The Key to Smart Factory Implementation: Manufacturing Data Utilization and Process Standardization
Smart factories are not simply about automating production equipment. They involve building an environment that collects and connects data generated during manufacturing, helps companies understand production status, and supports process improvement and operations management.
Manufacturing companies generate data across areas such as production, quality, inventory, and equipment. When data is managed differently across departments or systems, it can become difficult to access the information needed, limiting the use of accumulated data for operational improvement.
Therefore, before introducing new technologies, companies need to assess their current processes and data management practices and establish a foundation for managing data based on consistent standards as they move toward smart factory implementation.
Building a Data Management System for Smart Factory Transformation
Manufacturing sites generate various types of data, including production results, process information, quality data, inventory status, and equipment status. This data is needed to understand production status and analyze the causes of problems.
However, when production, quality, inventory, and equipment data are managed differently, companies may need to consolidate information from multiple sources, making it difficult to quickly understand current production status.
Smart factory implementation requires a management foundation that can collect and connect data generated during manufacturing. With systematic data management, companies can better understand production status and review operational improvements based on accumulated information.
Business Process and Data Standardization for Data Use
An important part of smart factory implementation, alongside system adoption, is organizing business processes and master data. To use data in actual operations, companies must first establish how information will be managed internally.
Manufacturing companies manage various types of master data, including item codes, BOM (Bill of Materials), process information, and inventory standards. When these data are managed according to different standards across departments, it becomes difficult to use the same data consistently, and data management issues may persist after system implementation.
For example, if the same item is managed under different codes across departments or production standards are not standardized, the accuracy of production analysis and data-based decisions may decline.
To address these issues, companies need to standardize key master data, manage data across departments based on consistent standards, and build a consistent data set. This standardized data can then serve as a basis for production analysis, process improvement, quality management, and management decisions.
How MES Collects and Utilizes Manufacturing Data
MES is a system that collects and manages data generated on the manufacturing floor. It systematically manages data generated during manufacturing, including production planning, work orders, production results, process progress, quality information, and equipment status, helping companies understand production status.
Manufacturing companies can use MES to accumulate data generated during production and analyze production status and operations based on that data. Reviewing production results and process data helps companies understand production progress against plans and identify areas for improvement.
KNIC’s production management MES provides manufacturing management functions such as production planning, work orders, production results, quality management, LOT tracking, and performance monitoring. It also supports the integration of shop floor systems such as PDA and POP to manage data generated during production.
In a smart factory, the goal is not simply to store data, but to establish a management environment that uses accumulated manufacturing data to improve production operations.
A Step-by-Step Smart Factory Implementation Strategy for Small and Mid-Sized Manufacturers
Smart factory implementation requires a step-by-step approach that considers each company’s production environment and level of data management. Because production methods, organizational structures, and existing system environments vary by company, the same implementation approach cannot be applied to every company.
First, companies need to assess their current processes and data management practices and organize their business processes and master data. They can then implement systems suited to their business environment, integrate existing systems such as ERP and MES, and establish a management system for utilizing accumulated data.
Small and mid-sized manufacturers need to review their current management needs and implementation goals and expand their systems step by step. Rather than implementing all functions from the outset, companies should set priorities based on their circumstances and systematically expand into the areas they need.
Ultimately, smart factory implementation is not simply about adopting technology. It is about establishing a data management system suited to the company’s environment and creating an environment for continuous operational improvement based on that system.