Asia Trip Day 9: Back 2 Tokyo (12/27/17)

-

Our breakfast was at Ichiran ramen in Dotonbori. In Ichiran, customers use a vending machine to pay and create their custom order. It cost 1,490 yen (~$13) for a bowl of tonkotsu ramen with extra sides (egg, seaweed, pork). The vending machine had individual options for additional sides or drinks.  I still wasn’t feeling too well, so we only ordered one bowl. Once the payment was made, a receipt was printed out.


We took the receipt and brought it to the dining area, which were bar-style booths that were separated from each other with panels. In front of the seats was a window that exposed only the waist of our chef. Each stall also had a water tap so customers can self-serve. After handing the receipt to the chef, we were given with an order sheet to customize the ramen. It had a 1 to 10 scale for various properties of the ramen, such as broth richess, spiciness, noodle texture


The bowl of ramen was served through the window, as well as the additional sides dishes. The chef saw we were two people sharing one bowl, so they provided an extra bowl. Xuezhu ordered the spiciness at 6, which means a large dollop of chili sauce in the middle. I took my share of noodles and broth before it was mixed in. A wooden curtain was then pulled down over the window to give privacy.
Almond jelly with matcha 

This service style is in stark contrast with the sushi or kobe beef, where it is highly impersonal and fast. I suppose that while ramen is held in high-esteem, it is not considered a fancy meal requiring much hassle. So I suppose ramen is treated like fast food pizza or burger in Japan. The ramen itself was standard, but it was nice to have it tailored to our specifications. Since Xuezhu ordered a lower richness, the fat content wasn’t as high.



We walked around the Dotombori a bit more, and visited the Kuromon fish market again. We went to another restaurant to try okonomiyaki, which is a savory pancake topped with a variety of eggs, mushrooms, vegetables, seafood and smothered with toppings similar to takoyaki (bonito flakes, sweet brown sauce, mayonnaise). The flavors were rich and creamy, and the portion was quite large.

Shinkansen back to Tokyo

With our time in Osaka finished, we took the Shinkansen back to Tokyo, and transferred to Shinjuku to return to our 12/25 hotel (Kyu Kyu). By the time we were in the station, it was around peak time (6:30), so we had to miss a few trains due to the amount of people. Despite how polite Japanese are considered, we witnessed how pushy people will be in order to squeeze into the train. People wouldn’t shove, but just move their body into any empty space until the train was completely packed.

By the time we arrived in Shinjuku, I was tired and still felt a little sick so I turned in for the night. Xuezhu ventured out wanting to try more food, and she dined on a beef gyudon and more sushi. My dinner was some apples her mother packed for us in China. I figured it would best to rest as much as possible so that I could recover sooner and enjoy the remainder of the trip to the fullest.

Like hot pot, thin slices of beef  are cooked in the soup
Dipped into raw egg before eating
Lean, medium fatty, and fatty tuna nigiri

Comments

Post a Comment

Popular posts from this blog

6S DMAIC: Analyze

-
Image
After we’ve found out that something is wrong and how to measure it, we need to find the root cause of the problem. Analyze  is this deductive part of DMAIC; it’s a deep dive into all the details of the problem. Like a murder mystery, the detective investigates all the clues to determine the real killer. Many analytical templates have been created within the engineering industry to help plot out these details and help form a cohesive story. There’ll be a lot of push-and-pull between engineers and managers about the cost, bandwidth, and lead times required for each proposed root cause. These analytical tools are eye-candy for upper management, because they summarize the rigorous analyze, and justifies why the selected root cause is the best choice for both the business and process. The 5 most common analytical tools: 1. Brainstorming 2. Is-Is Not Analysis 3. The 6Ms (AKA Fishbone or Ishikawa) 4. The 5 Whys 5. Contradiction Matrix 1. Brainstorming Once we recognize a problem, our min...
Read more

Lean: 5S Methodology

-
Image
Before my mom left for work, she assigned various chores to me and my siblings. She wanted a nice clean house to return to after a long day of work. From these childhood chores, I learned good habits for maintaining cleanliness. A clean space not only looks nice, but makes everyday life easier: With the floors clear, you don’t worry about tripping over things With the tables clear, you don’t worry about knocking things over With the valuables in a special area, you don’t worry about losing them We’re all capable of great things, but we let distractions waste our time and focus. I’ve leafed through various self-help books and they all advice contemplating on what is truly important in our lives. After cutting out all the useless noise, we can focus on the important matters The common advice for improving work efficiency is having a clean work station, because a clear environment is a clear mind. If we know exactly where our tools and resources are, it becomes one less factor to consider...
Read more

6S DMAIC: Measure

-
Image
After we define the problem, we need evidence to support that it wasn’t just a freak accident. If odds are that it’ll never happen again, we won’t need to anything, right? In daily life, we are conditioned by habit; in diet, sleep, work, stress, and so on. When something unusual happens, it raises alarms that something might be wrong. In manufacturing engineering, data can be tracked using Statistical Process Control (SPC). Operators and equipment records process data of test, measurement, and yield. When the process is automated, a large database of “normal” data can be determined. Once a baseline is established, there are still allowable tolerances that are expected from noise and variation. An example SPC chart. When data exceeds the UCL (3 sigma above mean), there needs to be action! As expected from Six Sigma: any data point that crosses beyond the Lower Control Limit (LCL) or Upper Control Limit (UCL) should be measured. With these deviations compared against a long history of da...
Read more