- Email: [email protected]
Quality management II (SPC 1)
Quality Management II (SPC by John B. Durkee
n the January 2003 column, we provided a simple and scientific basis for answering the following questions: Question #l. If all your parts look and feel the same, how do you tell which, if any, are clean? Question #2. If the data coming from your cleaning test show the desired performance, how do you know any of those numbers mean anything? The basis was the t-test. This is a statistical routine, which can be run by today’s spreadsheets. It tells you the chance that two groups of data are equivalent, or not, by computing their averages and examining how individual data vary from those averages. Question #4. If your process is running today apparently as it was running yesterday, has anything changed. And, do you care? Question #4 will be answered in a subsequent column. e will find another and different Question #3. If a vat of aqueous cleaning juice always looks gray, how do we know when it is spent? My answer for your consideration is to measure the dynamic surface tension of the aqueous cleaning bath and use the cumulative sum (CUSUM) technique to track that variable versus results of past tests. I want to introduce two not-new technologies. Each has been used commercially for at least one generation. The techniques are measurement of dynamic surface tension and monitoring of process performance via CUSUM. To my knowledge, neither technique has been used at a significant extent in industrial parts washing. “Man is a tool-using animal nothing, with tools he is all.“l OF DYNAMIC
. . . Without tools he is
face, we have to pull molecules up to the surface against this one-sided attraction. The work done in creating one unit of surface area is called surface tension. Water, at ambient temperature, has a high surface tension in the range of 72 dynes/cm (d/cm). Organic chemicals, typically, are in the 20 to 30 d/cm range. Any substance dissolved in the liquid will affect the intermolecular forces and, hence, the surface tension. Some substances have the property of accumulating on the surface and dramatically altering surface tension even at low concentrations: they are appropriately called surfactants. If a formulation changes then the surface tension will change. The presence of another chemical, or a contaminant, will change the surface tension. Measuring surface tension is a direct indicator of the quality of any chemical or formulation. Reduction of surface tension takes several seconds. The formulation eventually reaches equilibrium (static) surface tension. While the solution is reaching equilibrium, operation is in the dynamic zone. The measurement is dynamic surface tension The behavior is shown in Figure 1. The approach is asymptotic. Classical surface tension methods, such as the DeNouy Ring, work with a dead or static surface. The gas/liquid in.terface has reache MEASURING
DYNAMIC
SUR
A controlled flow of nitrogen flows through a tube into a cell full of hquid. A bubble is produced. Its size is the diameter of the tube. Internal pressure in the bubble is measured. This is the raw data. Surface tension is calculated from a force balance:
SURFACE TENSION
Molecules in a liquid are subjected to attraction by surrounding molecules. In the bulk of the liquid, the field is symmetrical and has no net effect. At the surface, however, the surface molecules are pulled in towards the bulk of the liquid. If we wish to increase the area at gas/liquid interJohn B. Durkee is President ofCreative EnterpriZes, a consulting firm located in Kerrville, Texas. E-mail, [email protected].
(Internal pressure -bulk liquid pressure) = 2 x (surface tension)/(bubble radius) Actually, two tubes of different sizes are used simultaneously. The two force balance equations can be subtracted, and the effect of bulk liquid pressure is cancelled. In this way measurements can be made in microgravity or at high pressure. In use, bubble flow rate is decreased and the time of diffusion of surfactants to the surface increases. -
March
2003
55
Flgure 1. Dynamic surface tension.
Consequently, the measured dynamic surface tension decreases as the mixture at the surface becomes richer. A data set contains measurements of dynamic surface tension at various diffusion times or surface ages. This takes less than 1 minute to achieve. A plot of the data set shows asymptotic decline of surface tension with increasing surface age. See Figure 2 for a plot of data for a generalized water-soluble solvent. The static surface tension is about 48 d/cm for this situation. Laboratory data were taken by one supplier of equipment at 20°C for several water-soluble lubricants. One product, used for stamping operations,
Figure 2. Dynamic surface tension data (asymptotic
56
behavior).
was diluted by a factor of 200 to l(O.5 ~01% or 5,000 ppm). The dynamic and static surface tension were measured. Results are plotted in Figure 3. Please note the similarity to expected asymptotic behavior. This lubricant had never been tested, and the measurement conditions (orifice diameter and bubble flow rate) were not optimized for it. Please note that the time to measure another value of static surface tension is only a few seconds. Additional tests were conducted at a dilution of 2,000 to 1 (0.05 ~01%or 500 ppm). Test purpose was to learn about the detection sensitivity versus product dilution. Results are plotted in Figure 4. The plot has the expected shape and shows feasibility for operation at low concentration (high dilution). Obviously, some optimization of bubble flow rate and orifice diameter are necessary for commercial operation with this product. Please recall the surface tension of pure water is approximately 72 d/cm. The pure product has a value of approximately 30 d/cm. Data for the pure components and the two intermediate dilutions are shown in Figure 5. It appears that results from the two intermediate dilutions are consistent with values from the pure components. Sensitivity appears to be several hundred ppm by volume. Since a cleaning bath typically operates at a few percent concentration, or less, and the rinsing bath
Figure 3. Dynamic of 200 to 1).
surface tension
data (calibration
at dilution
Metal Finishing
3.
4.
5.
6.
high soil loading would not be a good application. b. It is likely that a caustic-based system will produce a small amount of emulsion. I believe a small amount of emulsion can be tolerated. The sample must be clean. Basically, this means free of particles, which might plug the tube or affect its diameter. There can be no polymerization ongoing. The additives must not coat the tube. The force balance would contain the wrong size information about the bubble. The temperature must be relatively constant. In fact, a good instrument should also measure the temperature. Surface tension changes reciprocal to temperature. There must be enough of the surfactant present to affect the measured surface tension (see Fig. 5).
MONITORING Figure 4. Dynamic surface tension data (calibration of 2,000 to 1).
at dilution
operates at several hundred ppm, or less, it appears that dynamic surface tension may be used with this lubricant in both process zones. An integrated instrument from one supplier costs around $9,000 with electronic output. There is a rent-to-own program where the rental fee is applied to purchase cost. LIMITATIONS
OF DYNAMIC
SURFACE TENSION
Measurement of dynamic surface tension in cleaning applications has the following limitations: 1. The sample must be single phase. Floating hydrocarbon materials compromise the measurement. That’s why this technique is never used in typical aqueous cleaning-removal of oils by caustic. a. A secondary concern is that cross-contamination with oil-soluble lubricants will produce a second phase. b. As long as a caustic-based cleaning system is used, some oils will be rendered watersoluble via saponification with caustic. As will be noted in my next column, the crosscontamination should be recognized by a change in the shape of the dynamic curve. 2. The single phase must be a solution, not an emulsion. The bonds between chemical impurity and water retard diffusion of the impurity because it is not free to migrate. a. A neutral-pH emulsifying cleaner with a March 2003
PROCESS
PERFORMANCE
WITH CUSURl
Control charts are used to routinely monitor quality. CUSUM is a type of control chart. There are two general causes of control instability: a shift in the aim point (mean, goal, or center line of the CUSUM chart) or shift in process variability. Assume a single quality characteristic, say surface tension, has been measured or computed from a sample. The control chart shows the value of the quality characteristic versus the sample number or versus time. In general, the chart contains a center line that represents the mean or goal value for the in-control process. Two other horizontal lines, called the upper control limit (UCL) and the lower control limit (LCL), are also shown on the chart. These control limits are chosen so that almost all of the data points will fall within these limits as long as the process remains in control. Please note: control limits are not specification limits. Control limits are used to determine if the
Figure 5. Surface tension versus composition ibration).
(water-soluble
cal-
57
process is producing consistent output. Specification limits are used to determine if the product will function in the intended fashion. In the U.S., it is an acceptable practice to base the control limits upon a multiple of the standard deviation. Often, this multiple is 3 and thus the limits are called 3-sigma limits. Values from 3 to 5 are commonly used. Narrower control limits can cause unnecessary reaction to short-term shifts in the measured variable. Unnecessary means that we think there is a real shift in the target aim point (mean) when that has not happened. If a data point falls outside the control limits, we assume that the process is probably out of control and that an investigation is warranted to find why the mean or variability have shifted. More than that, we would like to conduct that investigation before the process is probably out of control-so as to keep that from happening. The CUSUM chart does this because something other than the measured variable, say surface tension, is plotted. Instead, we plot the cumulative sum of the deviations of individual samples from the mean or goal value. It can be very, as we learned with the t-test, if averages of a few data points are plotted and not the individual data. The CUSUM technique is very sensitive to subtle shifts in the point of aim (mean). The CUSUM technique is very insensitive to random variations in the point of aim. Formulas for calculating the continuing sum of deviations from the mean are:
Off aim (mean) cleaning operation will eventually produce parts that are too dirty to use. CUSUM recognizes this situation before it happens. Comparison to UCL and LCL are the trigger points for corrective action before it is needed. The equations used in CUSUM were given above. While simple in form, the published nomenclature is easy to misunderstand or misuse. Here are the equations and terms: 0 C is Cumulative Sum (CUSUM) ?? p0 is the largest aim point (mean) 0 x. is the current observation ?? i is the count of observations (ith) * K is a constant. It is a “tuning parameter.” Decreasing values of K delay the time response of the CUSUM variable for a given difference between the target aim point (mean) and the current observation. 0 A typical value of K is one half (used in Table I>the standard deviation of the measured variable. ?? Set K to zero to plot the actual difference between measured variable and aim point (mean). 0 xi - (p. + K) is the “tuned” error. There would be no error if the measured variable equaled the aim point (mean>. 0 The max (0 ) . . . . . . .) function means to choose the largest of 0 or . . . . . . . Cfi = max [O, q - (uO+ K) + C+i_ll 111
C+i = max [O, X; - (uo + K) + C+i_,] [l] Cmi= max [O, (uc - K) - xi + C-i_1l[Zl CREATING CUSUM CHARTS
Test runs 8 through 16, in Table I, show a sustained but small shift of the measured dynamic surface tension above the aim point (mean). This produces a shift upward in CUSUM. Test runs 1 through 7 and 17 through 30 show nearly pure random oscillation around the man. This produces little upward or downward change in CUSUM. Figures 6,7, and 8, produced from the same data as in Table I, show the power of CUSUM process control. That power is to differentiate continuous operating time spent off the mean from random variation about the mean. 58
Figure 6. CUSUM
anticipation
(prevents excursion of limits).
Metal Finishing
Equation 111 (for C’) is operable greater than u,,.
only when xi is
Ci = m-~ [O, (u. - K) - xi + C-i_ll 121 Equation 121 (for C-> is operable only when xi is less than po. Whichever equation is used, a difference between the measured variable xi and the “tuned” aim point (p. +K) is algebraically added to the current value of CUSUM. Note that in calculating C, the sign of K is always positive. It always acts to delay or depress the contribution “tuned” error to CUSUM. Finally, note that CUSUM does not change if the
March 2003
measured variable xi does not change. In other words, CUSUM does not reward continued and stable off-aim operation
There are a half-dozen common techniques for creating control charts to manage product quality. Plotting the measured variable is the simplest. This can be done with control limits, but no direct warning is provided in advance of loss of control. During the 1920s Walter A. Shewhart proposed a general model for control charts. Basically, Shewhart charts are plots with running averages of the measured variable with the control limits from 59
Figure 7. CUSUM
anticipation
(prevents excursion of limits).
the center line, expressed in terms of standard deviation units. The main drawback of Shewhart charts is that they only use the information about the process contained in the last data point. The second drawback is they best monitor large changes in the measured variable. CUSUM charts employ the concept of control limits with plots of cumulative deviation from the aim point. Hence, information contained in all points is used. They are better suited for monitoring small changes in the measured variable. Exponentially Weighed Moving Averages (EWMA) charts are similar to CUSUM charts except they have a factor similar to K, which accelerates the response when the measured variable is off-aim. EWMA charts are better suited to managing rapid small changes in the measured variable. I recommend CUSUM charts for monitoring of cleaning processes because: (1) the changes are very small from the mean and (2) they don’t happen very fast (hr vs set). There are three major factors, IMO, which have limited use of CUSUM charts in cleaning operations. The first is that they are perceived to be complex to use. One purpose of this column is to show that they can be simple to use and understand. The second factor is that they can give “false alarms.” Overly narrow control limits will foster false alarms. Overly broad control limits will foster somnambulance-a belief that things are copacetic, when they are not. Either will diminish the credibility of the technique 60
Figure 8. CUSUM
anticipation
(prevents excursion of limits).
in the eyes of management. Successful use of CUSUM nearly always requires some tuning of the UCL and LCL over the range of 3 to 5 standard deviations. PUTTING IT ALL TGGETRER
The third major factor limiting use of CUSUM charts in cleaning operations is that there is a shortage of suitable control variables. Dynamic surface tension can be that variable if the above limitations don’t dominate. That’s what excites me! In some cases we can now control cleaning operations in metal finishing using real engineering tools. Today, many cleaning baths are changed after a fixed number of hours or days (without regard to the parts or soil load) or when the bath reaches a certain color or aroma. “The manipulation of statistical formulas substitute for knowing what one is doing.@
is no
In the final column of this series, we will show how CUSUM and dynamic surface tension are used together to improve process operation. And we’ll show what benefits come about from so doing. INTERESTING
NEW STUFF
There are four legal and product issues we are following. Three pertain to solvent cleaning, and the other pertains to aqueous cleaning. Nonhalogenated Solvents You knew it was going to happen. We’re out of the
“normally-structured” products. Recently, a Japanese firm (Kurary) introduced Metal Finishing
through their U.S. trading partner (CRC America) a new cleaning solvent. What’s unique about that is that the solvent doesn’t contain any halogens (chloride, bromide, or fluoride). Not to say there will never be another new halogenated cleaning solvent. But if there were a valuable new general purpose halogenated cleaning solvent, wouldn’t it have made its appearance by now? Perhaps the next generation of cleaning solvents will come from: (1) nonhalogenated chemicals, and
(2) chemicals not now considered as potential cleaning solvents. The recently introduced product is 3-methoxy-3methyl-butanol, known as 33B. ucb remains to be known about it, but Table II shows what I have been able to learn. 33B appears to be a versatile solvent because it has both an ether group and an alcoholic bydroxy group (see Fig. 9). The manufacturer claims that 33B solvates both polar and nonpolar soils
DOES YOUR WATER TREATMENT SYSTEM ALWAYS KEEP YOU IN COMPLIANCE? TIRED OF WALKING THAT FINE LINE OF BEING IN OR OUT OF COMPLIANC
ELIMINATE THESE PROBLEMS AND WORRIES IN 128 S
So just how important are these 128 seconds?
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Figure
9. Structure
of 338.
Complete water solubility extends the range of use. A flash point above 140°F wins the coveted Class IIIA NFPA rating. I was not able to locate an exposure limit, and received little cooperation from the distributor. Although I am not a toxicologist, health testing with animals does not suggest the need for abnormal concern. The main drawback is one shared with nMethyl pyrrolidone (NMP)-poor drying rate. 33B would not be a good wipe cleaning solvent despite the good flash point. High boiling point would limit its use as a vapor degreasing solvent versus trans 1,2-dichloroethane. For the same reason it is not a replacement for HCFC 141 b. Halogenated
Solvents
Speaking of HCFC 141b, don’t unless you bring your wallet. On January 1, the U.S. EPA’s U.S. production
ban went into effect-because it is an ozone depleting compound (ODC). That doesn’t mean you can’t buy HCFC 141b. There are reputed to be large surpluses of it throughout the balance of 2003. Expect to pay for the privilege of purchase. In 2004 you may need an “Abie” (a $5 bill) to purchase one pound. So what are your options? Short term-wring out all the defects in your unit and operating procedures, which increase use rate. Long term-plan to switch to something. Perhaps n-propyl bromide or a blend or azeotrope of solvents? N-PropyI Bromide (nPB) Well, to do that, the U.S. EPA has to complete a task it started back in 1995. That is to produce a Significant New Alternatives Program (SNAP) decision about exposure limits and areas of application. Don’t be confused by the SNAP decision-you can use nPB today, at whatever exposure limit (CEL or AEL) is recommended by the manufacturer. But absence of the SNAP decision has thwarted plans for achievement of significant sales volumes. Few firms want to convert to a product and find out that the EPA’s exposure limit is 1/4of the CEL. Today, two manufacturers (Great Lakes and Albemarle) have reduced the intensity of their expenses and efforts. The third manufacturer of bromine-based products (Dead Seas) has a U.S. dis-
1000 Gal. PE 45” cone bottom tank 2 expandable to 4 cu. ft. filler press ??4 hp air mixer & 1” diaphragm pump ??Analyzers, sensors, pumps available ??6’xlO’skid with piping, ladder & platform ??
??
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tributor (Poly Systems). Technical personnel formerly with the other firms now work there. Their technical focus seems to be on blends with pentafluoro butane and azeotropes-to reduce effective exposure and solvation on plastics. Their political focus seems to be on telling the U.S. EPA that they have no jurisdiction to set exposure limits. They hope OSHA will be more lenient to manufacturers. While this may offer temporary relief to suppliers, in the long run it is a waste of effort. The exposure limit, called threshold limit Value (TLV), set by the American Conference of Government Industrial Hygienists (ACGIH) is the one to which others will converge.
Did you get a Valentine’s Day gift? If you do, or are considering doing, aqueous cleaning, you may have gotten one without knowing it. Since 1994, the U.S. EPA has been drafting and receiving comments on a major rewriting of the regulations governing management of water discharges. Fourteen major U.S. industries were to have been involved. In 1997, the first half of the new regulation was withdrawn because public comments said it was unfair, too costly, and based on poor technology and data. In 2001, the EPA made a proposal for regulation for all fourteen industries, asked for comment. Later they asked for effluent data to better define the problem and possible solutions. In June 2002, an Agency official conceded during a
public meeting that the original assumptions regarding the economic impact and environmental benefits of a proposed Metal Products and Machinery (MP&M) rule were flawed and would cause the agenc;yito significantly revise any final rule. A final ruling by the EPA was planned for late November 2002. To my surprise, and that of others, the agency was able to get an agreement with the Natural Resources Defense Council to push back the rulemaking to Feb. 14, 2003. The reason given was “... new data and inaccuracies in the old data...“. Although this is written before Valentine’s Day, discussion in the finishing industries is about no new limits requ.ired from the MP M rule. The editor will no doubt cover this in ge ral in the April issue, and I will discuss its application to cleaning in the May issue. While politics are no doubt a part of every rule made by every agency, there is a solid Lesson here. Our system of laws made by Congress and regulations made by Agencies worked. A regulation based on inaccurate data wasn’t released. A regulation whose consequences weren’t cost-effective wasn’t released. Industry comments based on provable facts, and not fears, had a dominant effect. REFERENCES 1. Carlyle,Thomas
2. Blalock,H.M. Jr., Social Statistics,2nd ed; 1972
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n the January 2003 column, we provided a simple and scientific basis for answering the following questions: Question #l. If all your parts look and feel the same, how do you tell which, if any, are clean? Question #2. If the data coming from your cleaning test show the desired performance, how do you know any of those numbers mean anything? The basis was the t-test. This is a statistical routine, which can be run by today’s spreadsheets. It tells you the chance that two groups of data are equivalent, or not, by computing their averages and examining how individual data vary from those averages. Question #4. If your process is running today apparently as it was running yesterday, has anything changed. And, do you care? Question #4 will be answered in a subsequent column. e will find another and different Question #3. If a vat of aqueous cleaning juice always looks gray, how do we know when it is spent? My answer for your consideration is to measure the dynamic surface tension of the aqueous cleaning bath and use the cumulative sum (CUSUM) technique to track that variable versus results of past tests. I want to introduce two not-new technologies. Each has been used commercially for at least one generation. The techniques are measurement of dynamic surface tension and monitoring of process performance via CUSUM. To my knowledge, neither technique has been used at a significant extent in industrial parts washing. “Man is a tool-using animal nothing, with tools he is all.“l OF DYNAMIC
. . . Without tools he is
face, we have to pull molecules up to the surface against this one-sided attraction. The work done in creating one unit of surface area is called surface tension. Water, at ambient temperature, has a high surface tension in the range of 72 dynes/cm (d/cm). Organic chemicals, typically, are in the 20 to 30 d/cm range. Any substance dissolved in the liquid will affect the intermolecular forces and, hence, the surface tension. Some substances have the property of accumulating on the surface and dramatically altering surface tension even at low concentrations: they are appropriately called surfactants. If a formulation changes then the surface tension will change. The presence of another chemical, or a contaminant, will change the surface tension. Measuring surface tension is a direct indicator of the quality of any chemical or formulation. Reduction of surface tension takes several seconds. The formulation eventually reaches equilibrium (static) surface tension. While the solution is reaching equilibrium, operation is in the dynamic zone. The measurement is dynamic surface tension The behavior is shown in Figure 1. The approach is asymptotic. Classical surface tension methods, such as the DeNouy Ring, work with a dead or static surface. The gas/liquid in.terface has reache MEASURING
DYNAMIC
SUR
A controlled flow of nitrogen flows through a tube into a cell full of hquid. A bubble is produced. Its size is the diameter of the tube. Internal pressure in the bubble is measured. This is the raw data. Surface tension is calculated from a force balance:
SURFACE TENSION
Molecules in a liquid are subjected to attraction by surrounding molecules. In the bulk of the liquid, the field is symmetrical and has no net effect. At the surface, however, the surface molecules are pulled in towards the bulk of the liquid. If we wish to increase the area at gas/liquid interJohn B. Durkee is President ofCreative EnterpriZes, a consulting firm located in Kerrville, Texas. E-mail, [email protected].
(Internal pressure -bulk liquid pressure) = 2 x (surface tension)/(bubble radius) Actually, two tubes of different sizes are used simultaneously. The two force balance equations can be subtracted, and the effect of bulk liquid pressure is cancelled. In this way measurements can be made in microgravity or at high pressure. In use, bubble flow rate is decreased and the time of diffusion of surfactants to the surface increases. -
March
2003
55
Flgure 1. Dynamic surface tension.
Consequently, the measured dynamic surface tension decreases as the mixture at the surface becomes richer. A data set contains measurements of dynamic surface tension at various diffusion times or surface ages. This takes less than 1 minute to achieve. A plot of the data set shows asymptotic decline of surface tension with increasing surface age. See Figure 2 for a plot of data for a generalized water-soluble solvent. The static surface tension is about 48 d/cm for this situation. Laboratory data were taken by one supplier of equipment at 20°C for several water-soluble lubricants. One product, used for stamping operations,
Figure 2. Dynamic surface tension data (asymptotic
56
behavior).
was diluted by a factor of 200 to l(O.5 ~01% or 5,000 ppm). The dynamic and static surface tension were measured. Results are plotted in Figure 3. Please note the similarity to expected asymptotic behavior. This lubricant had never been tested, and the measurement conditions (orifice diameter and bubble flow rate) were not optimized for it. Please note that the time to measure another value of static surface tension is only a few seconds. Additional tests were conducted at a dilution of 2,000 to 1 (0.05 ~01%or 500 ppm). Test purpose was to learn about the detection sensitivity versus product dilution. Results are plotted in Figure 4. The plot has the expected shape and shows feasibility for operation at low concentration (high dilution). Obviously, some optimization of bubble flow rate and orifice diameter are necessary for commercial operation with this product. Please recall the surface tension of pure water is approximately 72 d/cm. The pure product has a value of approximately 30 d/cm. Data for the pure components and the two intermediate dilutions are shown in Figure 5. It appears that results from the two intermediate dilutions are consistent with values from the pure components. Sensitivity appears to be several hundred ppm by volume. Since a cleaning bath typically operates at a few percent concentration, or less, and the rinsing bath
Figure 3. Dynamic of 200 to 1).
surface tension
data (calibration
at dilution
Metal Finishing
3.
4.
5.
6.
high soil loading would not be a good application. b. It is likely that a caustic-based system will produce a small amount of emulsion. I believe a small amount of emulsion can be tolerated. The sample must be clean. Basically, this means free of particles, which might plug the tube or affect its diameter. There can be no polymerization ongoing. The additives must not coat the tube. The force balance would contain the wrong size information about the bubble. The temperature must be relatively constant. In fact, a good instrument should also measure the temperature. Surface tension changes reciprocal to temperature. There must be enough of the surfactant present to affect the measured surface tension (see Fig. 5).
MONITORING Figure 4. Dynamic surface tension data (calibration of 2,000 to 1).
at dilution
operates at several hundred ppm, or less, it appears that dynamic surface tension may be used with this lubricant in both process zones. An integrated instrument from one supplier costs around $9,000 with electronic output. There is a rent-to-own program where the rental fee is applied to purchase cost. LIMITATIONS
OF DYNAMIC
SURFACE TENSION
Measurement of dynamic surface tension in cleaning applications has the following limitations: 1. The sample must be single phase. Floating hydrocarbon materials compromise the measurement. That’s why this technique is never used in typical aqueous cleaning-removal of oils by caustic. a. A secondary concern is that cross-contamination with oil-soluble lubricants will produce a second phase. b. As long as a caustic-based cleaning system is used, some oils will be rendered watersoluble via saponification with caustic. As will be noted in my next column, the crosscontamination should be recognized by a change in the shape of the dynamic curve. 2. The single phase must be a solution, not an emulsion. The bonds between chemical impurity and water retard diffusion of the impurity because it is not free to migrate. a. A neutral-pH emulsifying cleaner with a March 2003
PROCESS
PERFORMANCE
WITH CUSURl
Control charts are used to routinely monitor quality. CUSUM is a type of control chart. There are two general causes of control instability: a shift in the aim point (mean, goal, or center line of the CUSUM chart) or shift in process variability. Assume a single quality characteristic, say surface tension, has been measured or computed from a sample. The control chart shows the value of the quality characteristic versus the sample number or versus time. In general, the chart contains a center line that represents the mean or goal value for the in-control process. Two other horizontal lines, called the upper control limit (UCL) and the lower control limit (LCL), are also shown on the chart. These control limits are chosen so that almost all of the data points will fall within these limits as long as the process remains in control. Please note: control limits are not specification limits. Control limits are used to determine if the
Figure 5. Surface tension versus composition ibration).
(water-soluble
cal-
57
process is producing consistent output. Specification limits are used to determine if the product will function in the intended fashion. In the U.S., it is an acceptable practice to base the control limits upon a multiple of the standard deviation. Often, this multiple is 3 and thus the limits are called 3-sigma limits. Values from 3 to 5 are commonly used. Narrower control limits can cause unnecessary reaction to short-term shifts in the measured variable. Unnecessary means that we think there is a real shift in the target aim point (mean) when that has not happened. If a data point falls outside the control limits, we assume that the process is probably out of control and that an investigation is warranted to find why the mean or variability have shifted. More than that, we would like to conduct that investigation before the process is probably out of control-so as to keep that from happening. The CUSUM chart does this because something other than the measured variable, say surface tension, is plotted. Instead, we plot the cumulative sum of the deviations of individual samples from the mean or goal value. It can be very, as we learned with the t-test, if averages of a few data points are plotted and not the individual data. The CUSUM technique is very sensitive to subtle shifts in the point of aim (mean). The CUSUM technique is very insensitive to random variations in the point of aim. Formulas for calculating the continuing sum of deviations from the mean are:
Off aim (mean) cleaning operation will eventually produce parts that are too dirty to use. CUSUM recognizes this situation before it happens. Comparison to UCL and LCL are the trigger points for corrective action before it is needed. The equations used in CUSUM were given above. While simple in form, the published nomenclature is easy to misunderstand or misuse. Here are the equations and terms: 0 C is Cumulative Sum (CUSUM) ?? p0 is the largest aim point (mean) 0 x. is the current observation ?? i is the count of observations (ith) * K is a constant. It is a “tuning parameter.” Decreasing values of K delay the time response of the CUSUM variable for a given difference between the target aim point (mean) and the current observation. 0 A typical value of K is one half (used in Table I>the standard deviation of the measured variable. ?? Set K to zero to plot the actual difference between measured variable and aim point (mean). 0 xi - (p. + K) is the “tuned” error. There would be no error if the measured variable equaled the aim point (mean>. 0 The max (0 ) . . . . . . .) function means to choose the largest of 0 or . . . . . . . Cfi = max [O, q - (uO+ K) + C+i_ll 111
C+i = max [O, X; - (uo + K) + C+i_,] [l] Cmi= max [O, (uc - K) - xi + C-i_1l[Zl CREATING CUSUM CHARTS
Test runs 8 through 16, in Table I, show a sustained but small shift of the measured dynamic surface tension above the aim point (mean). This produces a shift upward in CUSUM. Test runs 1 through 7 and 17 through 30 show nearly pure random oscillation around the man. This produces little upward or downward change in CUSUM. Figures 6,7, and 8, produced from the same data as in Table I, show the power of CUSUM process control. That power is to differentiate continuous operating time spent off the mean from random variation about the mean. 58
Figure 6. CUSUM
anticipation
(prevents excursion of limits).
Metal Finishing
Equation 111 (for C’) is operable greater than u,,.
only when xi is
Ci = m-~ [O, (u. - K) - xi + C-i_ll 121 Equation 121 (for C-> is operable only when xi is less than po. Whichever equation is used, a difference between the measured variable xi and the “tuned” aim point (p. +K) is algebraically added to the current value of CUSUM. Note that in calculating C, the sign of K is always positive. It always acts to delay or depress the contribution “tuned” error to CUSUM. Finally, note that CUSUM does not change if the
March 2003
measured variable xi does not change. In other words, CUSUM does not reward continued and stable off-aim operation
There are a half-dozen common techniques for creating control charts to manage product quality. Plotting the measured variable is the simplest. This can be done with control limits, but no direct warning is provided in advance of loss of control. During the 1920s Walter A. Shewhart proposed a general model for control charts. Basically, Shewhart charts are plots with running averages of the measured variable with the control limits from 59
Figure 7. CUSUM
anticipation
(prevents excursion of limits).
the center line, expressed in terms of standard deviation units. The main drawback of Shewhart charts is that they only use the information about the process contained in the last data point. The second drawback is they best monitor large changes in the measured variable. CUSUM charts employ the concept of control limits with plots of cumulative deviation from the aim point. Hence, information contained in all points is used. They are better suited for monitoring small changes in the measured variable. Exponentially Weighed Moving Averages (EWMA) charts are similar to CUSUM charts except they have a factor similar to K, which accelerates the response when the measured variable is off-aim. EWMA charts are better suited to managing rapid small changes in the measured variable. I recommend CUSUM charts for monitoring of cleaning processes because: (1) the changes are very small from the mean and (2) they don’t happen very fast (hr vs set). There are three major factors, IMO, which have limited use of CUSUM charts in cleaning operations. The first is that they are perceived to be complex to use. One purpose of this column is to show that they can be simple to use and understand. The second factor is that they can give “false alarms.” Overly narrow control limits will foster false alarms. Overly broad control limits will foster somnambulance-a belief that things are copacetic, when they are not. Either will diminish the credibility of the technique 60
Figure 8. CUSUM
anticipation
(prevents excursion of limits).
in the eyes of management. Successful use of CUSUM nearly always requires some tuning of the UCL and LCL over the range of 3 to 5 standard deviations. PUTTING IT ALL TGGETRER
The third major factor limiting use of CUSUM charts in cleaning operations is that there is a shortage of suitable control variables. Dynamic surface tension can be that variable if the above limitations don’t dominate. That’s what excites me! In some cases we can now control cleaning operations in metal finishing using real engineering tools. Today, many cleaning baths are changed after a fixed number of hours or days (without regard to the parts or soil load) or when the bath reaches a certain color or aroma. “The manipulation of statistical formulas substitute for knowing what one is doing.@
is no
In the final column of this series, we will show how CUSUM and dynamic surface tension are used together to improve process operation. And we’ll show what benefits come about from so doing. INTERESTING
NEW STUFF
There are four legal and product issues we are following. Three pertain to solvent cleaning, and the other pertains to aqueous cleaning. Nonhalogenated Solvents You knew it was going to happen. We’re out of the
“normally-structured” products. Recently, a Japanese firm (Kurary) introduced Metal Finishing
through their U.S. trading partner (CRC America) a new cleaning solvent. What’s unique about that is that the solvent doesn’t contain any halogens (chloride, bromide, or fluoride). Not to say there will never be another new halogenated cleaning solvent. But if there were a valuable new general purpose halogenated cleaning solvent, wouldn’t it have made its appearance by now? Perhaps the next generation of cleaning solvents will come from: (1) nonhalogenated chemicals, and
(2) chemicals not now considered as potential cleaning solvents. The recently introduced product is 3-methoxy-3methyl-butanol, known as 33B. ucb remains to be known about it, but Table II shows what I have been able to learn. 33B appears to be a versatile solvent because it has both an ether group and an alcoholic bydroxy group (see Fig. 9). The manufacturer claims that 33B solvates both polar and nonpolar soils
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Figure
9. Structure
of 338.
Complete water solubility extends the range of use. A flash point above 140°F wins the coveted Class IIIA NFPA rating. I was not able to locate an exposure limit, and received little cooperation from the distributor. Although I am not a toxicologist, health testing with animals does not suggest the need for abnormal concern. The main drawback is one shared with nMethyl pyrrolidone (NMP)-poor drying rate. 33B would not be a good wipe cleaning solvent despite the good flash point. High boiling point would limit its use as a vapor degreasing solvent versus trans 1,2-dichloroethane. For the same reason it is not a replacement for HCFC 141 b. Halogenated
Solvents
Speaking of HCFC 141b, don’t unless you bring your wallet. On January 1, the U.S. EPA’s U.S. production
ban went into effect-because it is an ozone depleting compound (ODC). That doesn’t mean you can’t buy HCFC 141b. There are reputed to be large surpluses of it throughout the balance of 2003. Expect to pay for the privilege of purchase. In 2004 you may need an “Abie” (a $5 bill) to purchase one pound. So what are your options? Short term-wring out all the defects in your unit and operating procedures, which increase use rate. Long term-plan to switch to something. Perhaps n-propyl bromide or a blend or azeotrope of solvents? N-PropyI Bromide (nPB) Well, to do that, the U.S. EPA has to complete a task it started back in 1995. That is to produce a Significant New Alternatives Program (SNAP) decision about exposure limits and areas of application. Don’t be confused by the SNAP decision-you can use nPB today, at whatever exposure limit (CEL or AEL) is recommended by the manufacturer. But absence of the SNAP decision has thwarted plans for achievement of significant sales volumes. Few firms want to convert to a product and find out that the EPA’s exposure limit is 1/4of the CEL. Today, two manufacturers (Great Lakes and Albemarle) have reduced the intensity of their expenses and efforts. The third manufacturer of bromine-based products (Dead Seas) has a U.S. dis-
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tributor (Poly Systems). Technical personnel formerly with the other firms now work there. Their technical focus seems to be on blends with pentafluoro butane and azeotropes-to reduce effective exposure and solvation on plastics. Their political focus seems to be on telling the U.S. EPA that they have no jurisdiction to set exposure limits. They hope OSHA will be more lenient to manufacturers. While this may offer temporary relief to suppliers, in the long run it is a waste of effort. The exposure limit, called threshold limit Value (TLV), set by the American Conference of Government Industrial Hygienists (ACGIH) is the one to which others will converge.
Did you get a Valentine’s Day gift? If you do, or are considering doing, aqueous cleaning, you may have gotten one without knowing it. Since 1994, the U.S. EPA has been drafting and receiving comments on a major rewriting of the regulations governing management of water discharges. Fourteen major U.S. industries were to have been involved. In 1997, the first half of the new regulation was withdrawn because public comments said it was unfair, too costly, and based on poor technology and data. In 2001, the EPA made a proposal for regulation for all fourteen industries, asked for comment. Later they asked for effluent data to better define the problem and possible solutions. In June 2002, an Agency official conceded during a
public meeting that the original assumptions regarding the economic impact and environmental benefits of a proposed Metal Products and Machinery (MP&M) rule were flawed and would cause the agenc;yito significantly revise any final rule. A final ruling by the EPA was planned for late November 2002. To my surprise, and that of others, the agency was able to get an agreement with the Natural Resources Defense Council to push back the rulemaking to Feb. 14, 2003. The reason given was “... new data and inaccuracies in the old data...“. Although this is written before Valentine’s Day, discussion in the finishing industries is about no new limits requ.ired from the MP M rule. The editor will no doubt cover this in ge ral in the April issue, and I will discuss its application to cleaning in the May issue. While politics are no doubt a part of every rule made by every agency, there is a solid Lesson here. Our system of laws made by Congress and regulations made by Agencies worked. A regulation based on inaccurate data wasn’t released. A regulation whose consequences weren’t cost-effective wasn’t released. Industry comments based on provable facts, and not fears, had a dominant effect. REFERENCES 1. Carlyle,Thomas
2. Blalock,H.M. Jr., Social Statistics,2nd ed; 1972
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