Source: http://www.docstoc.com/docs/52681355/Method-And-Apparatus-For-Weight-Controlled-Portioning-Of-Articles-Having-Non-uniform-Weight---Patent-6712221
Timestamp: 2013-12-05 03:09:10
Document Index: 423861858

Matched Legal Cases: ['arts 4', 'arts 4', 'arts 4', 'art 4', 'arts 4', 'art 4']

Method And Apparatus For Weight Controlled Portioning Of Articles Having Non-uniform Weight - Patent 6712221
United States Patent: 6712221
6,712,221
in the supply flow, but according to the invention it is still better to
base such calculations on a regularly updated recorded histogram (28) of
the weight distribution of a relatively high number of newly weighed
articles. Thereby the target calculations will rely on factual rather than
just expected conditions, and a very important result is that it is
possible to effect relevant batching even when the article weights in the
supply flow are not normally distributed.
09/379,511
379511Aug., 1999
209/645  ; 177/25.11; 209/592; 209/650; 209/657
B07C 5/00&amp;nbsp(20060101); B07C 5/18&amp;nbsp(20060101); G01G 19/00&amp;nbsp(20060101); G01G 19/30&amp;nbsp(20060101); G01G 19/38&amp;nbsp(20060101); B07C 005/16&amp;nbsp()
209/645,592,650,657 177/25.11,25.12,25.13,25.18,25.19,116,119,145
Kvisgaard et al.
6151866
0 065 820
WO 83/02002
This application is Continuation-In-Part of co-pending U.S. patent
application Ser. No. 08/809,492, filed Mar. 17, 1997.
1.  A method for determining the probability for filling at least one batch with at least one item having at least one characteristic property and for assigning an item to the
at least one batch based upon the best choice probability determined from the at least one characteristic property, the method comprising: providing a first set of data representing at least one characteristic property of at least one item;  providing a
second set of data representing the fill-up requirement of at least one batch;  generating a third set of data representing a table of the number of combinations of the at least one item represented in the first set of data as a function of the fill-up
requirement and the item count;  providing a fourth set of data indicating at least one fill-up requirement;  generating the probability for filling the at least one batch with at least one item relative to the fill-up requirements from the fourth set of
data based upon the best choice determined from the third set of data representing a table of the number of combinations of the at least one item represented in the first set of data, and effecting assignment of the at least one item to a respective
batch as determined from the best choice probability generated.
2.  A method for determining the probability according to claim 1, wherein at least one entry of the first set of data is removed and/or at least one entry is added to the first set of data when an item has been assigned in a process of assigning
at least one item to at least one batch of items.
3.  A method for determining the probability for filling a batch according to claim 1, wherein the first set of data is organized as a first in first out queue of entries, the queue has accordingly a first and a last entry and the last entry of
this queue represents an item most recently applied in a process of assigning an item to a batch of items.
4.  A method for determining the probability according to claim 1, wherein the number of entries of the first set of data is selected so that fluctuations in the probability due to removal and/or addition of entries to the first set of data is
lower than a predetermined limit and so that the prospect will be able to follow a general change in population of items.
5.  A method for determining the probability for filling a batch according to claim 1, wherein the number of entries of the first set of data is from 50-500.
6.  A method for determining the probability for filling a batch according to claim 1, wherein the third set of data is updated substantially each time an item is assigned to a batch.
7.  A method for determining the probability for filling a batch according to claim 1, wherein one entry of the first set of data is removed and one entry is added to the first set of data substantially each time an item is assigned to a batch.
8.  A method for determining the probability for filling a batch according to claim 7, wherein the third set of data is updated periodically each time a substantial change in the distribution of characteristic properties of the items represented
in the first set of data occur.  Description
In the food processing industry it is a well known problem that it is difficult to obtain portions consisting of a number of parts (such as pieces of fresh or frozen fish, meat or poultry) when it is additionally required that a predetermined
precise portion weight (possibly with tight tolerances) be combined with a pre-determined number of pieces, in particular in those cases where the weight of the individual pieces deviates in such a manner that the weight distribution of the pieces is
non-normal or changing.  Portions having a fixed number of pieces or a number in a chosen interval may be aimed at.
A weight distribution may be normal, whereby the usual concepts `average and spread` may be used as well as well tested statistical calculation procedures.  The weight distribution may also be non-normal, because of the fact that the charge or
flow of material being weighed may, at an earlier stage, already have been subjected to sorting and possible removal of all items within certain weight intervals, and this will have removed the possibility for traditional statistical calculations.
computer which hence keeps track of the relative position in the line and the respective weights.  A distribution unit places the parts selectively in collecting bins, whereby the portions are built up, while the accumulated weights of parts in the
In the last mentioned method a noticeable improvement has been achieved, cf.  GB-C-2,116,732, in that based on a qualified estimate of the freight distribution in the mass of parts one causes a selective sorting out in such a manner that parts
with a weight above and below the average, respectively, are brought together to make part portions which in order to fill to the desired weight need only one or a few parts which have the average weight.  The method hence is based on the probability
consideration that, of the normal distribution, there will be the largest number of those parts which have the respective average weight, whereby the final filling of the portions may occur the fastest when the waiting is for parts of in particular this
preprogrammed normal distribution curve, may be performed with limited data (equipment, a.o.  because according to normal practice one may allow that a new part may simply be fed to the first of such part portions which waits for a part in the weight
deliberate change in the part weight distribution the remaining parts usable for the portioning will no longer ex-hibit the normal distribution.  In this way a sorter or batcher of the said known type is given a task which it is not suited to solve.  If
therewith to a fixed price of the packings.  Instead, it has become a common practice to batch desired numbers of articles, e.g. four cutlets, and to weigh the individual packings as a basis for an automatic printing of weight and price or associated
then, exhibits any kind of natural distribution.  Any attempt of making such a batching economical based on expectations as to a normal distribution would be completely fruitless, and no other usable methods or means have been disclosed so far.
As an opposite extreme it has been found that the use of the invention for the batching of normally distributed articles for a variety of distributions seems to give still better results than the said known method.  However, it is still the
possibility of handling articles with pronounced non-normal weight distribution which is the major aspect of the present invention.
distribution curve based on general statistics.  According to the invention the weights of the incoming and currently weighed parts ace methodically registered in a serial register basically of the FIFO type (First In, First Out), such that the different
clearly reflect e.g. the absence of all parts of a certain weight category, whether these parts are actually missing in the supply low or they are successively selected for separate collection in dedicated bins.
Based on the histogram it is easy to calculate the probability of the occurrence of parts in the individual weight groups, and it is correspondingly easy to determine which parts should be brought together in order to form a basic sub portion
parts, and the computer equipment may be correspondingly adapted to handle infeed details from several sources so as to coordinate these details with the requirements of the various receiver bins.  The determination of the weight of the parts may be
effected by any appropriate means, thus also by a vision equipment.
In FIG. 1 is shown a batcher system of a conventional mechanical lay-out.  It comprises a feeder conveyor 2, on which parts 4 to be batched are conveyed one by one and brought to a conveyor 6 forming part of a dynamic weigher 8 registering in a
computer 10 the weight of the single parts 4.  Once weighed, the parts 4 are fed to a sorting conveyor 12 having at one side a row of receiver bins 14 and at the other side a corresponding row of diverter wings 16 with associated actuator units 18
operable to selectively swing the arms into a diverter position as shown at 16&#39;, in order to unload a given part 4 into a selected bin 14.  The computer 10 controls the operation of the wings 16 so as to effect unloading of parts 4 of particular weights
into selected bins, keeping track of the total contents of the individual bins.
predetermined target weight, preferably even with a predetermined number of parts in each portion, e.g. as described in said GB-C-2,116,732.
The described general lay-out of a batching system will be perfectly applicable in connection with the pre sent invention, which is focussed on the programming of the computer or control unit 10 in order to provide for a highly improved
FIG. 2 shows the same system in blocks, and the same picture is refound in FIG. 3, which illustrates the invention in more detail, with added blocks indicative of the operation of the control unit 10.  FIG. 3 a dotted line 1 divides these blocks
in real time operations, above the line, and background operations below the line.
to calculate the probability of the weight of the next arriving part 4, assuming the same distribution, viz.  by dividing the part numbers of the individual groups by the total number.  In FIG. 4, the probability of the next part or parts to belong to
each of the groups is listed under p, amounting from 5% for group 15 to 40% for group 12.
be formed by two different incidents, viz.  either a part from group 11 following a part from group 12 or just the opposite.  The probability of these incidents is the same (0.3.times.0.4=0.12 , so the combined probability will be twice as high, i.e.
For further explanation, although it will be trivial to statistical experts, FIG. 9 will be representative of a partial portion made of four pieces and missing one piece.  Any bin hereby holding a sum weight of group 40 will have maximum
probability (0.337) to reach the target weight range according to FIG. 7 since, as apparent from FIG. 8, pieces of weight group 10 are predominant in number.  On the other hand, a bin having reached weight group 34 will have a very low probability
(0.007) of coming up to the target weight and even only up to the acceptable underweight range, because in order to land at weight group 49, its only possibility is to wait for a piece from the maximum weight group 15, of which only very few can be
Since according to FIG. 7 only 10% of the target portions are allowed to exhibit the acceptable small underweight, the computer should also keep account of the allowability of finishing an underweight portion, inasfar as the previous batching
history will of course be decisive for such an allowability decision, based on the said 10%, measured for example over the last 1000 batches.
As another example, if a bin has already collected three pieces to the sum level 26 as appearent from FIG. 10, this bin will now be missing two parts, and of course there will be several combination possibilities available for two pieces to join
into the missing weight groups of FIG. 7.  Thus, a first piece from the extreme upper weight group 15 will require a second piece from weight group 11 in order to land at the permissible overweight group 52 (26+15+11=52), or, of course, it could be
allocated a first piece of weight group 11 and then a second piece of weight group 15, amounting to the same result.  However, having a first received a piece of weight group 25, it could still better be allocated a final piece of the minimum weight
group 10, this amounting to practically the same result, though now in overweight target group 51, but with an increased probability because there are more pieces available in group 10 than in group 11.  It would of course be ideal if a last piece of
group 9 could be selected, as this would enable the reaching of the ideal target weight of group 50 (FIG. 7), but according to the example, pieces of this weight group are simply not available.
In more general, the remaining two pieces for building up of a full target portion from stage 26 in FIG. 10 may be combined by parts from several of the available part weight ranges according to FIG. 8.  This leads to the said backwards
calculations, turning (26+15+11=52) into (52-15-11=26).  Thus, for the stage 26 of FIG. 10, it is relevant to operate with a probability function given by the sum of the following twenty combination possibilities, these being listed with their respective
probability values (FIG. 8):
1. 52 - 15 - 11 = 26 0.05 .times. 0.07 .times. 0.02 = 0.0007  2. 52 - 14 - 12 = 26 0.05 .times. 0.08 .times. 0.15 = 0.0006  3. 52 - 13 - 13 = 26 0.05 .times. 0.10 .times. 0.10 = 0.0005  4. 52 - 12 - 14 = 26 0.05 .times. 0.15 .times. 0.08 =
0.0006  5. 52 - 11 - 15 = 26 0.05 .times. 0.20 .times. 0.07 = 0.0007  6. 51 - 15 - 10 = 26 0.05 .times. 0.07 .times. 0.40 = 0.0014  . . . 11. 51 - 10 - 15 = 26 0.05 .times. 0.40 .times. 0.07 = 0.0014  12. 50 - 14 - 10 = 26 0.80 .times. 0.08 .times. 0.40
= 0.0256  13. 50 - 13 - 11 = 26 0.80 .times. 0.10 .times. 0.20 = 0.0160  . . . 16. 50 - 10 - 14 = 26 0.80 .times. 0.40 .times. 0.08 = 0.0256  17. 49 - 13 - 10 = 26 0.10 .times. 0.10 .times. 0.40 = 0.0040  18. 49 - 12 - 11 = 26 0.10 .times. 0.15 .times.
0.20 = 0.0030  19. 49 - 11 - 12 = 26 0.10 .times. 0.20 .times. 0.15 = 0.0030  20. 49 - 10 - 13 = 26 0.10 .times. 0.40 .times. 0.10 = 0.0040  0.1242  (FIG. 10, &quot;26&quot;)
Thus, if a bin holds a sum weight, which makes it possible to reach the target by means of different choices of number of missing parts, and more than one of these choices will not violate restrictions for total number of parts, the probabilities
for the possible choices can be added.  For example, FIGS. 10 and 11 shows that target can be reached from a sum weight of group 20 by means of 2 parts as well as by means of 3 parts.  To take both choices into account, the values for group 20 can be
summed, thus representing the possibility of finishing by means of either 2 or 3 parts.  It can then be evaluated which of these choices should be preferred.
of parts is missing, with the relevant probability function as provided be the unit 34 (confer FIGS. 8-10).  This can be done in the manner that it is calculated, for each bin, how an allocation of the new part for that bin would affect the probability
for a successful target filling will then rise to a maximum compared with the corresponding probabilities for all of the other bins, or whether the preferred bin should be the one in which the individual probability will enjoy the biggest increase (or,
respectively, the smallest decrease).  Also, it can be decided that the new part will not fit adequately in any of the bins, whereby it is rejected and moved for recirculation if not usable otherwise.
It will be appreciated that the required calculations are based on the factual histogram.  It will be understood however, that for some operations the histogram may still be effectively factural, even if based on a detection of the weight of e.g.
every second or third arriving article.  For the operation as such it will make no difference if, for example, the high proportion of parts of some average weight is not present at all or only in a very low proportion.  The system will operate perfectly
well anyway with all the remaining parts.
According to another aspect of the invention it has been found possible to use the grader technique for &quot;mixed jobs&quot; or &quot;multi product batching&quot; such as a co-batching of different chicken parts in the individual batches, typically two pieces of
breast, drumsticks, thighs and wings, respectively, up to a specific target weight (target weight range or target weight distribution).  Each chicken may end up in two of each such pieces, and it would be easy to pack a parted chicken in a packing
containing these eight main parts thereof.  However, the chickens and therewith these respective main parts thereof are not all of the same weights, and generally it would be attractive if such packings could be sold at fixed weight and price.
Sporadically, this has lead to attempts of merging pieces from one chicken with other pieces from other chickens in order to arrive at portions with a fixed standard weight, for enabling a uniform price marking, but this is a matter of careful or lucky
&quot;manual selection&quot; which, averagely, is highly time consuming and extremely likely to result in a considerable overweight (&quot;give-away&quot;) if or when it is prescribed that any underweight should be avoided.  As the chicken parts come by on a conveyor and
weighing line, the operator(s) will have very little time to decide between placing the newcoming articles in one or another of the already initiated portions.  At the principal level, however, it becomes possible to make use of parts of chickens of both
overweight and underweight, when the different pairs of different categories are joined in portions of an average target weight, despite the normally arising high degree of giveaway.
The batching technique by means of a grader has been developed for the handling and batching of items of respective individual product types arriving with a certain weight distribution, but it is it novel contribution to propose that even
different types of articles can be merged into the same batches in a well controlled manner.
Thus, already with a batcher as disclosed in the said GB 2,116,732 it will be perfectly possible to effect co-batching of e.g. different types of chicken pieces, provided the control system is geared to distinguish between the different types.
If the pieces of the respective different types are of marked different weight ranges, then it is obviously only a matter of calling for the weighing station or its computer to effect &quot;type recognition&quot;.  If the weights of the different types are more or
less overlapping, the associated problem has already long ago been solved in connection with pure sorting machines of basically the same layout as the grader according to said GB 2,116,732, viz.  in prescribing that items of different types should,
inletwise, be placed at respective dedicated positions of the feeder conveyor, such that the sorter control unit (without any weighing or recognition station) will nevertheless keep account of the kind of items arriving to the sorter line.
Once this is ensured in connection with a grader line with an associated weighing unit it will, on the level of principle, be very easy to program the control unit in such a manner that it will arrange for the desired merging of articles of
different types and weights into common batches, according to prescribed conditions.
A very simple control model will be to specify, by way of example, that each bill should receive at first a predetermined number of items of a first type, up to a predetermined partial batch weight for that type of items, following which the
process goes on with an addition to each partial batch of the required number of another type of items for the building up of an additional predetermined partial batch weight or target weight for items of this type, and so forth until the batch is
finished.  In practice, when the items of all types are supplied in mixed formation, the computer should be programmed such that different bins should receive respective different types of items, thus avoiding that all bins at a time will call for only
the same type of items.
With the above control model, acceptable small overweights of the individual partial batches will be summed up in each final batch, thus possibly amounting to a less acceptable total overweight.  On the other hand, this model implies that the
items of the different types should not be allocated to the individual bins in any predetermined sequence pattern, as the computer can easily handle the job of merging respective types of items to respective partial target weights even if the items are
allocated in mixed order.
One way of reducing such a possible overweight will be to arrange for the computer to effect a compensation adjustment for the target weight of one or more following partial batches in response to one or more preceding partial batch or batches
already having amounted to a noticeable overweight, or, for that sake, an acceptable `partial underweight`.  Thus, during the building up of the batches it is possible to operate with appreciable tolerances for the target weights of the respective
different types of items, whereby the batching may be greatly facilitated.
Ideally, of course, the different types of items should be allocated to the individual bins in respective sequential series, again in such a manner that normally there will always be bins calling for mutually different types of items.  The
sequence pattern for the individual bins should not necessarily be predetermined, inasfar as the computer may well be programmed to make coordinated decisions with respect to choice of &quot;new type&quot; for the individual bins, specifically with the purpose of
smoothening out the demands for the different types so as to keep the general batching capacity high.
It is a further possibility to effect batching control based on combinatoric calculations with the aim of arriving at the desired target weight (weight range, weight distribution) for the full batches, without defining specific partial target
weights for the individual types of items, though still with the required numbers of items of the respective types.  To illustrate this, FIG. 12 indicates a calculation model for the determination of &quot;best choice&quot; in allocating items to a selected bin
when the same is missing 4, 3, 2 and 1 items or item, respectively, in order to build up therein a batch of 2.times.2 items of two different types A and B. In connection with a natural weight distribution of the respective two types an ideal choice of
the batch target weight, M, should be the double sum of the average weights of the items of the respective types, or a well defined target range across or adjacent to this sum weight.
When a given bin it missing 1 item as represented by the line 1 in FIG. 12 it will of course be either an A- or a B-item, and since it has previously been endeavoured to provide for a partial batch missing just one such item exhibiting the
average weight of the relevant respective distribution (A or B), then such a weighed-in item will soon be localized and allocated to this bin for completing the batch therein.  When 2 items are missing, cf.  line 2, these will be either 2 A-items, 2
B-items or 1A- and 1 B-item, i.e. there will be three options.  The computer, knowing the available and expectable item types and weights according to the respective weight distributions and also knowing the weights of the collected items in all of the
bins missing two items, will then decide &quot;best choice&quot; for any new item to be allocated to such a bin which, when thereafter missing one item in stage 1, will have the better likelihood of being built up to the target weight M. It will be understood that
the required two items can be selected, each, within relatively broader weight ranges, inasfar as they should only fulfil the condition that the sum of their weights should build up the partial batch weight of the items in the selected bin to the point
or narrow range, from which the batch can be completed by one item from the average weight range of the items of either type A or type B.
When 3 items are missing (line 3), such items will be either one A-item plus two B-items or one B-item plus two A-items, i.e. now with still more combination options that will satisfy the conditions for the building up of the relevant partial
batches to the stage in which they miss but two items.  Here again the individual items can be selected from a still broader weight range of the respective item types, when only the sum of weight of the three items is sufficient to satisfy the conditions
In step 4, which will be the first step of the building up of a batch in any bin just requiring a first item, it will at least in principle be possible to select freely from the two types of items and from the entire weight range of the
respective distributions, confiding in the possibility of thereafter, in stage 3, further building up the partial batch weight to satisfy the conditions of that stage.
It should be considered, however, that it will not always be possible to exploit all of the items of a given distribution, in particular because a selection of a first item from either end of the spread of the distribution may make it practically
impossible to thereafter arrive at a predetermined target weight.  In such cases it will be a preferred possibility to sort out or neglect all of these extreme items, which are relatively few in numbers and then accept that the effective weight range of
the distribution is correspondingly restricted.
In FIG. 12, the course of sequence of the required calculations is illustrated in full lines in two dimensions only, linked with the handling of but two different types of items, each exhibiting individual weight distributions.  If items of three
different types are involved, the same calculations can be extended to comprise even the presence of &quot;C type items&quot; in a third dimension as shown in dotted lines, and if still further types are added it will thus be adequate to speak of calculations in a
&quot;multidimensional space&quot;.
In an analogous manner it will be possible to effect the calculations based on probability considerations as according to FIGS. 7-11, now with registrations of separate histograms for the weight distribution of the respective different types of
items.  Also in this connection, any of the calculation models discussed above can be selected.
Some co-batching jobs may be connected with special conditions to be observed.  Thus, for the batching of different chicken parts in pairs it may be set as a condition or at least a preference that the parts in any pair should be of reasonable
uniform weight, i.e. originating from the same relatively narrow weight range, in order to look &quot;natural&quot;.  Generally, the customers will not find it particularly remarkable if, in a packing with 2.times.4 chicken parts, the respective pairs of parts
originate from chickens of pronounced different weight classes, when only the parts of the individual pairs are reasonably alike, and the grader system, therefore, will still have good possibilities to merge items so as to form pairs or even larger
numbers of items with substantially equal weights and yet arrive at batching results with acceptable tolerances out from a wide weight range of the respective types of items.
In the foregoing it has been assumed that the overall goal is to make up batches holding a predetermined number of items amounting to predetermined target weights (weight ranges, weight distributions).  It is a still further aspect of the
invention, however, that while it is still desirable to work with one or more predetermined target weights, it will be practiceable to renounce the requirement as to the predetermined number of items in the batches.  It has been found that with the aid
of modern signal analysis equipment, whether operating in real time or in high speed simulation mode, it will be possible for the batching computer to recommend, generally or periodically, to build up all or some batches with another number of items in
order to reach the target weight more economically (small give-away overweight, small rage of recycling of unplaceable items).  Such a recommendation can be conveyed to a batching operator, who will then decide whether the recommendation should be
followed, perhaps in view of other conditions, or the computer may be set to simply institute switches between different numbers of items in all or some of the batches whenever this is found appropriate and permissible In connection with co-batching of
items of different types such shifts may effected individually for each type of items.
The general picture of the co-batching of items of different types as given so far is that the items of each batch are all allocated to the same receiver, in which the complete batch is built up.  It is another possibility, however, that the
items of each batch be allocated to two or more receivers, though still being batched to one target weight.  The partial batches in the different receivers can then be merged to form the full batch.  This can be practised when it is desired to produce
batches larger than the receiving capacity of each of the receivers, but a special possibility will be to effect separate collection of the respective different types of items, which may then, in the complete batch, be present as respective individual
groups, e.g. packed in individual bags, though in common still representing one full batch measured out to one total target weight.  This will be an advantageous option in connection with so-called catering packings of chicken parts, where it is often
desirable to keep the different types of parts separated from each other.
While a grader machine will normally have a plurality of receiver bins it will, at least in principle, be possible to use but a single bin for a specific batching job, whilst the other bins are used for one or more other jobs.  Such a &quot;single
bin&quot; should not necessarily be one particular bin, but rather &quot;one bin at a time&quot;; at the outlet from the grader it will be immaterial from which bin a given batch originates, if only the control unit provides an identification signal linking the
discharged batch with the relevant job, e.g. by an associated order number.
Method and apparatus for weight controlled portioning of articles having non-uniform weight, Kvisgaard, et al., Thorkild Kvisgaard, John Bomholt, Application number 09 379-511, Classifying Separating And Assorting Solids, Weighing Scales, Patent Lens, Patent Documents, Lens Search, Patent Drawings, Primary Examiner, computer system, Expiration Date, Data Services, English Español, Patent Community
1. Field of the InventionIn the food processing industry it is a well known problem that it is difficult to obtain portions consisting of a number of parts (such as pieces of fresh or frozen fish, meat or poultry) when it is additionally required that a predeterminedprecise portion weight (possibly with tight tolerances) be combined with a pre-determined number of pieces, in particular in those cases where the weight of the individual pieces deviates in such a manner that the weight distribution of the pieces isnon-normal or changing. Portions having a fixed number of pieces or a number in a chosen interval may be aimed at.A weight distribution may be normal, whereby the usual concepts `average and spread` may be used as well as well tested statistical calculation procedures. The weight distribution may also be non-normal, because of the fact that the charge orflow of material being weighed may, at an earlier stage, already have been subjected to sorting and possible removal of all items within certain weight intervals, and this will have removed the possibility for traditional statistical calculations.2. Description of Related ArtKnown methods to obtain portions of the kind discussed comprise manual weighing which is a very stressful activity and in most cases the built-in security for the customer in the form of over-weight means a considerable loss for the manufacturer.Two principally different automatic methods are known: The combination weighing principle and the accumulation weighing principle. In the first, a number of weighed parts or part portions are disposed in a number of weighing bins or in thecombination bins of such weighing bins, whereupon, based on the part weights measured, a computer calculates which bin sub portions in combination will constitute the portion which is closest in weight to the predetermined target weight. The limitationof this method is in particular that the number of parts which is available for the combination is limited.