In 2016, I did a short internship from August 3 to August 9 in Tokyo. I stayed at Chisun Hotel in Hamamatsucho for doing a five-day internship at AIMNEXT Inc. It takes around five minutes on foot to get in the office. AIMNEXT Inc. is a consulting firm with an ecosystem of services that works well in Japan, China, Singapore, Vietnam, and Indonesia. clients. Tokyo office remains the headquarter of the group, although each branch seems to be autonomous to bring expertise to its potential clients.
Throughout this essay, I am going to talk about - the overall opinion and impression - great discovery encountered at AIMNEXT Inc. -how this internship helped me to improve my analytical thinking skills.
First, I am thankful for the warm welcome of the board of AIMNEXT Inc. It’s been an immense pleasure to take part in the orientation session led by the CEO. Despite his hectic schedule, he came to introduce the workflow, vision, mission, and values of the company. It’s relatively rare for most interns to meet high-ups of the organization while doing an internship. The CEO of AIMNEXT Inc. is renowned for his hospitality of guiding visitors to know the company as much as they can. At the end of the internship, he brought us to Tokyo Skytree to sightseeing the city in all its splendor. As souvenirs, the company gave us some bullet pens, picture frame, notebook, and internship completion certificate.
AIMNEXT Inc. has built an ecosystem that involves large numbers of impressive products that propel the company to grab opportunities in the Japanese market. The company smoothly plants roots in Japan because of its flagship product so-called “Smart Factory”. This product implies Big data concepts to extract insights from the massive size of structured data from a set of machines; the key idea is to improve the quality management level and increase production efficiency.
Regarding the quality management level, it concerns –the prevention of defective outflow due to real-time monitoring and faster response at the time of failure –and compares the casting conditions and product quality, the determination of the casting conditions from the record. As for the production efficiency, it concerns the equipment utilization rate, the accurate grasp of the stop time/number of times, and corresponds to the proper understanding of the equipment maintenance timing.
My first day at AIMNEXT Inc. I was looking forward to seeing the project prototype. Fortunately, the roadmap of the internship program also included some series of demos. After the first demo, I said a long “WOW”. In a nutshell, this project is simply amazing! I realized the power of big data in a factory in term of clarification of the cause-and-effect relationship between the information (improvement of real-time information).
Seamlessly I can say it is one of my great discoveries in the internship. Besides, my task was to propose a real-time Machine Learning model with spark streaming for detecting issues begotten by electrical and mechanical faults of these machines and report them via an e-mail distribution list.
To build the model, I worked alongside a staff, since I was not familiar with the data structure of the system. I experienced this challenge at AIMNEXT Inc, it pushed me to learn many Machine Learning techniques. This internship really painted a very beautiful picture of the company in my mind.