Plannet Engineering Co., Ltd. was founded in February 1998 and mainly processes metal components for semiconductor manufacturing equipment, as well as food manufacturing equipment and medical devices. As manufacturing professionals, they have proposed optimal manufacturing methods to meet customer needs, ensuring product quality and delivery dates. They have a strong trust from customers and process many products daily.

One of the challenging tasks at Plannet Engineering was the estimation process. In this task, drawings from past orders or similar projects were searched, and from those, information about processing methods and materials were gathered. Based on that, the estimate was adjusted for material price changes and processing differences, increasing the accuracy of the estimate. However, there were many past orders, and the number of drawings to be searched was enormous. In the search, one would guess from the drawing name or project name, or open and check similar project drawings one by one. There were individual differences in the speed of finding the relevant drawings and the similarity of the found drawings.

Mr. Tagami:

“For instance, within our team, which includes Mr. A, Mr. B, Mr. C, and myself, I have the most in-depth familiarity with drawing content and previous cases, given my primary responsibility for drawing analysis and estimate provision. The search speed differs significantly from one person to another, resulting in completely different sets of drawings being retrieved depending on who’s conducting the search. At times, the disparities are so pronounced that we struggle to comprehend them, making it challenging to locate the needed information. I firmly believed that enabling anyone to perform the same task would yield substantial benefits.”

The challenge wasn’t just that. Due to the difference in the quality of work, tasks were concentrated on experienced people, leading to a dependence on specific individuals. If an experienced person left the job for some reason, the work would stop. It would take a long time to get a new person up to the same quality. The company was always looking for a system to solve this situation.

Future-Ready Efficiency: Achieving Consistency and Quality in Work Through Accessible Systems

At Plannet Engineering, they have proactively introduced what they deemed good to eliminate wasteful tasks that simply repeat and take time. They clearly distinguish between what is good and what is wasteful. While searching for a new system for stable and improved drawing-related work quality, they considered several systems based on this philosophy. They chose the cloud system for drawing data utilization, “CADDi Drawer”.

Mr. Masuda:

“I thought CADDi was a company that incorporated on-site opinions. Looking 5 or 10 years ahead, we must think about the future. We have introduced various systems in our company so far, but as we grow, we reach limits within 1 or 2 years. I felt that CADDi Drawer would evolve by incorporating user requests. It wasn’t just the function and performance; that was also a decisive factor in the introduction.”

Effects of introduction, as described by Mr. Masuda and Mr. Tagami:

Mr. Masuda:

“CADDi Drawer is very efficient. Its processing ability is fast, and searching is overwhelmingly quick. Everything comes up in bulk, which alone reduces the time.”

Mr. Tagami:

“It helps the most that the same drawings come out regardless of who does it. Previously, information was written on paper and came to me, but now information can be exchanged digitally. Past information is written there, so the time to search for past information is eliminated. The efficiency has improved considerably.”

Unifying Drawing Insights: How CADDi Drawer Bridges Tenure Gaps

By introducing CADDi Drawer, Plannet Engineering has improved the speed and accuracy of drawing searches in estimates, improving work quality. Anyone can get consistent results, and even those with little knowledge or experience of drawings can handle the task. It has also helped eliminate personal dependency.

At Plannet Engineering, they are considering expanding the use of CADDi Drawer and discussing more effective utilization methods with CADDi.

Mr. Tagami:

“Currently, we are entering information manually. In the future, that information will probably be automatically extracted and entered. If that task is eliminated, I believe we can reduce the time even further.”

Mr. Masuda:

“While increasing sales is essential, it’s not our only goal; we value the content. For example, profit margins or operation rates. We hope to increase those using CADDi Drawer. Right now, we’re only using about 30% of its potential, but maybe we can increase that to 50%. We want to continue that way. And as young people energetically work, older ones need to pass on their knowledge and experience to the next generation. Not just doing the job, but creating the next generation. The system will also evolve, so we always want to use it with the intention of creating the next version.”

Plannet Engineering aims to provide “the best manufacturing” more than ever by utilizing CADDi Drawer.