Patent Application
20230138993
The present invention relates, generally, to the manufacture of plastic-free, fiber-based products and, more particularly, to designs, chemistry, and tooling for fiber-based cups.
Molded pulp manufacturing has experienced increased popularity in recent years in a wide range of applications, including, for example, cups, bowls, straws, and the like. Fiber-based packaging products are biodegradable, compostable and, unlike plastics, do not migrate into the ocean.
The two most common types of molded pulp are classified as Type 1 and Type 2. Type 1 molded pulp manufacturing, also known as “dry” manufacturing, uses a fiber slurry made from ground newsprint, kraft paper or other fibers dissolved in water. A mold mounted on a platen is dipped or submerged in the slurry and a vacuum is applied to the generally convex backside. The vacuum pulls the slurry onto the mold to form the shape of the package. While still under the vacuum, the mold is removed from the slurry tank, allowing the water to drain from the pulp. Air is then blown through the tool to eject the molded fiber piece. The part is typically deposited on a conveyor within a drying oven.
Type 2 molded pulp manufacturing, also known as “wet” manufacturing, is typically used for packaging electronic equipment, cellular phones and household items with containers having particular wall dimensions. Type 2 molded pulp uses the same material and follows the same basic process as Type 1 manufacturing up the point where the vacuum pulls the slurry onto the mold. After this step, a transfer mold mates with the fiber package, moves the formed “wet part” to a hot press, and compresses and dries the fiber material to increase density and provide a smooth external surface finish.
While currently known fiber-based products are desirable in a number of respect, systems and methods are still needed that overcome the limitations of the prior art. For example, it is difficult to manufacture drinking cups that can maintain their strength while holding hot or cold liquids. Various features and characteristics will also become apparent from the subsequent detailed description and the appended claims, taken in conjunction with the accompanying drawings and this background section.
In accordance with various embodiments, a fiber-based, plastic-free drinking cup is formed by providing a fiber-based slurry comprising a hydrophobic additive and a strength additive, then forming a drinking cup component by compressing and drying the fiber-based slurry in a form press assembly having an internal shape characterized by a conic frustum (i.e., a cup-shaped form). The fiber-based slurry may include a dry pulp mixture of virgin fiber and recycled fiber, the hydrophobic additive is 1.0-10.0% of the dry pulp weight, and the strength additive is 1.0-10.0% of the dry pulp weight. In a particularly efficacious mixture, the fiber-based slurry may include about 50% bleached hardwood, about 50% bleached softwood, about 2.5% strength additive, and about 3.5% hydrophobic additive by dry pulp weight. The molding method might employ a thermoform wet press, a dry press, or any other paper-making method.
Exemplary embodiments will hereinafter be described in conjunction with the appended drawing figures, wherein like numerals denote like elements, and:
The present invention relates to systems and methods for fiber-based drinking cups (for both hot and cold applications), including details of tooling, manufacturer, and fiber/additive composition. The following detailed description of the invention is merely exemplary in nature and is not intended to limit the invention or the application and uses of the invention. Furthermore, there is no intention to be bound by any theory presented in the preceding background or the following detailed description.
In general,
In contrast,
Drinking cups of the present invention may be fabricated using a variety of fiber compositions and chemistries. In general, by adding both a water barrier and strength additive to the cellulosic/hemicellulosic fiber, hydrophobic and strength properties can be added to the material. The fiber material itself may be virgin, recycled, or a combination of each. Furthermore, the formulation may be used in a wet press (thermoform), a dry press (traditional), or any other paper-making process.
In accordance with one embodiment, the fiber blend includes 0-100% virgin fiber and the balance recycled fiber, and the internal chemistry (weight percentage of dry pulp) of 0-10% strength additive (e.g., starch), and 0-10% alkyl ketene dimer (AKD).
In accordance with another embodiment, the fiber blend includes 20-80% bleached hardwood and the balance bleached softwood, with an internal chemistry of 0-6% strength additive, and 0-6% AKD.
In a preferred embodiment, the fiber blend includes 50% bleached hardwood, 50% bleached softwood, and an internal chemistry of 2.5% strength additive and 3.5% hydrophobic additive (e.g., AKD). This particular mixture was found by the inventors to be particularly effective and be surprisingly effective. That is, this mixture appears to have synergistic effects with respect to the ability to maintain its strength while being used to hold a liquid (either hot or cold).
The systems, methods, and resulting products described above may be used in the context of products manufactured using a fiber base mixture of pulp and water, with added chemical components to impart desired performance characteristics tuned to each particular product application.
In that regard, the systems and methods described above may incorporate the teachings of one or more of the following issued and pending patents: U.S. Pat. Pub. No. 2020/0206984, “Methods, Apparatus, and Chemical Compositions for Selectively Coating Fiber-Based Food Containers,” U.S. Ser. No. 10/428,467, “Methods and Apparatus for Manufacturing Fiber-Based Meat Products,” U.S. Pat. No. 9,988,199, “Methods and Apparatus for Manufacturing Fiber-Based Microwavable Food Containers,” U.S. Ser. No. 10/036,126, “Methods for Manufacturing Fiber-Based Beverage Lids,” U.S. Ser. No. 10/124,926, “Methods and Apparatus for Manufacturing Fiber-Based, Foldable Packaging Assemblies,” U.S. Pat. No. 9,856,608, “Methods for Manufacturing Fiber-Based Product Containers,” U.S. Ser. No. 10/087,584, “Methods and Apparatus for Manufacturing Fiber-Based Meat Containers,” U.S. Pat. No. 9,869,062, “Method for Manufacturing Microwavable Food Containers,” U.S. Ser. No. 10/377,547, “Method and Apparatus for In-line Die Cutting of Vacuum Formed Molded Pulp Container,” U.S. Ser. No. 10/240,286, “Die Press Assembly for Drying and Cutting Molded Fiber Parts,” and U.S. Ser. No. 10/683,611, “Method for Simultaneously Pressing and Cutting a Molded Fiber Part.”
Embodiments of the present disclosure may be described in terms of functional and/or logical block components and various processing steps. It should be appreciated that such block components may be realized by any number of hardware, software, and/or firmware components configured to perform the specified functions. For example, an embodiment of the present disclosure may employ various integrated circuit components, e.g., memory elements, digital signal processing elements, field-programmable gate arrays (FPGAs), Application Specific Integrated Circuits (ASICs), logic elements, look-up tables, or the like, which may carry out a variety of functions under the control of one or more microprocessors or other control devices.
In addition, the various functional modules described herein may be implemented entirely or in part using a machine learning or predictive analytics model. In this regard, the phrase “machine learning” model is used without loss of generality to refer to any result of an analysis that is designed to make some form of prediction, such as predicting the state of a response variable, clustering patients, determining association rules, and performing anomaly detection. Thus, for example, the term “machine learning” refers to models that undergo supervised, unsupervised, semi-supervised, and/or reinforcement learning. Such models may perform classification (e.g., binary or multiclass classification), regression, clustering, dimensionality reduction, and/or such tasks. Examples of such models include, without limitation, artificial neural networks (ANN) (such as a recurrent neural networks (RNN) and convolutional neural network (CNN)), decision tree models (such as classification and regression trees (CART)), ensemble learning models (such as boosting, bootstrapped aggregation, gradient boosting machines, and random forests), Bayesian network models (e.g., naive Bayes), principal component analysis (PCA), support vector machines (SVM), clustering models (such as K-nearest-neighbor, K-means, expectation maximization, hierarchical clustering, etc.), linear discriminant analysis models.
In addition, those skilled in the art will appreciate that embodiments of the present disclosure may be practiced in conjunction with any number of systems, and that the systems described herein are merely exemplary embodiments of the present disclosure. Further, the connecting lines shown in the various figures contained herein are intended to represent example functional relationships and/or physical couplings between the various elements. It should be noted that many alternative or additional functional relationships or physical connections may be present in an embodiment of the present disclosure.
As used herein, the terms “module” or “controller” refer to any hardware, software, firmware, electronic control component, processing logic, and/or processor device, individually or in any combination, including without limitation: application specific integrated circuits (ASICs), field-programmable gate-arrays (FPGAs), dedicated neural network devices (e.g., Google Tensor Processing Units), electronic circuits, processors (shared, dedicated, or group) configured to execute one or more software or firmware programs, a combinational logic circuit, and/or other suitable components that provide the described functionality.
While the present invention has been described in the context of the foregoing embodiments, it will be appreciated that the invention is not so limited. As used herein, the word “exemplary” means “serving as an example, instance, or illustration.” Any implementation described herein as “exemplary” is not necessarily to be construed as preferred or advantageous over other implementations, nor is it intended to be construed as a model that must be literally duplicated.
While the foregoing detailed description will provide those skilled in the art with a convenient road map for implementing various embodiments of the invention, it should be appreciated that the particular embodiments described above are only examples, and are not intended to limit the scope, applicability, or configuration of the invention in any way. To the contrary, various changes may be made in the function and arrangement of elements described without departing from the scope of the invention.
This application claims priority to U.S. Provisional Patent Application No. 63/274,648, filed Nov. 2, 2021, the contents of which are hereby incorporated by reference.
| Number | Date | Country | |
|---|---|---|---|
| 63274648 | Nov 2021 | US |
