Question

How can one of the attributes control charts (p, np, c or u) could be used to stabilize the process? Can you please give an example of a process from a quality perspective?

Answer 1

Answer :

ATTRIBUTES DATA AND CONTROL CHARTS

Clients today anticipate a quality item, yet they additionally expect quality in things related with the item. This incorporates picking up the telephone when a client calls, settling a client issue on the principal telephone call, right invoicing and on-time shipments, just to give some examples. These sorts of "traits" are not effectively estimated as a rule. How might we screen these kinds of circumstances after some time? Traits control diagrams can be utilized with this sort of information.

These sorts of information, which depend on checks, are regularly called qualities information. There are two kinds of properties information: yes/no and checking type information. With yes/no sort information, you are looking at particular things, (for example, solicitations, conveyances, or telephone calls). With checking type information, you are normally inspecting a zone where a deformity has a chance to happen. The two sorts of information are clarified underneath.

Indeed/No Data: For every thing, there are just two potential results: it is possible that it passes or it flops some preset particular. Every thing examined is either faulty (i.e., it doesn't meet the determinations) or isn't inadequate (i.e., it meets particulars). Instances of the yes/no information are telephone replied/not replied, item in spec/not in spec, shipment on schedule/not on schedule and receipt right/mistaken.

In the event that you have yes/no information, you will utilize either a p or np control graph to inspect the variety in the part of things not meeting a preset determination in a gathering of things. You would utilize a p control graph if the subgroup size (the quantity of things analyzed in a given timeframe) changes after some time. You would utilize the np control outline if the subgroup size remains the equivalent

Tallying Data: With checking information, you tally the quantity of deformities. A deformity happens when something doesn't meet a preset particular. It doesn't imply that the thing itself is blemished. For instance, a TV can have a scratched bureau (an imperfection) yet work appropriately. When taking a gander at tallying information, you end up with entire numbers, for example, 0, 1, 2, 3; you can't have half of a check.

In the event that you have tallying information, you would utilize a c outline or a u graph. The c outline would be utilized if the zone remained steady from test to test; the u graph would be utilized if the region didn't remain consistent.

On the off chance that you don't have information dependent on tallies, you have factors information. Factors information are taken from a continuum and are regularly alluded to as constant. Factors information can, hypothetically, be estimated to any accuracy you like. Instances of factors information incorporate time, length, width, thickness, dollars, and stature.

NP CONTROL CHARTS :

A np control diagram is utilized to take a gander at variety in yes/no sort traits information. There are just two potential results: either the thing is inadequate or it isn't flawed. The np control graph is utilized to decide whether the quantity of faulty things in a gathering of things is reliable after some time. The subgroup size (the quantity of thing in the gathering) must be the equivalent for each example.

An item or administration is flawed on the off chance that it falls flat, in some regard, to adjust to particulars or a standard. For instance, clients like solicitations to be right. On the off chance that you charge them to an extreme, you will find out about it and it will take more time to get paid. On the off chance that you charge them excessively little, you may never catch wind of it. As an association, it is significant that your solicitations be right. Assume you have chosen that a receipt is imperfect on the off chance that it has an inappropriate thing or wrong cost on it. You could then take an irregular example of solicitations (e.g., 100 every week) and check each receipt to check whether it is inadequate. You could then utilize a np control outline to screen the procedure.

You utilize a np control diagram when you have yes/no sort information. This kind of diagram includes tallies. You are tallying things. To utilize a np control outline, the checks should likewise fulfill the accompanying two conditions:

You are tallying n things. A tally is the quantity of things in those n things that neglect to adjust to particular.

Assume p is the likelihood that a thing will neglect to fit in with the determination. The estimation of p must be the equivalent for every one of the n things in a solitary example.

On the off chance that these two conditions are met, the binomial dispersion can be utilized to assess the conveyance of the tallies and the np control diagram can be utilized. As far as possible conditions for the np control diagram depend on the suspicion that you have a binomial conveyance. Be cautious here in light of the fact that condition 2 doesn't generally hold. For instance, a few people utilize the p control graph to screen on-time conveyance on a month to month premise. A p control graph is equivalent to the np control outline, yet the subgroup size doesn't need to be steady. You can't utilize the p control outline except if the likelihood of every shipment during the month being on time is the equivalent for every one of the shipments. Huge clients regularly get need on their requests, so the likelihood of their requests being on time is unique in relation to that of different clients and you can't utilize the p control diagram. In the event that the conditions are not met, consider utilizing a people control diagram.

STEPS IN CONSTRUCTING A NP CONTROL CHART :

The means in developing the np outline are given beneath. The information from above is utilized to show the figurings.

1. Assemble the information.

a. Select the subgroup size (n). Properties information frequently require enormous subgroup sizes (50 - 200). The subgroup size ought to be huge enough to have a few imperfect things. The subgroup size must be steady.

b. Select the recurrence with which the information will be gathered. Information ought to be gathered in the request in which it is produced.

c. Select the quantity of subgroups (k) to be gathered before control breaking points are determined. You can begin a control outline with as few as five to six however you ought to recalculate the normal and control limits until you have around 20 subgroups.

d. Examine every thing in the subgroup and record the thing as either inadequate or non-deficient. On the off chance that a thing has a few imperfections, it is as yet considered one inadequate thing.

e. Decide np for every subgroup.

np = number of damaged things found

f. Record the information.

2. Plot the information

a. Select the scales for the control graph.

b. Plot the estimations of np for every subgroup on the control graph.

c. Interface sequential focuses with straight lines.

3. Figure the procedure normal and control limits.

a. Calculate the process average number defective:

( NOTE : all the numerical values are just an assumption to make you understand the procedure)

where np₁, np₂, etc. are the number of defective items in subgroups 1, 2, etc. and k is the number of subgroups.

b. Draw the process average number defective on the control chart as a solid line and label.

c. Calculate the control limits for the np chart. The upper control limit is given by UCLnp. The lower control limit is given by LCLnp.

a. Ascertain the procedure normal number inadequate:

np bar( NOTE : all the numerical qualities are only a suspicion to cause you to comprehend the technique)

where np1, np2, and so forth are the quantity of imperfect things in subgroups 1, 2, and so on. also, k is the quantity of subgroups.

b. Draw the procedure normal number inadequate on the control outline as a strong line and name.

c. Ascertain as far as possible for the np outline. The upper control farthest point is given by UCLnp. The lower control point of confinement is given by LCLnp.

np control limits :

As far as possible for the red globule information are determined by substituting the estimation of 9.54 for the normal number flawed and the estimation of 50 for the subgroup size in the conditions above. This gives an upper control point of confinement of 17.87 and a lower control utmost of 1.20.

d. Draw as far as possible on the control outline as ran lines and mark.

4. Decipher the outline for measurable control.

a. The accompanying tests for measurable control are legitimate.

Focuses outside the ability as far as possible

Length of runs test

Number of runs test

Every one of the focuses are between as far as possible and there are no examples.

Keep in mind that the upper control farthest point speaks to the biggest number we would expect if just regular reason for variety is available.

The lower control point of confinement speaks to the most modest number we would anticipate.

For whatever length of time that the procedure remains the equivalent, we can anticipate what will occur later on.

Every individual will have somewhere in the range of 2 and 17 red dabs in the example. This won't change until we essentially change the procedure