 341.5 / 155.0 420.6 / 341.5 / 154.9 420.4 / 342.6 / 154.9 419.4 / 341.2 / 154.9 419.0 / 341.6 / 154.9 419.9 / 342.5 / 154.8 419.8 / 342.1 / 154.8 418.8 / 342.4 / 154.8 420.1 / 342.1 / 154.7 420.1 / 341.3 / 154.7 418.8 / 341.5 / 154.7 420.1 / 341.2 / 154.3 420.6 / 341.9 / 154.2 419.8 / 342.2 / 154.1 420.4 / 341.5 / 153.8 Max: 420.6 / 342.6 / 155.1 Min: 418.4 / 341.2 / 153.8 Avg: 419.8 / 341.8 / 154.7 SDEV: 0.6 / 0.5 / 0.3 | |||
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Thanks, this is just what I need. Any additional info greatly appreciated. joe b. | |||
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So basically you are trying to build up a histogram? Why? I did this for years. Somewhere, in one of my numerous notebooks, I've probably got several. I did it enought to realize that the histogram got noticeably flatter as bullet weights increased. Wider weight distribution (larger variance) with increased weight. The histogram is also critically dependent on what firm made the mould. A SAECO or H&G mould, for instance, has a lower variance than a Lee or Lyman mould. Still, so what? Interesting numbers but what do you hope to learn from this? | |||
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Interesting! With some experience in statistical analysis, I would have expected the distribution to show a longer tail towards lower weights (due to voids and incomplete fill-out) and a shorter tail at the higher end (maybe not holding the mould as tightly closed), but these look pretty "bell-curve-ish". Certainly "tight" bell-curves like these show very good technique and inspection. floodgate | |||
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Quote: Ken, You're the man to be puttin' the book together, {;o)! Cheers, Richard Ps. Nice CZ, lol, now I'm back to playing with lever actions. | |||
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Quote: The distributions are frequently not at all normal looking, and frequently there ain't much of a tail at either end. All my data says that the standard deviation is independant of the mean bullet weight, about .1-.2 grains-in that range. I'm trying to verify my data with others, particularly with heavy and light bullets. Merry Christmas!!!!!!!!!!! joe b. | |||
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Years ago I tried separating bullets into 0.1 grain weight groups. Just to many of them. Finally I settled on 1 grain weight groupings. I cast the bullets up and then separate them into boxes consistent to one grain. Current electronic balances being what they are, however, I'm sure that there is a little slop in this. A long time ago I use to record the number of bullets in each of these groups. That lead me to the conclusion that weight variation depends most on two things, the weight of the bullet and who made the mould. Heavier bullets usually have a higher weight variance. Poorly made blocks do also, regardless of weight. As a practical matter I used this to restrict the kind of moulds I would buy. Low weight variations occurs with Ballisti-Cast, Hensley & Gibbs, NEI (back when Walt was alive), RCBS and SAECO moulds. If I seriously want to control weight variation AND these companies make the mould I need I buy from them. Hoch does good work too but I don't have enough experience with his moulds to know how well his moulds control weight. I've only used his double cut-off plate blocks. CBE, in Australia, isn't bad either. If you really want to study weight variations and are going to weight bullets to the tenth of a grain then there is another series of experiments that are interesting. Take a single cavity mould and save and weight the bullets in their as cast order. Plot the results in such a way as to show which bullets were visually acceptable and which were not. If you do this you will see, for example, that fluxing changes the pattern. Weights drop after a fluxing and, if memory serves, so to does visual acceptance rates. This is why I haven't fluxed during a casting session in decades. Simarily you can make and change you like, like changing the temperature, as see what effect it has on these plots. A LOT of work but really interesting. This is the only case I know of where weighing bullets closer than to the nearest grain seems to be worth the effort. | |||
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Quote: Interesting approach - to gain insight from others' practices - that certainly is an indicator of normality or not. If, however, you do not have a distribution approaching a 'normal' distribution, then look for the cause. There is ALWAYS an assignable cause. Finding it may be the trick, but when the variation is there it's a statistical indicator that SOMETHING is happening. That's why it's used in industry to observe and control manufacturing processes. Since weighing bullets takes place when they're cooler, knowing the sequence of casting may well tell you a lot. | |||
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"If, however, you do not have a distribution approaching a 'normal' distribution, then look for the cause. There is ALWAYS an assignable cause." Really?! I thought that if you took very large numbers of measurements most things would end up looking "normal." | |||
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There's nothing that I know of that tells me that the distribution of bullet weights should be normal. No matter how many I measure. The dreaded "central limit theorem" tells me that sample means are distributed normal, regardless of the shape of the parent distribution. And something tells me that opinions are much easier to find than is data. Merry and happy; joe b. | |||
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[quoteReally?! I thought that if you took very large numbers of measurements most things would end up looking "normal." No, only if you take samples of size "n" and average them. These averages are distributed normal.Central Limit Theorem joe b. | |||
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[quote If, however, you do not have a distribution approaching a 'normal' distribution, then look for the cause. There is ALWAYS an assignable cause. Finding it may be the trick, but when the variation is there it's a statistical indicator that SOMETHING is happening. That's why it's used in industry to observe and control manufacturing processes. Statistical Process Control, for variables, ex X bar and R charting, estimates the sample standard deviation from the range, adjusts that population S.D. estimate by the sample size per C.L.T., and makes the normality assumption per C.L.T. A lack of understanding of the probability of a sample piece beyond control limits is why SPC has come and gone in 3 waves in my 45 year association with industrial statistics. | |||
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Yea. I think we're in agreement. As you said, we're not talking sampling here but have the entire population. When we test motors for performance (for example one of the tests is a critical test of variation of speed within one revolution while the motor is turning); I try to teach people to look not just at the numbers (which indicate pass/fail) but at the waveforms of the tester (which indicate something of the nature of the defect causing the variation). That leads more or less quickly to the solution of fixing the variation. Which is to say, as we all know from watching someone new get into casting, that there are a number of variables we play with, and it's a fun game learning at least how to gain consistancy to control the process and hopefully to learn what each of the variables influences. You've started a very good discussion here, thanks! | |||
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Quote: That is correct assuming that normal variation will cause a normal distribution. What I'm saying is that when, either with a population or with a large enough sample of a larger population, there is something else than a normal distribution, there is a reason for that difference. For example a reasonable test would be to do two runs of casting say 100 boolets each. With one run keep the temperature as level as possible, with the other increase the temperature over the run. The variation in weight over the distribution should be measurable and correlated to the change in temperature. The control group may or may not have a 'normal' distribution - but that would be for other reasons. So what are the things that may cause a varaition in weight in casting boolets? Several things come to mind immediately. Temperature of both the mould and of the alloy. Rounding of edges. Inclusion of foriegn material in the alloy. Presence or absence of wrinkles. Gaps internally from shrinkage. Variation in pressure and rate of fill. Look at Bruce B's comments and techniques. He's reported in detail the results of his methods. | |||
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I thought I knew what this was, but now don't. There are 20 bullet weights of each mold. Is that all that were cast in the session? Or are these 20 a sample? Please advise. joe b. Quote: | |||
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Gents, With all due respect to those who have made a career out of the "numbers", I am oft reminded of the following; "Their are lies, damned lies, and then there's statistics". (  )All figures can be manipulated to produce desired results, The converse is true as well. Cheers, R*2 | |||
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Quote: Well, R*2, the difference between opinion and fact is those pesky numbers. And in fact, it is not true to say that "All figures can be manipulated to produce desired results, The converse is true as well." Vioxx is off the market. joe b. | |||
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Hello Joe- The numbers are from 10 consecutive cycles, each from a double cavity mould. The moulds were brought up to temp and my casting rythm established. The bullets were then collected from the consecutive cycles and measured. The same process was used for each of the three moulds represented. Best regards- Sky C. | |||
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