Maintaining stable production through error and predictive detection.

As industry shifts from the Internet of things, entailing machine-to-machine (M2M) and person-to-person communication, to the Internet of everything, enabling communication between people and things on a global scale, it is necessary to build more advanced systems by integrating items beyond just things, that include people, processes, and data. For example, changes in automotives and the use of VR and AI are revealing new possibilities.

Smarter factories require production systems with integrated data linkage and automation (Figure 1). Systems that permit devices to share data and automatically solve problems are being put to practical use as productivity-enhancing measures. Considering this, Fuji Smart Factory’s smart solutions are taking the lead toward this level of automation.

Figure 1. Smart factories require production systems that “talk” to each other without human intervention.

As expressed by Fuji’s head of Robotic Solutions, Takeshi Sato, “Fuji is exceeding placement limits under the ‘Target Zero’ concept, aiming for the ideal SMT production site. This concept encompasses ‘Zero placement defects’, ‘Zero machine operators’, and ‘Zero machine stops,’ leading to the newly defined goal of ‘Zero placement limits.’ Each of these contributes directly to achieving high quality, automation, stabilization of production, and enhancement of the ability to handle complex placements, and is an important pillar supporting the next generation of manufacturing.

“Fuji has worked to achieve the first three zeros by developing equipment that does not permit placement defects, creating a production environment in which lines do not stop, and automating standard operations, all while sincerely addressing the problems faced on the production floor. Now, in response to the rapid changes in technology and markets, we have expanded our focus to ‘Zero placement limits,’ with the belief that there is no placement Fuji cannot achieve.

“In addition to state-of-the-art equipment capabilities, the integration of advanced technologies such as AI, data utilization, and automated conveyance with AMR alleviates issues such as manpower shortages and dependency on manual labor, enabling human resources to be focused on more creative work.”

Smart Factory Roadmap

In 2017, the FUJI Smart Factory project was launched to develop work guidance functions and units that automate manual tasks (Figure 2). Starting at around the same time, Fuji also formed alliances with other equipment manufacturers that make up the SMT line to expand M2M functions that lead to improvements in overall equipment effectiveness (OEE).

Figure 2. The Fuji Smart Factory includes alliances with SMT equipment OEMs aimed at improving OEE.

The roadmap for FUJI Smart Factory (FSF) is broken into three steps:

• In FSF 1.0the systems and machines that configure the production line are linked together, and some traditional manual work is automated;
• In FSF 2.0, the current stage of smart factory support provided to customers, automation and linkage extend beyond individual lines to the entire production floor;
• And in FSF 3.0, the planned next step in automation, the 5M+E data contained within the factory is consolidated to realize a factory that continues to operate through feedback cycles and analysis of differences between planned and actual production.

Improved Placement Efficiency

FSF 2.0 includes the following features for automation of the entire production floor. Collectively, these features lead to increased efficiency, reduced production times, improved utilization rates, drastically reduced potential for errors, enhanced flexibility, higher quality in output and improvements in inventory management.

Production schedules. As shown in Figure 3, Fuji’s Scheduler tool automatically creates the optimal production schedule that includes the optimal conditions for production, taking into account multiple factors, including panel widths and reflow temperatures.

Figure 3. Location management expedites parts picking.

Parts allocation (reservation) prevents repetition of tasks due to a lack of the necessary parts after production preparation has begun.

Parts picking. The system guides parts that must be collected at each storage location by utilizing parts location management for efficient collection of the necessary parts using the shortest route.

The host system transmits information on necessary parts to the automated warehouse, enabling reliable checkout of parts.

Offline changeover. The system provides changeover guidance, so operators know what work they need to do and in what order to ensure that the necessary parts are supplied to the placement line without delay. LED lighting patterns provide a visual indication of whether it is possible to use a feeder (Figure 4).

Figure 4. Automatic work orders inform offline changeover.

Floor logistics. Autonomous mobile robots (AMRs) automatically transport the necessary feeders, printing materials and panels to load and unload these items to and from the line.

Figure 5. AMRs move materials and equipment.

Production lines. By scanning either the kanban ID or panel ID code, production programs can be changed from the current production to the next for all machines that configure the line. Upon receiving inspection results from SPI and AOI, the necessary actions are performed automatically inline with any trends that indicate status changes (Figure 6).

Figure 6. Inspection machines automatically communicate changes upstream.

Maintenance. Automatic maintenance units clean feeders, nozzles and heads, and check the performance of these after cleaning. Through system linking, maintenance history is recorded and guidance for when to perform maintenance is issued automatically.

Management. The system presents visual information necessary for management, including the progress status of the entire production floor, the state of production lines and equipment, and the occurrence of pickup errors (Figure 7). Using the board ID or panel ID as a key, traceability data, including SPI and AOI inspection images, is provided immediately.

Figure 7. A dashboard conveys critical production status information.

Workload Reduction

The introduction of FSF2.0 will reduce the workload of operators and enable production with fewer workers. Some events require operator intervention to prevent productivity loss and defects due to equipment malfunctions, however. FSF 2.0 provides tools to alert workers when an event occurs that should be handled by operators or when signs of such an event are detected.

• IPQC Expert can be used to note status changes based on short-term trends, and prompt action at the stage before defects occur.
• FSF Mobile Conductor sends machine error and warning notifications to mobile terminals held by operators.

These tools can be used in tandem to minimize the occurrence of defects, to minimize losses caused by errors and to maintain productivity.

Through aggregation of data from the production floor, analysis, predictive forecasting, autonomous control and self-diagnosis, Fuji is pursuing production process optimization. Fuji believes that this placement technology advancement will not only improve manufacturing sites but will also play a role in shaping the future of manufacturing.

Akihiro Senga is engineering planning department manager at Fuji Corp. (fuji.co.jp); ak.senga@fuji.co.jp.

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