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's fat of the cheeseburgers on their 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, is going to lose some of its capacity. This session will 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, we look at another industry, custom apparel. So you might be able to tell from seeing the, video now for a couple of sessions. Apparel and fashion are not my core competence, But this should not get into the way of the session. There are hundreds of Walmart 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, you takes some 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 around the shirt style, as well as its colors. This combines the three forms of variety that we saw in the last session. Field-based,, performance-based, and taste-based variety. Once your order is in, the tailor typically takes a couple of days, if not a couple of weeks, to turn the order around. Oftentimes, there is an incentive for you to order multiple shirts as opposed to just ordering one shirt. Alternatively, I notice that many online retailers have minimum orders, where you can only get shirts custom-made if you order at least five shirts. Apparel 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 want 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. You know, then there might be the front of the shirt, the back of the shirt, the collar piece, and the cuffs. And those are programmed into a machine that will later on do the actual cutting. Now notice that this setup of programming the machine or building the standard, takes a certain amount of time that is independent of whether we're going to produce one shirt, ten shirts, or 100 shirts. Once we have done the setup of the machine, the actual cutting can begin. Oftentimes, there are even multiple layers of textile 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 multiple 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. When we analyse the production process of the apparel 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 set-up 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 the batch. The batch refers to a collection of flow units. More specifically, we refer to a batch as a number of flow units that are produced between two set-ups. As we change template or the programming parameters from one shirt size to the next, we start a new batch. So here's how the capacity calculation works. Imagine we have a batch size of fifteen shirts. We're going to find the capacity by asking ourselves, well how long will it take to produce these fifteen shirts? The production process starts by setting up the machine for these specific shirts, which will take twenty minutes. Once the machine is set up, it will take fifteen shirts times the processing time of four minutes per shirt to produce this batch. Thus, our capacity is simply fifteen shirts divided by 80 minutes. 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 fifteen shirts we produced and twenty minute setup plus four times fifteen minutes of production time, Which is equal to fifteen divided by 80 which is roughly 1.88. Notice that cutting step is the only resource here in the process that requires a set-up time. For these reasons of fact that this is a batch operation is not relevant when we calculate the various capacity levels at 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 0.2. So, for the next step, we have five divided 30, Which gives us 0.1666, And then finally, one divided by three equals 0.33. So we notice that the step was the lowest capacity. It's over here at section two, Then we'll define the step as the bottleneck. Earlier on, I mentioned that many production companies require their customers to order 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 the particular resource. Remember, in our example in a moment ago, where we had a set-up time of twenty minutes and a four minute processing time for every unit that is made. Now ask yourself, what's the capacity if we just make one unit? Well, if we make one unit, we're gonna get one unit, And it will take us twenty minutes of setup, plus four minute of production. That is roughly one divided by 24 which is equal to 0.04 and a little bit. Now, increase the batch size from one to ten We're having ten units and it'll take us twenty minutes to set up plus 40 of production which is ten divided by 60 which is equals to 0.1667. Now think about a really big batch size. Imagine somebody is buying like a 1,000 shits. How long will that take us? Well, we gonna get a 1,000 shirts and it would take us twenty minutes for set-up plus 4,000 minutes of production. This number is amazingly close to. 0.25, which is simply one over the processing time. Let's graph this effect in this chart here, Where we have some batch size on the x axis and the capacity on the vertical axis. We see that as the batch size increases, so does the capacity. The [inaudible] here, this is one over the processing time. Even with an infinite batch size, the capacity of the step here will never be faster than one-fourth. However, as the batch size decreases, I have to spend more and more of the resources time, and set up more. Thus, that generally is a form of scale economies. Larger batches means extra free capacity for the company and that is something nice. This is what 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 oftentimes incur a setup. Set-ups 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 loans and residential mortgages. Set-ups reduce capacity and for this reason, we have incentive to run long production batches. This really creates a form of scale economy. 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