Equipment engineering involves maximizing the operating rate of equipment, which is a significant part of the product cost in the device industry. It also aims to find and remove causes of equipment failure in order to manage the equipment parameters in real time, to prevent defects in advance.⁴ To implement a smart factory, all equipment on site should be connected among themselves and to a control center, using IoT sensors.⁵ This requires major equipment at the production site, where the necessary information from the equipment is raised in real time and controlled by the Manufacturing Execution System (MES).

Therefore, EES deployment should precede to perform the necessary functions of the smart factory.

These centrally controlled equipment engineering systems require process control, working conditions engineering, and equipment efficiency engineering. Process control consists of a Fault Detection Classification (FDC) and a Run-to-Run (R2R) system that controls the process conditions of the product. The operation condition control consists of a Recipe Management System (RMS) that automatically controls the recipe. The Equipment Performance Tracking (EPT) is a system that monitors the equipment status in real time, and analyzes and manages status information.

At the manufacturing site, the equipment management system relays first information real-time data from the equipment to users and managers to support decision making. The upper level helps manage accurate orders and production plans through links with MES, ERP, and SCM, and enables automation from the lower level through the control of equipment, material handling, and PLC/POP equipment. With this process, it connects the ERP to the lowest production equipment and is configured to provide central control. (Refer to Fig. 1).⁶

Fig. 1 
Equipment engineering system configuration

The equipment engineering system provides FDC, which detects abnormalities by monitoring the parameters generated by the equipment in real time, and by predicting abnormalities through diagnosis and classification. For R2R to improve the capability of each lot, this is the latest technology to calibrate the recipe parameter by feedback and feed forward data for the entire process. The purpose of process control is to overcome dispersion by the process or the equipment. Its goal is to secure uniform quality by minimizing variability between each lot and maximizing yield.

In order to build an equipment engineering system, a link with the MES is required. The system itself consists of one of the major MES modules. As a reference for the implementation of the MES, there are studies on the establishment of a micro-sized MES for a small businessl,⁷ strategies and effectiveness analysis for the configuration of the MES for small and medium PCB manufacturers,⁸ and the establishment of a production information system in digital factories.⁹ Moreover, there is the context adaptive dispatching methodology¹⁰ for the construction of a production operating system for semiconductor processing lines. The etch rate of plasma equipment was predicted using the equipment engineering system’s delivery data.¹¹

In this study, the requirements of the manufacturing site for electronic components (BGA-PCBs) are analyzed to define the required functions, to analyze the way of working on the site, and to define the necessary functions in the design system. The smart equipment engineering system selects the target product first and analyzes the current equipment engineering process of the target line to accurately identify and clean up the problem in order to build the system for the site.

In the second step, target processes and equipment are selected by analyzing the requirements and processes of the site. Major equipment is chosen mainly from the main production equipment, and core equipment is selected considering the cost of entry. The following constitutes the standard architecture of the equipment engineering system for the target products, processes, and equipment. Considering the target products, processes, equipment, and production volumes, it is efficient in terms of investment cost and performance, and is easy to develop.

The analysis of the requirements for equipment engineering among different classes of users at the site resulted in four major categories. These items are divided into Equipmentp performance tracking, Recipe management, Parameter management, Process control. Equipment on-line should be the basic function (Table 1). Equipment efficiency control is selected as the most basic function. The required equipment information at the higher level should be collected in real time and two-way communication between the application and the equipment at the MES should be possible. Recipe management is a function to manage the Recipe by product used in the equipment and to automatically upload and download the Recipe. Parameter management is a function for real-time monitoring and diagnosis of equipment parameters. Important factors are selected from the equipment’s parameters and data are monitored in real-time. The necessary actions are taken by setting the interlock for processing if any errors are found. Process control sets the optimal conditions by calibrating the working conditions of the process by reflecting the defined measurement data and the after process data by lot. Equipment on-line automates the equipment in a standardized manner to collect and control the data required for the major equipment at the production site.

When it comes to applying the system, only those necessary processes are selected in which the maximum effect can be achieved at the most ideal or minimum cost.

In other words, an analysis of the entire process was carried out and approximately six of them were selected (Fig. 2), where the selection criteria centered round PCB manufacturing operations, and equipment engineering, and quality control. The equipment in this process were all classified as critical equipment. Equipment status information, conditions, and parameters were uploaded to the equipment engineering system in real time through the equipment on-line to enable two-way communication. In addition, each of these processes implemented a function to enable operators to enter and retrieve necessary information easily on the touch screen, by installing input PCs for workers.

Fig. 2 
BGA PCB Process flow chart

Smart factory equipment engineering includes RMS, FDC, R2R, and EPT, which are essential to implement a smart factory.

RMS is a function that manages the working conditions of many products and automatically uploads and downloads them onto and from the system. FDC is a function to detect and diagnose abnormalities in equipment. EPT is a function to manage efficiency by showing real-time equipment status information and analyzing equipment operation status. Many companies have developed and commercialized functions for equipment engineering. Most manufacturers use these functions individually to maintain the equipment engineering methods of production. The smart factory equipment engineering system implemented this time uses the framework comprising EPT, and RMS products in Korea on the one hand, and FDC, and R2R which are developed through industry-academic tasks (Fig. 3).

Fig. 3 
Application architecture

EPT incorporates a wide range of user requirements. Moreover, the FDC function was applied along with a logic that was developed to detect abnormalities from the critical parameters in the target equipment. The R2R function was applied to the plating process by developing an algorithm to compensate for the process conditions by reflecting the defined measurement data and the measurement results of the subsequent processes. DBMS used Oracle/Unix, an institutional interconnection with RS-232C, and equipment for server communication with TCP/IP. All data on the manufacturing site was semi-automatically labeled in all equipment, lots, and so on, and then entered using the Bar Code Reader (BCR).

Fig. 4 shows the final complete application architecture of the smart factory equipment engineering system and divides the configuration into four main areas: application, knowledge, data, and communication layer. As the application functions configured here are composed of different products, processes, and equipment depending on the characteristics of the product being produced, it is desirable to configure the necessary functions according to the concept of the product. Thus, the equipment engineering framework is commonly used to implement the smart factory equipment system for the product, and the functions implemented above are selected by the product, process, and equipment. The communication layer is responsible for defining the necessary functions by fitting into the smart factory’s entire system configuration, and by linking them with the associated higher system or sub-system.

Fig. 4 
Equipment engineering system user interface

The equipment control screen can be viewed by separating the equipment layout and the current status of equipment by building, floor, or area of the manufacturing site. The status information of the equipment is displayed by dividing it into operation, non-operation, shutdown, and preventive maintenance.

Equipment efficiency analysis shows the functions of analyzing detailed equipment status and performance, and managing the history of each process. Specifically, it is allows the comparison and analysis of indicators, such as equipment operation rate and failure time for each process. It also shows a comparative analysis of the current status of equipment in the device, lot information in progress, and operation performance of the equipment (Fig. 4).

Traceability screen, which allows users to manage the history of each product, has implemented a function to analyze the work history by lot. The equipment control screen was implemented for rapid action by monitoring the equipment status of the site in real time, and by establishing a system that automatically notifies the equipment protection staff and engineers in the event of an equipment failure.

Table 2 divides FDC, RMS, R2R, and EPT, which are classified based on performance before and after the application of the equipment engineering system. The work areas were further subdivided into categories such as equipment parameter control, equipment error detection, work condition management, work history control, operation condition setting, equipment on-line, equipment monitoring, and equipment operation improvement.

The effectiveness of the introduction of smart equipment engineering system is divided into the qualitative and quantitative effectiveness and then calculated. The qualitative effectiveness selects the quality prevention through the micro-management of equipment, the engineering defect prevention through management of working conditions, the quality improvement through process control, and the improvement of equipment operating rate through equipment on-line (Table 3).

The quantitative effectiveness divides the work into the micro-management of equipment, the engineering of working conditions, process control, and the engineering of equipment effectiveness as seen in Table 3, and then selects the detailed evaluation items. Specific evaluation items understand the effect of the defect reduction through engineering of equipment parameter, the engineering defect improvement through the management of working condition parameter, the quality improvement through the process control parameter, and the improvements in equipment operating rate through the engineering of equipment effectiveness parameter. The qualitative result and application effectiveness are shown in Table 4. The figure by item shown in Table 4 is an improvement after application compared to before application.