All right. The next question is about chicken eggs and I went on Google here to

inform myself about the average weight of this chicken eggs.

I hope I got this right, I believe it's 47 gram,

And, I have this eco-friendly farmer here who is concerned about the output of his,

well, it is not really his output, but the output of his the chicken.

And he takes a sample and finds them that, they have basically, a mean of 47 and a

weight of two grams. However you can only make money of them if it fall into this

specification interval between 44 and 50. And so, you want to basically do some of

this sigma calculations that we talked about in class.

Try it out. Alright. The first one is relatively easy,

I would argue. Right?

The first one is a capability score. And remember this capability score looks

at the upper specification of a limit minus the lower specification limit,

Which is 44 divided by six times the standard deviation.

And so in this case here, that is simply six divided by six times two, which is

0.5. Now that is a relatively low capability score.

If you just go back through the slide that we discussed in class, you notice that you

know, you are somewhere between a one sigma and a two sigma process, and so this

corresponds now to a bunch of defects. And that's what the second question is

about. So what percentage of the eggs fall within

the specification limits provided by the local distributor?

So for that, I have to leave my PowerPoint quickly and, and jump in to Excel and so,

what I want to find out, is really I want to find out, from the normal distribution,

the specification limit, the upper specification limit is a 50.

All right? And so I have a distribution, a normal distribution was 47 mean and a two

standard deviation, and I'm looking at the cumulative normal here, and so I have

basically 93.3% of zx below 50 grams. And so one minus that, probability here

gives me the probability that this egg is going to be too, too heavy.

So six percent of the cases. As far as, the probability that this egg

is too light is concerned, I can again look at the normal

distribution and I can look at the scenario that I have a 44, and that normal

distribution was 47 mean and two as a standard deviation.

And that is, surprise, surprise, also 6.6%, because the mean of 47 is just right

in the middle of the confidence interval. So if I add up those probabilities, since

air can't be too heavy and too light at the same time,

I'm going to get a, a probability of 13.36,

Percent that the egg is outside the confidence interval or the specification

interval. And then, one minus that probability,

equals to 86%, is the probability that I had been fishing for in the question.

Alright. So that's you know, that's the kind of the

number two here. I'm just going to write, see Excel,

And I'm going to put the Excel spreadsheet up there on the Wiki,

And then the third question looks at basically how much does the standard

deviation have to be improved to get to a CP score of two thirds. Okay? And so we

just take the same equation as above, which was 50 minus 44 divided by six

times, And now, we leave the sigma as a variable,

as an unknown to be solved for and that we want to be equals to two third. And so

that is equivalent to, you know, that's basically this is six.

Six divided by six cancels out and then we have a one over a sigma equals to two

thirds, and that means that sigma would have to be reduced from the current state,

which was two grams would have to be reduced to 1.5 grams.

I have to disclose here that in the questions that we're doing, we'll always

assume that the current mean is actually in the middle of the specification

interval. It gets a little tricky otherwise, but,

I'm sure you can figure it out in Excel, And I promise to not test you on the exam

with that special nasty type of question. Alright. My last question is a very

creative one. It's a, a word matching problem in the

context of the Toyota production system. And the way this works is I've, provided

you here with, seven descriptions of, of, of managerial practices in operations and

I have seven Japanese terms here, below. And what I want you to do is I want you to

go ahead and, read these statements and match them to the Japanese words.

Go ahead. All right, let's tackle the first one.

let's just go A through G through each of these ones and just think about what

Japanese words comes to mind. So examples of this includes working to

working, medical workers making unnecessary movements, working on defects,

idle time, all of the stuff that shouts out waste, waste, waste and the Japanese

term for that is muja. So we have A and right here,

Second, a system that enables a line worker to signal that she or he needs

assistant, assistance from his supervisor and that's used to implement the Jidoka

principle, So that is the Andon Cord.

Now the Andon Cord, this cord that goes adjacent to the line, and that helps

people to alert the supervisor. And notice at, at that time the light

starts blinking, It's not that all of the factory, the

entire production line stops, but just the line segment and even that is not

necessarily always stop the course typically even at Toyota.

You're just going to have some buffers in there.

So that's the Andon Cord. C, A brainstorming technique that helps you,

find root causes, Of usually undesirable outcomes.

That is the Fishbone diagram, right, also known as the Ishikawa diagram,

And please don't think that Ishikawa is a fish in Japanese, but I think it's just

named by the inventor, Though, I really have to do close-set, I

speak absolutely no Japanese, I'm sorry for that.

Then Part D, workers at Toyota make suggestions to process improvement.

It's not just management that comes up with these suggestions and that is the

classic Kaizen process. Kaizen the process of continuous

improvement. How do you control the amount of work and

process inventory? That is an easy one,

Especially since we're running out of options here and that looks like Kanban,