Based in South Korea, Dongwha Enterprise Co. Ltd is one of the global pioneers in the wood panel and chemical industry. With the company's 75-year history, it has expanded across the globe from Vietnam, Malaysia, Australia to Finland in the boards and building materials sector.

To realize its vision of Industry 4.0, Dongwha Enterprise’s specialized Data Lab unit built its own smart factory platform for its overseas production sites. The platform helps to collect, analyze, and fully utilize the vast amount of data generated by smart factories in real-time.

Dongwha Enterprise is building and operating smart factories on AWS cloud with the goal of process automation and digital internalization. However, it was not easy to collect, store, and quickly analyze the rapidly increasing facility data as the factories expanded.

Initially, Dongwha Enterprise’s smart factory system stored and managed sensor data and business data together in a relational database. As data and traffic grew exponentially over time, the team continued to experience frequent database failures, resulting in poor query performance and data inconsistency.

In response, the company began to review its smart factory system from the ground up and found that most of the overload was caused by read and write traffic in a database. To solve this problem, Dongwha Enterprise decided to introduce the document based community version of MongoDB on Amazon Elastic Compute Cloud (Amazon EC2).

Based on MongoDB, Dongwha Enterprise could solve most of the problems caused by large amounts of data and provide stable service to its system. In addition, the flexibility of MongoDB’s schema allowed the team to maximize data consistency and utilization by storing and managing various data in a single collection. However, with the rapid expansion of smart factories at home and abroad, other difficulties began to arise, such as server monitoring, database optimization, and version control.

Uram Jeong, Senior Associate, Data Lab, Dongwha Enterprise

The more diverse a smart factory is, the more problems can arise across processes, equipment, and maintenance. And it gets more complicated to track them.

Dongwha Enterprise required both the fast performance of a time-series database, and the reliability of MongoDB. When MongoDB introduced MongoDB 5.0, which includes native time-series support in 2021, Dongwha Enterprise found a single solution to multiple problems: the developer data platform MongoDB Atlas.

Uram Jeong, Dongwha Enterprise’s Senior Associate, Data Lab explained, “Cloud-based MongoDB Atlas simplifies complex tasks for administrators, improves reliability and availability, and provides a working environment where engineers can focus on application development.”

MongoDB Atlas has helped Dongwha Enterprise’s D-FactoryIn platform make four breakthroughs.

The first was the automatic indexing of MongoDB Atlas, which helped Data Lab gain greater analytical capabilities over its data. It suggested indexes to manage and search the history of slow queries in the database, pinpointing problems and enabling effective monitoring.

“While reducing the effort of manually applying and managing indexes, we are now able to understand data from a user’s point of view,” said DoYoung Kang, Senior Associate, Data Lab at Dongwha Enterprise. “Since MongoDB plays the role of database administrator and handles some of our tasks, we can focus on business-critical projects while reducing the workload.”

The second big advantage was that MongoDB Atlas made the team more productive with a simple installation and only a few clicks required to change settings. For example, Data Lab could instantly reflect version upgrades, auto-scaling, latest features, security updates, bug fixes, and so on. This has enabled Dongwha Enterprise to rapidly scale its smart factories and to increase work productivity by raising development standards.

Workload monitoring has also been greatly improved. With MongoDB Atlas’ detailed monitoring alerts, the team can now manage the data underlying its smart factories, such as cluster status, disk management, and network, without data loss, and quickly respond to issues with email-based notifications.

The flexibility of MongoDB’s schema makes designing data models much easier, which is a significant advantage for the team. Data Lab was able to create a data model that precisely fit for MongoDB. “Since deploying cloud-based MongoDB Atlas, we have had very few hardware outages in the past year, and our data retrieval performance has improved significantly compared to before,” said Jung.

Through proactive cooperation with MongoDB Korea, Dongwha Enterprise now operates facility management services with MongoDB Atlas across five smart factories at home and abroad.

DoYoung Kang, Senior Associate, Data Lab, Dongwha Enterprise

Dongwha Enterprise has been one of the earliest manufacturers embarked on a full end-to-end digital transformation journey. Since embarking on the journey with AWS in 2017, it has gone beyond just building a production automation system, to optimizing its entire work process, including facilities, products, services, and environments. Working with MongoDB has been a stepping stone for Dongwha Enterprise to innovate faster, establish efficient processes for collecting and storing facility data, expand operational processes and improve employee experience when using data.

Many positive and meaningful changes have permeated the organization. Most recently, Dongwha Enterprise became the first South Korean company to win a MongoDB APAC Innovation Award in recognition of the team’s capabilities leveraging MongoDB to innovate in the Industry 4.0 category.

Moving forward, Dongwha Enterprise’s Data Lab will continue to help smart factories and workers effectively use intelligent business analytics services. The team will continue to refine and maintain advanced analytics capabilities to support both problem-solving analysis and automation.

SeRi Song, Data Lab Manager of Dongwha Enterprise, emphasized, “We strive to create innovative value that drives digital transformation in the manufacturing industry through productive data collection and utilization. We will continue to work closely with MongoDB to realize the potential of Dongwha Enterprise.”

SeRi Song, Data Lab Manager, Dongwha Enterprise