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1、TIP 0404-26 ISSUED 1982 REVISED 1987 REVISED 1992 WITHDRAWN 2001 REVISED AND REINSTATED 2001 2001 TAPPI The information and data contained in this document were prepared by a technical committee of the Association. The committee and the Association assume no liability or responsibility in connection
2、 with the use of such information or data, including but not limited to any liability or responsibility under patent, copyright, or trade secret laws. The user is responsible for determining that this document is the most recent edition published. TIP Category Automatically Periodically Reviewed (Te
3、n-year review) TAPPI Paper machine clothing performance analysis Scope Paper machine clothing traditionally has been evaluated by days life and cost per ton indices. Achievement of maximum clothing life and minimum cost per ton often results in significant reductions in paper machine operating perfo
4、rmance. Sacrifices in machine performance to reduce clothing costs can reduce total mill profitability significantly. Alternate clothing evaluation techniques based on impact on paper machine performance have been developed. These techniques relate key operating parameters to the clothing run. Two t
5、echniques which have proven useful over a broad spectrum of machines are described. The techniques are most beneficial when clothing performance is monitored over several months or years. Safety precautions . No specific safety requirements apply to this TIP. Mill safety requirements should be follo
6、wed when installing monitoring devices or collecting information relative to press section clothing. Content NOTE 1: See Table 1 for SI metric conversion factors. Table 1. Conversion factors for Sl units Quantity Customary units Multiply by To obtain Length feet (ft) 0.3048 meters (m) Mass ounces (o
7、z) 28.3495 grams (g) pounds (lb) 0.45359 kilograms (kg) tons (=2000 lb) 0.90718 tonne (metric ton) (t) Significance The techniques described can be used to effectively manage paper machine clothing to optimize total paper machine economics. Clothing cost is relatively small when compared to the prof
8、its generated by added production. Good clothing management can improve mill profits by thousands of dollars per year. TIP 0404-26 Paper machine clothing performance analysis / 2 Definitions Period: The time span between any two clothing changes is a period. Periods normally do not have an equal num
9、ber of days. Clothing set: All of the pieces of clothing on the machine during a single period constitute a clothing set. Histogram: A histogram is an averaged, graphical display of key machine performance variables plotted against clothing installations. Each period appears as a rectangle whose hei
10、ght corresponds to the magnitude of the parameters being graphed. The rectangle width is proportional to the number of days the clothing set was run on the machine. Procedure Selection of variables to be monitored For optimum results, quantifiable key operating parameters upon which clothing perform
11、ance ca directly impact should be monitored. The key parameters vary for each machine, depending on available data and restrictions to production capacity. All data must be qualified on machines which run a variety of grades, furnishes, and speeds. A truly multiple-grade machine will be very difficu
12、lt to analyze accurately. For example, sheet moisture content (at constant speed and basis weight) leaving the press section is an excellent indication of press felt performance. However, a large percentage of machines do not have on-line moisture sensors at this location. Sheet moisture grab sample
13、s taken during regular, frequent intervals (weekly), can be used (on-line sensors are helpful but not a necessity). On drying limited machines, machine speed is a very good alternate to monitor. If the machine is limited by drive speed, and steam consumption is accurately measured, steam consumption
14、 per pound of paper may be a good alternate parameter to measure. . Key operating parameters, in order of impact by clothing performance for most paper machines, are as follows: Sheet moisture content leaving the press section. This is an excellent parameter to monitor since it is a direct indicatio
15、n of wet-end water removal. Machine speed. Average speed, maximum speed achieved, or percent of standard speed may be used, depending on available data. Pounds of steam per pound of paper dried. This is a good indicator of sheet moisture content leaving the press section. Number of breaks. Analysis
16、by machine section is desirable. For example, if forming fabric performance is being studied, breaks at the couch, in the wet presses, or on the wet end would be better than total machine breaks which may include reel change snapoffs. Production rate at the reel. Winder production should be avoided
17、since trim and cull losses may vary. Operating lost time. If total lost time is used, lost time due to mechanical and electrical problems should be excluded since they are not impacted by clothing performance. Difference in clothing change time between suppliers/designs could be significant. Machine
18、 efficiency. This measurement can be useful if clearly defined. It generally should be avoided since many variables which are not related to clothing performance affect efficiency. Efficiency after the winder is especially bad. Quality parameters Clothings effect on product quality is becoming incre
19、asingly important. Mills producing grades for certain markets may find this a key variable in charting clothing performance. The degree of wire or felt marking, first-pass 3 / Paper machine clothing performance analysis TIP 0404-26 solids, fines, or ash retention (affecting porosity, opacity, and tw
20、o-sidedness) are all quantifiable and can be included in an analysis. For all operating parameters, the data used must be accurate for optimum results. The clothing analysis can only be as good as the data used in the analysis. Sensors such as moisture gauges, steam flowmeters, and speed indicators
21、should be calibrated frequently. When number and location of breaks, including operating lost time, are logged manually, the machine crew personnel must report data accurately. Key independent process variables should be monitored and logged to see if they correlate with any observed changes in the
22、dependent variables being monitored on-machine. Otherwise, misleading conclusions could be reached. Example: A decrease in percent solids out of the press section may have been attributed to a felt change, when in reality it was caused by a dramatic freeness shift in the pulp mill. Again, the correc
23、t process variables to monitor are quite mill-specific. Possibilities include furnish component freenesses, headbox freeness, system temperature, and wet end charge. Significant mechanical problems and changes also should be logged. Mills with a great deal of process instability may find a good clot
24、hing analysis impossible to accomplish. Data collection Daily values of the parameters to be monitored are logged on a data sheet as shown in Table 2. For illustration, data from a news machine is shown. Clothing record Clothing changes and descriptive information are recorded on a clothing record s
25、heet. Existing mill records may be adequate. An example of a press section clothing record is shown in Table 3. -,-,- TIP 0404-26 Paper machine clothing performance analysis / 4 Table 2. Daily data sheet. Machine Mill Location Production Steam use, Machine Press Wet-end Date tons/day 1000 lb/day spe
26、ed, ft/min moisture breaks 1 256 1128 2500 59.0 2 2 255 1080 2490 59.2 3 3 226 1032 2510 59.3 0 4 278 1236 2580 59.3 4 5 266 1224 2570 59.0 2 6 245 1120 2370 59.5 3 7 256 1296 2480 59.7 5 8 186 1104 2470 59.4 4 9 110 1148 2540 59.6 2 10 247 1128 2390 59.8 6 11 257 1209 2490 59.5 1 12 217 1032 2400 5
27、8.9 3 13 255 1296 2470 58.8 4 14 245 1104 2490 59.2 2 15 149 1080 2180 59.2 3 16 116 844 2260 59.5 0 17 226 1132 2450 59.7 2 18 225 1080 2450 59.4 4 19 279 1224 2570 59.8 3 20 251 1224 2440 60.1 1 21 261 1080 2510 59.2 5 22 270 1132 2500 58.7 4 23 257 1128 2500 58.9 2 24 108 800 2100 58.9 2 25 119 6
28、48 2100 59.2 8 26 266 1200 2470 59.3 4 27 265 1132 2580 59.5 3 28 260 1132 2510 59.4 4 29 258 1080 2500 59.7 5 30 243 1032 2360 59.8 3 -,-,- 5 / Paper machine clothing performance analysis TIP 0404-26 Table 3. Clothing record. Press section ? Forming section Machine Mill Location Supplier Date Date
29、Position (% SYN) on off Days Design Pickup A-Felt (100) 1/1 1/10 9 ALPHA 3.5 oz B-Felt (100) 1/10 1/20 10 BROWN 3.6 oz C-Felt (100) 1/20 1/30 10 Thru mesh 3.6 oz 2nd press D-Felt (75) 1/1 1/9 8 XX-Fine 3.8 oz E-Felt (75) 1/9 1/18 9 Over mesh 3.8 oz F-Felt (75) 1/18 1/30 12 Real fine 3.8 oz 3rd press
30、 G-Felt (50) 1/1 1/20 19 Gamma 4.0 oz G-Felt (50) 1/20 1/30 10 Gamma 4.0 oz Compiling data The data may be grouped by clothing set (using clothing on all positions) or by clothing piece on one position. Analysis by position is simpler but may be limited by interactions between positions. Analysis by
31、 set treats all positions equally. On most machines, all clothing positions do not impact machine performance equally. For example, on machines with three presses, the second press usually does not affect machine performance as much as the first and third presses. A period starts when a new clothing
32、 piece is installed and ends when another piece of clothing is installed. When data is grouped by clothing set, a new period starts and ends when a piece of clothing on any of the positions included is changed. The data must be divided into periods corresponding to clothing changes. Refer to the clo
33、thing record sheet to determine the periods based on dates of clothing installation and removal. When the periods are established, determine the averages for each variable during each period on a period calculation work sheet (Table 4). -,-,- TIP 0404-26 Paper machine clothing performance analysis /
34、 6 Table 4. Period calculation worksheet. 1. Average production Total production / number days in period = 2078 tons / 9 days = 231 tons per day 2. Average pounds of steam per pound of paper Total lb steam / (total production) (2000 lb / ton) = 10,368,000 lb / (2078 tons) (2000 lb / ton) = 2.49 lb s
35、team per lb paper 3. Average machine speed Sum of machine speeds / number days in period = 22,510 ft / min / 9 days = 2501 ft/ min 4. Average press moisture Sum of press moistures / number days in period = 534 % / 9 days = 59.3% 5. Average number of wet end breaks Total number wet end breaks / numbe
36、r days in period = 25 / 9 days = 2.8 breaks per day When the averages of the desired parameters have been calculated, record them on the Period Data Sheet (Table 5), which is used for charting the data. Graphing data Figure 1 provides an example of a press section histogram. Step 1. Using data on th
37、e period data chart, determine the range necessary for the period averages of the variables to be charted. Put the range for each variable on the y axis. Step 2. On the x axis, determine convenient spacings on the graph paper for the time period studied. Subdivide and label accordingly. Write months
38、 and years in proper spaces. Step 3. Still on the x axis, subdivide proper periods with time for the piece(s) of clothing studied based on the clothing records. When sets (more than one position) are used, repeat with a separate line for each position studied. The top line should be used for the pos
39、ition closest to the headbox. Step 4. Label each position line below the x axis as to supplier (or design). Step 5. Draw appropriate variable averages for each period. Draw vertical lines connecting the values of subsequent periods. Analysis of histogram When the histogram is completed, study it to
40、determine which clothing provided the best (and worst) machine performance. Recurring good (or bad) performance with a particular supplier or design indicates a significant impact by that clothing on machine performance. The impact of major changes in other important variables such as machine mechan
41、ical condition, steam supply availability, and pulp quantity/uniformity should be noted and considered during the analysis. Ideally, this information should be recorded daily (see Table 2). If not, a separate form to note significant machine changes is needed (Table 6). -,-,- 7 / Paper machine cloth
42、ing performance analysis TIP 0404-26 Alternate procedure Another clothing performance analysis technique supplements the histogram analysis discussed previously. This technique is based on comparing the performance of each piece (or set) of clothing with the pieces (or sets) of clothing which ran be
43、fore and after. Advantages over the histogram technique include: 1. Compensates for seasonal effects, improvements in machine performance, and other changes in machine conditions. 2. Permits differentiation of small changes in performance. Before/after difference analysis Table 7 provides an example
44、 of a before/after difference work sheet. Step 1. Calculate average performance of clothing piece/set over installation period on variables monitored. See “Procedure.“ Step 2. List clothing pieces/sets in chronological order with averages of variables monitored. Step 3. Obtain difference for each va
45、riable between pieces/sets installed before and after each piece/set. Better values should be given a plus (+) sign, worse values a minus () sign. Step 4. Obtain average of before and after differences and record. Step 5. When the same design/set is run consecutively, obtain before and after differe
46、nces between last different design/set and next different design/set. Step 6. When steps 3 and 4 are complete for all designs/sets to be evaluated, combine data for each design/set. Total and divide by the number of data points to obtain average performance for that piece/set. Step 7. Compare result
47、s for various designs/sets. Positive results indicate better performance, negative results poor performance. Zero indicates average performance. Step 8. Compare results of before/after difference evaluation with histogram analyses, average performance of each design or supplier, and other clothing a
48、nalysis observations. Guidelines for good clothing performance analysis Forming fabrics and press felts generally have the greatest impact on paper machine performance. Dryer fabric analyses using the techniques described are generally not successful due to very long runs and less impact on the vari
49、ables monitored. On machines where dryer fabrics fill quickly, machine performance differences may be apparent. Histograms are most beneficial when used over long periods such as 9 to 12 months. Ample time is needed for clothing usage to be repeated and for trends in machine performance to become evident. Interpretation is difficult when a large number of suppliers or designs are used. Firm conclu