Cálculos de capacidad con configuraciones

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From the course by University of Pennsylvania

Introducción a la Gestión de Operaciones

48 ratings

University of Pennsylvania

Introducción a la Gestión de Operaciones

48 ratings

Course 3 of 5 in the Specialization Fundamentos Empresariales

Aprende a analizar y a mejorar los procesos empresariales en servicios o en la industria. Aprende cómo incrementar la productividad y a ofrecer niveles de calidad mayores. Después de que finalices con éxito este curso, podrás aplicar estas habilidades en un reto empresarial del mundo real como parte de la Programa Especializado de Fundamentos Empresariales de Wharton.

From the lesson

Calidad

La calidad no solo es la piedra angular de la gestión de operaciones, sino que también es un componente fundamental de la viabilidad y del éxito de una compañía a largo plazo. En este módulo se tratan todos los aspectos más importantes de la calidad en las operaciones, desde examinar las razones más comunes de los defectos, a las técnicas de implementación más usadas para abordar problemas de calidad y asegurar la fiabilidad y los estándares. Al final de este módulo, serás capaz de anticipar dónde podrán ocurrir los defectos y recomendar una estrategia sólida para mantener la calidad y la estabilidad.

Razones de Variedad6:10

Cálculos de capacidad con configuraciones10:42

Producción Modelo Mixto14:31

Elección de tamaño de un lote8:49

La fragmentación de la demanda y Fondo Común de Reserva9:31

Flexibility9:57

Plataformas y modularidad9:22

Límites a la elección del cliente5:17

Revisión del Módulo Variedad12:18

Meet the Instructors

Christian Terwiesch
Andrew M. Heller Professor at the Wharton School, Senior Fellow Leonard Davis Institute for Health Economics Co-Director, Mack Institute of Innovation Management
The Wharton School

Imagine two restaurants.

The first one is making cheeseburgers all day long.

The second one is making cheeseburgers and veggie sandwiches.

50 cheeseburgers, 50 veggie sandwiches, 50 cheeseburgers, 50 veggie sandwiches.

In between,

however, since the folks eating the veggie sandwiches don't want to have any of

the animal fat of the cheeseburgers on the sandwich, we have to clean the kitchen.

Clearly the first one,

the cheeseburger only restaurant, will have the highest capacity.

The reason for that is the second restaurant, every time they change over

from one sandwich type to the other, it is still going to lose some of its capacity.

In this session we'll introduce the concept of set-up times.

Set-up times require us to tweak our definition of a capacity

that we have introduced in the process analysis module.

Since we've had many sandwich and restaurant related examples in

the previous two modules, you'll look at another industry, custom apparel.

So you might be able to tell from seeing me on video now for

a couple of sessions, apparel and fashion are not my core competence, but

this should not get into the way of this session.

There are hundreds of online stores and, most likely thousands, and

thousands of tailors out there that have a business model around customization.

This is how the process works.

It starts with measurement.

In an online store, q takes the measures.

In the case of a tailor,

the tailor goes and starts taking your measures of the body geometry.

You then have to make a couple of choices about the shirt style

as well as the colors.

This combines the three forms of variety that we saw in the last session,

fit-based, performance-based and taste-based variety.

One the order is in, the tailor typically takes a couple of days,

if not a couple of weeks, to turn the order around.

Often time, there is an incentive for

you to order multiple shirts as opposed to just ordering one shirt.

Alternatively I noticed that many online retailers have minimum orders,

where you can only get shirts custom made if you order at least five shirts.

The power production is a very manual process.

It can be broken up into three steps.

The first step is the cutting department.

In the cutting department, we're going to take a layer of textile and

have to cut it in pieces.

This is typically supported by templates.

Templates, basically,

capture the pattern that capture to your specific body geometry.

They might have a specific arm size.

Then there might be the front of the shirt, the back of the shirt,

the collar piece and the cuffs.

And those are programmed in to a machine that will later on do the actual cutting.

Now notice that the setup of programming the machine or

building this template takes a certain amount of time that is independent of

whether we're going to produce 1 shirt, 10 shirts, or 100 shirts.

Once we have done the setup of the machine the actual cutting can begin.

Oftentimes they're using multiple layers of textiles piled on top of each other and

then cut in one go.

The next step is the sewing department.

This is a real assembly line where these small,

different pieces that we get out of the cutting are put together.

Finally, in the finishing department, the shirts get ironed and

folded together in a package ready for delivery to the customers.

While we analyze the production process of the parent company here,

we have to look at the capacity of each of the resources.

For the cutting machine,

the capacity calculations are a little bit more complicated than in the past.

The reason for this is the setup time.

When we're setting up the machine, when we're programming the sizes and the style

into the machine or when we're building the template, this eats up capacity and

thus can determine whether or not the cutting machine is the bottleneck.

To compute the capacity of the cutting machine,

we first have to introduce the concept of a batch.

The batch refers to a collection of flow units.

More specifically, we refer to a batch

as the number of flow units that are produced between two setups.

As we change the template or

the programming parameters from one shirt size to the next, we start a new batch.

So here's how the capacity calculation work.

Imagine we have a batch size of 15 shirts.

We're going to find the capacity we are asking ourselves, so

how long will it take to produce these 15 shirts?

The production process starts by setting up the machine for

these specific shirts, which will take 20 minutes.

Once a machine is set up it will take 15 shirts, times

the processing time of four minutes per shirt, to produce this batch.

That's our capacity is simply 15 shirts divided by 80 minutes.

This is expressed in shirts per minute.

This is a capacity given for batch size.

Now that was just the capacity calculation for the cutting machine.

To find the bottleneck of the process we have to calculate the capacity for

each of the four resources in the process.

As we said before, for the cutting machine, we had 15 shirts we produced and

20 minutes setup, plus four times 15 minutes of production time,

which is equal to 15 divided by 80,

which is roughly 1.88.

Notice that a cutting

step is the only resource here in the process that requires a setup time.

For this reason is the fact that this is batch operation is not relevant when we

calculate the various capacity levels as the assembly steps over here,

over here and then finally at finishing.

Here we calculate the capacity just as we did in the cases before.

We define capacity as the number of workers divided by the processing time.

Eight divided by 40 is equal to 2.2.

Similar for the next bit, we have five divided by 30,

which gives us 0.1666 and then, finally,

one divided by three equals 0.33.

So we notice that the step with the lowest capacity is over

here at section 2 and we define the step as the bottleneck.

Earlier on, I mentioned that many production companies require the customers

to order in a minimum order size.

Why would they do this?

To see this, consider the following calculation.

Let's ask ourselves how the batch size

is impacting the capacity at a particular resource.

Remember in our example a moment ago, where we had a setup time of 20 minutes,

and a four minute processing time for every unit that is made.

Now ask yourself what's the capacity if we make just one unit?

Well if we make one unit we're going to get one unit and

it will take us 20 minutes of set up plus four minutes of production.

That is roughly one divided by 24 which is equal to 0.04 and a little bit.

Now increase the batch from one to ten.

We're having ten units and that would take us 20

minutes to set up, plus 40 of production, which is,

ten divided by 60, which is equal to 0.1667.

Now think about a really big batch size.

Imagine somebody's buying 1,000 shirts.

How long will that take us?

Well we're going to get 1,000 shirts and it will take us 20 minutes for

setup plus 4,000 minutes of production.

This number is amazingly close to 0.25,

which is simply one over the processing time.

Let's grasp this effect in this chart here,

where we have the batch size of the X axis and the capacity on the vertical axis.

We see that as the batch size increases, so does the capacity.

Told ultimately here is one over the processing time.

Even with an infinite batch size,

the capacity of the step here will never be faster than one over four.

However, as the batch size decreases, I have to spend more and

more of the resources time in setup mode.

Thus batching really is a form of scale economies.

Larger batches means extra free capacity for

the company and that is something nice.

This is why company offers quantity discounts or

might require minimum purchase orders.

When we change from making one type of flow unit

to making another type of flow unit, we often time incur a setup.

Setups are by no means limited to the production sector.

Think about the service example.

Think about an underwriter in a bank who is producing,

or is underwriting, residential mortgages all day long.

Compare the productivity of this underwriter with an underwriter who is

alternate between underwriting consumer laws and residential mortgages.

Setups reduce capacity and for

this reason, we have an incentive to run long production benches.

This really creates a form of scale economies.

Long production batches are good for capacity.

However, as we will notice in the following session,

long production batches lead to big inventory, which oftentimes is a problem.

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