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Black liquor evaporator upgrades— life cycle cost analysis, TAPPI Journal March 2021
ABSTRACT: Black liquor evaporation is generally the most energy intensive unit operation in a pulp and paper manufacturing facility. The black liquor evaporators can represent a third or more of the total mill steam usage, followed by the paper machine and digester. Evaporator steam economy is defined as the unit mass of steam required to evaporate a unit mass of water from black liquor (i.e., lb/lb or kg/kg.) The economy is determined by the number of effects in an evaporator train and the system configuration. Older systems use four to six effects, most of which are the long tube vertical rising film type. Newer systems may be designed with seven or even eight effects using falling film and forced circulation crystallization technology for high product solids. The median age of all North American evaporator systems is 44 years. Roughly 25% of the current North American operating systems are 54 years or older. Older systems require more periodic maintenance and have a higher risk of unplanned downtime. Also, older systems have chronic issues with persistent liquor and vapor leaks, shell wall thinning, corrosion, and plugged tubes. Often these issues worsen to the point of requiring rebuild or replacement. When considering the age, technology, and lower efficiency of older systems, a major rebuild or new system may be warranted. The intent of this paper is to review the current state of black liquor evaporator systems in North America and present a basic method for determining whether a major rebuild or new installation is warrant-ed using total life cycle cost analysis (LCCA).
Journal articles
Magazine articles
Temperature profile measurement applications of moving webs and roll structures with intelligent roll embedded sensor technology, TAPPI Journal November 2021
ABSTRACT: An intelligent roll for sheet and roll cover temperature profiles is a mechatronic system consisting of a roll in a web handling machine that is also used as a transducer for sensing cross-machine direction (CD) profiles. The embedded temperature sensor strips are mounted under or inside the roll cover, covering the full width of the roll’s cross-dimensional length. The sensor system offers new opportunities for online temperature measurement through exceptional sensitivity and resolution, without adding external measurement devices. The measurement is contacting, making it free from various disturbances affecting non-contacting temperature measurements, and it can show the roll cover’s internal temperatures. This helps create applications that have been impossible with traditional technology, with opportunities for process control and condition monitoring. An application used for process analysis services without adding a roll cover is made with “iRoll Portable Temperature” by mounting the sensor on the shell in a helical arrangement with special taping. The iRoll Temperature sensors are used for various purposes, depending on the application. The two main targets are the online temperature profile measurement of the moving web and the monitoring of the roll covers’ internal temperatures. The online sheet temperature profile has its main utilization in optimizing moisture profiles and drying processes. This enables the removal of speed and runnability bottlenecks by detecting inadequate drying capacity across the sheet CD width, the monitoring condition of the drying equipment, the optimization of drying energy consumption, the prevention of unnecessary over-drying, the optimization of the float drying of coating colors, and the detection of reasons for moisture profile errors. This paper describes this novel technology and its use cases in the paper, board, and tissue industry, but the application can be extended to pulp drying and industries outside pulp and paper, such as the converting and manufacture of plastic films.
Journal articles
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Control of malodorous gases emission from wet-end white water with hydrogen peroxide, TAPPI Journal October 2021
ABSTRACT: White water is highly recycled in the papermaking process so that its quality is easily deteriorated, thus producing lots of malodorous gases that are extremely harmful to human health and the environment. In this paper, the effect of hydrogen peroxide (H2O2) on the control of malodorous gases released from white water was investigated. The results showed that the released amount of total volatile organic compounds (TVOC) decreased gradually with the increase of H2O2 dosage. Specifically, the TVOC emission reached the minimum as the H2O2 dosage was 1.5 mmol/L, and meanwhile, the hydrogen sulfide (H2S) and ammonia (NH3) were almost completely removed. It was also found that pH had little effect on the release of TVOC as H2O2 was added, but it evidently affect-ed the release of H2S and NH3. When the pH value of the white water was changed to 4.0 or 9.0, the emission of TVOC decreased slightly, while both H2S and NH3 were completely removed in both cases. The ferrous ions (Fe2+) and the copper ions (Cu2+) were found to promote the generation of hydroxyl radicals (HOœ) out of H2O2, enhancing its inhibition on the release of malodorous gases from white water. The Fe2+/H2O2 system and Cu2+/H2O2 system exhibited similar efficiency in inhibiting the TVOC releasing, whereas the Cu2+/H2O2 system showed better perfor-mance in removing H2S and NH3.
Journal articles
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Creating adaptive predictions for packaging-critical quality parameters using advanced analytics and machine learning, TAPPI Journal November 2019
ABSTRACT: Packaging manufacturers are challenged to achieve consistent strength targets and maximize pro-duction while reducing costs through smarter fiber utilization, chemical optimization, energy reduction, and more. With innovative instrumentation readily accessible, mills are collecting vast amounts of data that provide them with ever increasing visibility into their processes. Turning this visibility into actionable insight is key to successfully exceeding customer expectations and reducing costs. Predictive analytics supported by machine learning can provide real-time quality measures that remain robust and accurate in the face of changing machine conditions. These adaptive quality “soft sensors” allow for more informed, on-the-fly process changes; fast change detection; and process control optimization without requiring periodic model tuning.The use of predictive modeling in the paper industry has increased in recent years; however, little attention has been given to packaging finished quality. The use of machine learning to maintain prediction relevancy under ever-changing machine conditions is novel. In this paper, we demonstrate the process of establishing real-time, adaptive quality predictions in an industry focused on reel-to-reel quality control, and we discuss the value created through the availability and use of real-time critical quality.
Journal articles
Magazine articles
Lignin-based resins for kraft paper applications, TAPPI Journal November 2019
ABSTRACT: We investigated miscanthus (MS) and willow (W) lignin-furfural based resins as potential reinforce-ment agents on softwood and hardwood kraft paper. These resins might be sustainable alternatives to the commercial phenolformaldehyde (PF) resins. Phenol is a petrochemical product and formaldehyde has been classified as a carcinogen by the U.S. Environmental Protection Agency. The lignin used in this study was derived from hot water extraction (160ºC, 2 h) of MS and W biomass, and may be considered sulfur-free. These biorefinery lignins were characterized for their chemical composition and inherent properties via wet chemistry and instrumental techniques. The resin blends (MS-resin and W-resin) were characterized for their molecular weight, thermal behavior, and mechanical properties. Mechanical properties were measured by the resin’s ability to reinforce softwood and hard-wood kraft papers. The effect of adding hexamethylenetetramine (HMTA), a curing agent, to the resin was also examined. Mixtures of PF and lignin-based resins were investigated to further explore ways to reduce use of non-renewables, phenol, and carcinogenic formaldehyde. The results show that lignin-based resins have the potential to replace PF resins in kraft paper applications. For softwood paper, the highest strength was achieved using W-resin, without HMTA (2.5 times greater than PF with HMTA). For hardwood paper, MS-resin with HMTA gave the highest strength (2.3 times higher than PF with HMTA). The lignin-based resins, without HMTA, also yielded mechanical properties comparable to PF with HMTA.
Journal articles
Magazine articles
Determining operating variables that impact internal fiber bonding using Wedge statistical analysis
ABSTRACT: In this study, Wedge statistical analysis tools were used to collect, collate, clean up, plot, and analyze several years of operational data from a commercial paper machine. The z-direction tensile (ZDT) and Scott Bond tests were chosen as representative of fiber bond strength. After analyzing thousands of operational parameters, the ones with the most significant impact upon ZDT involved starch application method, starch penetration, and the amount of starch applied. Scott bond was found to be significantly impacted by formation and refining. Final calendering of the paper web has also shown an impact on internal fiber bonding.
Journal articles
Magazine articles
Creating adaptive predictions for packaging-critical quality parameters using advanced analytics and machine learning, TAPPI Journal November 2019
ABSTRACT: Packaging manufacturers are challenged to achieve consistent strength targets and maximize pro-duction while reducing costs through smarter fiber utilization, chemical optimization, energy reduction, and more. With innovative instrumentation readily accessible, mills are collecting vast amounts of data that provide them with ever increasing visibility into their processes. Turning this visibility into actionable insight is key to successfully exceeding customer expectations and reducing costs. Predictive analytics supported by machine learning can provide real-time quality measures that remain robust and accurate in the face of changing machine conditions. These adaptive quality “soft sensors” allow for more informed, on-the-fly process changes; fast change detection; and process control optimization without requiring periodic model tuning.The use of predictive modeling in the paper industry has increased in recent years; however, little attention has been given to packaging finished quality. The use of machine learning to maintain prediction relevancy under ever-changing machine conditions is novel. In this paper, we demonstrate the process of establishing real-time, adaptive quality predictions in an industry focused on reel-to-reel quality control, and we discuss the value created through the availability and use of real-time critical quality.
Journal articles
Magazine articles
Colloid chemical aspects of paper formation in the presence of nanofibrillated cellulose and cationic starch, TAPPI Journal September 2024
ABSTRACT: A series of experimental tests were carried out to examine colloidal-scale consequences of optionally treating nanofibrillated cellulose (NFC) with cationic starches of different charge density and dosage (0.5% or 2.0% by weight), adding that material to a furnish prepared from 100% recycled copy paper, and then subjecting the mixture to very different levels of hydrodynamic shear. Tests included optical microscopy, sediment volume tests, sediment velocity tests, and “percent fines” assessment by means of a fiber quality analyzer (FQA). In addition, the zeta potential and charge demand of the studied materials were evaluated. Optical imaging revealed that cationic starch treatment of the NFC tended to agglomerate it into multiparticle clusters, which sometimes could be mostly redispersed by hydrodynamic shear. Subsequent addition of the starch-treated NFC to the default furnish resulted in much of the colloidal material becoming attached to fibers. Subsequent shearing of the mixtures was at least partly effective in separating the clusters of NFC from the fiber surface, resulting in essentially a two-component mixture. Multiparticle NFC clusters coexisted with the fiber suspension, sometimes attached and sometimes not, depending on the details of treatments. Sediment volume tests showed that systems containing cationic starch-treated NFC tended to have a higher density after settling in comparison to untreated NFC; these findings are consistent with the cationic starch acting as a stabilizer on the solid surfaces, allowing them to slide past each other during the settling process. Application of intense hydrodynamic shear tended to result in denser sediment. Results of tests with the sediment velocity messurement and the FQA percent fines assessment did not correlate well with changes in test conditions considered in this study.
Journal articles
Magazine articles
Furnishing autohydrolyzed poplar weakly alkaline P-RC APMP to make lightweight coated base paper, TAPPI Journal February 2022
ABSTRACT: This work investigated the effects of autohydrolysis pretreatment severity on poplar (Populus tomentosa Carr.) woodchips used to make a type of high-yield pulp (HYP) known as preconditioning followed by refiner chemical treatment, alkaline peroxide mechanical pulp (P-RC APMP). It also investigated the ratios for partially replacing sodium hydroxide (NaOH) with magnesium oxide (MgO) in the high-consistency (HC) retention stage of the P-RC APMP process on the obtained HYP’s properties. The results show that the pretreatment severity of autohydrolysis at combined hydrolysis factor (CHF) = 10.77 and the 50 wt% ratio for partially substituting NaOH with MgO were the optimum conditions for making light-weight coated (LWC) base paper. Compared to the conventional P-RC APMP, the optimized P-RC APMP had similar bulk and higher tensile, burst, and tear indices, as well as opacity, but a slightly lower ISO brightness. When the optimized P-RC APMP and commercial softwood bleached sulfate pulp (SBKP) were blended to make LWC base paper, the most favorable pulp furnish was comprised of 50% optimized P-RC APMP and 50% commercial SBKP. The obtained LWC base paper handsheet had better bulk, and its other properties could also meet the require-ments of LWC base paper.
Journal articles
Magazine articles
Numerical investigation of the effect of ultrasound on paper drying, TAPPI Journal March 2022
ABSTRACT: The paper drying process is very energy inefficient. More than two-thirds of the total energy used in a paper machine is for drying paper. Novel drying technologies, such as ultrasound (US) drying, can be assessed numerically for developing next-generation drying technologies for the paper industry. This work numerically illustrates the impact on drying process energy efficiency of US transducers installed on a two-tiered dryer section of a paper machine. Piezoelectric transducers generate ultrasound waves, and liquid water mist can be ejected from the porous media. The drying rate of handsheet paper in the presence of direct-contact US is measured experimentally, and the resultant correlation is included in the theoretical model. The drying section of a paper machine is simulated by a theoretical drying model. In the model, three scenarios are considered. In the first scenario, the US modules are positioned in the dryer pockets, while in the second scenario, they are placed upstream of the drying section right after the press section. The third case is the combination of the first and second scenarios. The average moisture content and temperature during drying, enhancement of total mass flux leaving the paper by the US mechanism, total energy consumption, and thermal effect of heated US transducers are analyzed for all cases. Results show that the application of the US can decrease the total number of dryer drums for drying paper. This numerical study is based on the US correlation obtained with the US transducer direct-contact with the paper sample. Thus, future work should include US correlation based on a non-contact US transducer.