Packaging system

Package making – Methods – Filling preformed receptacle

Reexamination Certificate

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Details

C053S459000

Reexamination Certificate

active

06351926

ABSTRACT:

This invention relates to packaging and more particularly to an assembly for facilitating the loading of products into bags which are then closed to form packages. The assembly is especially suited for use with a bagging machine of the type which utilizes chains of preopened and interconnected bags.
BACKGROUND OF THE INVENTION
The use of chains of preopened and interconnected bags, such as those described in U.S. Pat. No. 3,254,828 entitled “Flexible Container Strips” issued Jun. 7, 1966 to Hershey Lerner (“the AutoBag Patent”), have enjoyed wide commercial success. Automated Packaging Systems, Inc. (“Automated”), as the assignee of the AutoBag Patent, manufactures and sells bagging machinery especially suited to the formation of packages through the use of chains of bags of the type taught in the AutoBag Patent. A machine sold under the trademark Excel® is described and claimed in U.S. Pat. No. 5,394,676 issued Mar. 7, 1995 to Bernard Lerner et al. under the title “Packaging Machine and Method” (“the Excel Patent”). The Excel machine is capable of the highest cycle rates of any of the machines made by Automated for use with AutoBag® webs.
Typically, the Excel Machine is used as a component of a modular system. Such a system typically includes vibratory feeders which dispense measured quantities of products onto conveyors in synchronism with the cycling of an Excel Machine. Collections of products to be packaged are sequentially and one collection at a time deposited into open bags positioned in a load station of the Excel Machine.
While such modular systems are highly efficient for many products, long, thin products such as plastic eating utensils are not well suited for packaging in such a system. As a consequence, long and thin products have been hand loaded into open bags positioned at the load station of a bagger such as an Excel Machine. Accordingly, there is a need for a mechanism which facilitates the loading of long, thin products into open bags positioned at load stations.
SUMMARY OF THE INVENTION
The loading of long, thin products into bags is greatly facilitated by a bag loading assembly made in accordance with the present invention. The loading assembly of the present invention may, for example, be mounted on an Excel Machine. The assembly includes a reciprocatably mounted load chute. The chute has a through product retention and dispensing passage extending from a load to a discharge end. Upstream from the passage the chute includes a chute-like load area. A moveable gate normally closes the discharge end.
When products to be packaged are in a machine mounted chute, and an open bag is positioned at a load station of the machine, the chute is advanced into the bag opening, the gate is opened and the products in the chute are gravity fed into the bag. The chute is then returned to a load position as the gate is closed. An operator then loads the long, thin products for the next subsequent package onto the chute as the machine completes a cycle by (a) sealing the loaded bag, (b) separating it from the web, and (c) advancing the web to position the next and now end one of the chain of bags in the load station where it is opened.
Since loading of the chute is occurring as the machine cycles, production rates are greatly enhanced. They are enhanced because absent the novel loading mechanism of this invention, the machine must pause each time a newly opened bag is present in the load station for a time long enough for an operator to manually load the products directly into the bag.
The load assisting assembly of the present invention includes a base or frame that is mounted on a bagging machine. A chute support is reciprocally mounted on the base. An air cylinder is interposed between the support and the base to cause rapid reciprocation of the support relative to the base when products are to be discharged into a bag.
In the preferred and disclosed embodiment, a plurality of elongated chute and gate subassemblies are provided. The chutes are of differing dimensions in order that an operator may select a chute of a size appropriate for the products to be packaged and for the size of bags to be used in forming packages. Each such chute has a torsional spring return discharge gate for normally closing the discharge end.
In use an operator selects a chute and gate subassembly of a size appropriate for the products to be packaged and the bags to be used. The selected chute is removably mounted on a reciprocatable support. A cam arrangement is adjusted such that when the mounted chute is moved into registration with an open bag, its gate will be cammed opened and products contained within it will be discharged into the open bag. The chute and support are then retracted along their reciprocal path to a load position as the gate is biased into its closed position to block the discharge end of the chute.
In the preferred and disclosed embodiment, an air cylinder is interposed between the frame and the reciprocatable support to affect high speed movement from a chute load position to a discharge position and return. Dashpots are provided to arrest the motion into the load position as the gate is opened. With this arrangement, gravity feed of the products being packaged is enhanced by the inertia of motion of those products when the chute containing them is arrested into a quick and relatively sudden stop.
Accordingly, the objects of the invention are to provide a novel and improved mechanism for assisting in the formation of packages and a process of packaging.


REFERENCES:
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patent: 4864800 (1989-09-01), Banys et al.
patent: 5987854 (1999-11-01), Killinger et al.
C. M. Bishop. “Neural Networks for Pattern Recognition.”Bayes Theorem.Clarendon Press. Oxford. Chap.1 pp. 17-23 (1995).
C.M. Bishop. “Neural Networks for Pattern Recognition.”The Normal DistributionClarendon Press.Oxford. Chap.2 pp. 34-38 (1995).
C.M. Bishop. “Neural Networks for Pattern Recognition.”Density Estimation in General.Clarendon Press. Oxford pp.51-55 (1995).
C.M. Bishop. “Neural networks for Pattern Recognition.” Mixtures Models/Maximum Likelihood/EM Algorithm. Clarendon Press. Oxford pp. 59-72 (1995).

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