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Lean Manufacturing

How lot sizes change your efficiency

The saying goes that single-item flow is a lot more efficient than batch processing. This is easy to see when considering that seeing large inventories piling up anywhere in your factory and other stations waiting to process a batch are one of the Seven Deadly Wastes. But how bad is it? Would reducing batch sizes make your process 20% more efficient? Or double? Will it compensate the additional motion and transportation – other deadly wastes or is the cure worse than the disease?

Let’s consider a simple scenario comparing lot sizes of four that have to be processed by three stations. For simplicity, we assume that each item has to be processed individually, which takes one time step, and moving one or all items to the next station also takes one time step. The animation below shows processing the items in lots of four.

Processing items in lots of four at three different stations. Moving the material through the system takes 15 time steps.

We can now compare this with a process in which each processed item is immediately moved to the next station. The advantage is here that all three stations will be able to work in parallel. The difference is dramatic:

Moving items to the next station immediately allows processing the same amount of material in 9 time steps.

Processing the same amount of materials is almost double as fast. This is no surprise, as work is done in parallel, requiring up to three workers, whereas processing the entire lot can be done by a single worker. (The cost of labor remains the same, as the same amount of work overall is being done.)

The key difference, however, is that materials have to be moved 12 times vs. 3 times. This works on a so-called flow line, where stations are next to each other and workers can pass parts from one to the other, but will increase cost substantially in a job shop setup, where each transfer of material requires significant transportation. This is why flow-lines are so much more efficient than job shops.

Would it be worth to put in a dedicated material handler to simulate a flow shop in such a scenario? Let’s do the math real quick. Assume we have lot size L with L=4 in this example. Assume we have S stations with S=3 in this example. Processing the entire lot therefore takes O(LS) time steps with O(S) moves. (Indeed, LS=12 plus S=3 is 15.) The “Big-O” notation is used to analyze algorithms in computer science and reads “on the order off”. It allows us to ignore details like differences in processing time across different stations, but focus on the fact that lot size and number of stations are multiplied.

The time it takes to process lots of size L through S stations is proportional to the product of L and S.

Let’s look a single item flow line now. Once the first item has been processed, it is moving to the next station. The first station is done after L time steps. By this time, the other stations have begun working, however, and the first item is leaving the line after being processed at S stations. The total time is therefore O(L+S). Another way to think about is that the first item will be done after S time steps and the last L time steps later. The total number of transportation events is now O(LS).

The time it takes process L items through S stations using a single-item flow is proportional to the sum of L and S.

Assuming you need to process L=1500 parts through S=6 stations, the difference in processing time is one order of magnitude, or it is almost 10 times slower to process items in a lot. If material handling would be free in terms of cost and the extra head-aches it creates, moving your process time from O(LS) to O(L+S), would be a no-brainer. It would allow you to substantially decrease lead time, rent, and facility cost.

Transportation is never free, however. Workers need not only to move materials from station to station, they would also need to know where to move each item, something this would change with every product being made. A trade-off is to chose intermediate lot sizes. For example, instead of processing 1500 items at the time, workers could work in batches of 100 and then pass on these smaller batches to the next station. Note, that the same math applies: L is now 15 (15*100=1500) and O(L+S) is still better than O(LS), only the difference is less accentuated.

In practice, the batch size B should be chosen so that processing B items at a specific station takes as much time as moving these parts from that station to the next. For example, when using a dedicated material handling worker who picks up processed items every 10 minutes, B should be the number of items a worker can process in 10 minutes.

An elegant solution to this problem (and one that we can help with) is using material handling robots that connect the different stations at a constant rate of flow, picking up whatever number of items already have been processed and moving it to the next. Operating such robots is substantially cheaper than the cost of a worker (up to 8 times in industries such as aerospace engineering) and will automate a lot of the book-keeping, such as when to move materials where.

Reducing lot sizes becomes problematic, when processing times at different stations widely vary. There are two extremes: in one, all materials will need to be processed at once, for example when washing or coating the parts. In the other, processing takes much longer, leading to inventory build-up at this station. The solutions are simple, however. In the first case, the simulated robotic flow line needs to end just before the batch processing station, with another one starting right afterwards (if necessary) to maintain all the benefits. In the second case, additional resources (workers) should be added to balance the line. Here, the robots can help with arbitrating the load, for example, by automatically switching between delivery to two different stations.

Robotic Materials Inc. mobile manipulation solution is available for rent or purchase, contact us today!

Nikolaus Correll is the CEO of Robotic Materials Inc. and a Professor of Computer Science at the University of Colorado at Boulder. He has been designing and building large-scale distributed robotic systems from swarms of robot as small as a ping-pong ball to teams of mobile manipulating robots with fine manipulation skills. He is manufacturing robots for manufacturers in Colorado since 2016.

Categories
Lean Manufacturing

How to turn your job shop into a flow shop with material handling robots

A job shop is usually the least productive way to organize your manufacturing effort, see for instance “Why Are Job Shops Always Such a Chaotic Mess” by Christoph Roser. Yet, there are reasons job shops do not go away, and this is why you are probably reading this article.

Three products running through different stations of a job shop (left). Three products running through different stations of a flow shop (right). The representations are not equivalent and not every job shop can be turned into a flow shop.

Lets look at the reasons everyone tells you to better turn your job shop into a flow shop:

  • Flow shops are easy to measure and optimize. You can immediately see what goes in, what comes out, how long it takes and where things get stuck.
  • Flow shops are easy to automate. Each step is consistent and repetitive.

In fact, these advantages are so strong, that the advice is to essentially do whatever it takes to squeeze the processes into your job shop into a flow shop where some products simply skip certain stations.

So why would you want to stick to your job shop layout?

  • Your existing processes simply cannot be mapped to a flow shop without adding many redundant stations.
  • Flow shops take more time to setup, in particular if you have to account for all the possible products you are making.
  • Flow shops are not flexible. This becomes a problem when your products constantly change such as for contract manufacturers.
  • Flow shops do not scale well with increasing demand, but are optimized for a certain throughput.

In practice, most manufacturers already employ a hybrid model, setting up multiple flow shops within a job shop. While this provides them with an optimal trade-off in terms of efficiency, it is difficult to organize (workers need to know what to bring where) and measure and optimize overall performance.

There is a way to reap to truly reap the benefits of both approaches. Autonomous material handling robots allow you to turn your job shop into a flow shop, with the robot quite literally operating as a flexible conveyor belt that connect all of your stations equally. For example, a robot might provide a station with a shelf with new parts as well as a shelf for outgoing parts upon the press of a button. Once the process is complete, the robot will first move the end product to a new station, then remove the new incoming parts shelf.

Furthermore, the operator can obtain detailed statistics of not only what went in and what came out of a station and when, but also visualize the entire flow of an evolving product throughout the line. This is data that is historically easier to gather from a flow shop, but not necessary available.

Robotic Materials Inc. mobile manipulation solution is available for rent or purchase, contact us today!

Nikolaus Correll is the CEO of Robotic Materials Inc. and a Professor of Computer Science at the University of Colorado at Boulder. He has been designing and building large-scale distributed robotic systems from swarms of robot as small as a ping-pong ball to teams of mobile manipulating robots with fine manipulation skills. He is manufacturing robots for manufacturers in Colorado since 2016.

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Articles

From Mainframes to PCs: What Robot Startups Can Learn From the Computer Revolution

In their search for killer apps, robotics companies should look at the amazing evolution of computers

By Nikolaus Correll

In their search for killer apps, robotics companies should look at the amazing evolution of computers

Autonomous robots are coming around slowly. We already got autonomous vacuum cleaners, autonomous lawn mowers, toys that bleep and blink, and (maybe) soon autonomous cars. Yet, generation after generation, we keep waiting for the robots that we all know from movies and TV shows. Instead, businesses seem to get farther and farther away from the robots that are able to do a large variety of tasks using general-purpose, human anatomy-inspired hardware.

Keep reading on IEEE Spectrum…

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Articles

Robots Getting a Grip on General Manipulation

How a new generation of grippers with improved 3D perception and tactile sensing is learning to manipulate a wide variety of objects

Robotic materials gripper
Photo: Robotic Materials Inc.
A gripper created by Robotic Materials Inc., founded by the author, Nikolaus Correll, performs a manipulation task during the industrial assembly competition at the World Robot Summit in Tokyo.

This is a guest post. The views expressed here are solely those of the author and do not represent positions of IEEE Spectrum or the IEEE.

While robots have prepared entire breakfasts since 1961, general manipulation in the real world is arguably an even more complex problem than autonomous driving. It is difficult to pinpoint exactly why, though. Closely watching the 1961 video suggests that a two-finger parallel gripper is good enough for a variety of tasks, and that it is only perception and encoded common sense that prevents a robot from performing such feats in the real world. Indeed, a recent Science article reminded us that even contact-intensive assembly tasks such as assembling a piece of furniture  are well within the realm of current industrial robots. The real problem is that the number of possible manipulation behaviors is very large, and the specific behaviors required to prepare a club sandwich aren’t necessarily the same as those required to assemble a chair.

Keep reading on IEEE Spectrum…

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News

TechCrunch: Robotic Materials makes robotics hands for factory environments

Robotic Materials Inc. has been a “Top Pick” in Techcrunch’s Startup alley.

Categories
News

Proximity and force sensor nominated for “Best Paper” Award

The paper “Integrated force and distance sensing using elastomer-embedded commodity proximity sensors” by Radhen Patel and Nikolaus Correll was nominated for a “Best Paper” and a “Best Student Paper” award the 2016 Robotics: Science and Systems Conference in Ann Arbor, Michigan. RoboticMaterials has begun negotiating a licensing agreement with the University of Colorado’s tech-transfer office.