Xinshida Motion Control System in Keyboard Assembly Applications within the 3C Electronics Industry
2025-07-16
Xinshida Motion Control System in Keyboard Assembly Applications within the 3C Electronics Industry
Project Background
You might not know that the assembly process of a laptop keyboard involves many little-known technical details. For example, beneath each key lies a delicate “scissor-switch” mechanism—this very design is what enables the keyboard to respond smoothly to every keystroke.
So, when installing the scissor-switches, how can we ensure that each “scissor-switch” component is positioned on the keyboard with its “front side” facing upward?
To ensure that each “scissor-foot” component can be precisely pressed into the fixture in the correct orientation, Xinsida has developed an advanced automated assembly technology and a sophisticated positioning system. These technologies not only enhance installation efficiency but also guarantee the consistency and stability of each key.
In an automated assembly device for aluminum plates used in the scissor-foot mechanism of a laptop keyboard, the scissor feet are randomly placed into a feeder tray in either their correct or reversed orientation. The feeder tray typically consists of a grid with multiple rows and 8 columns, and a camera identifies whether each scissor foot is oriented correctly or inverted.
Each workstation uses one robotic arm, and each robotic arm is equipped with eight suction nozzles. The robotic arms alternately pick up materials from two material trays—one on the left and one on the right—aiming to complete a full set of OK materials (i.e., eight scissor feet facing upward) in as few grasping cycles as possible, and then press the materials down onto the keyboard fixture.
When the OK materials in the material tray are insufficient to form a complete set, the material tray needs to be refreshed. Typically, the refresh process takes more than 8 seconds. Therefore, reducing the refresh time is crucial for improving the efficiency of laptop keyboard assembly. The selection method used by the robotic arm to pick up materials is an essential step in high-speed manufacturing. In response to this market demand, we will now introduce Xindashida’s innovative and upgraded screening solution.
Let’s briefly introduce the robotic arm’s material-handling method. For ease of understanding, we’ll randomly generate some tray data. The figure below shows the matrix-based data identified from a particular tray: dark blue represents the front-side materials, while light blue represents the back-side materials. The robotic arm’s material-handling requirement is as follows: it must pick up 8 front-side materials from the tray.
The first material retrieval plan is as follows:
Similarly, the second material-handling scheme is as follows:
Is there a more efficient material-handling solution?
Of course, it’s possible to offset the picking process. Suppose there are only two rows of data left in the material tray matrix. In the first pick, the robotic arm picks materials 1, 2, 4, and 5 from the first row. At this point, only nozzles 3, 6, 7, and 8 remain unoccupied. The robotic arm can then shift one column to the left and move down to perform the second pick. In this way, after just two picks, the entire set of picking requirements will be fulfilled.
Customer needs
Pain points of traditional screening methods
1. Frequent material retrieval leads to low efficiency and significant wear.
● Frequent sampling: Typically, it takes 3 to 4 sampling attempts to complete a set of data.
● Frequent operation of the robotic arm: Due to the high number of material-handling operations, the robotic arm must perform actions—such as moving, picking up materials, and placing materials—frequently, increasing the workload and accelerating wear and tear.
● Frequent tray refreshing: Traditional methods require frequent refreshing of material trays—after each material retrieval, the materials need to be rearranged or partially cleared out. This wastes time and may result in empty trays or uneven material distribution, thereby affecting the efficiency of subsequent material retrieval.
2. It takes a long time to take photos and perform recognition.
● Take a photo after each material retrieval: After completing the retrieval of materials from each group, you must use a camera to capture an image of the new material status. Following each photo shoot, the computer must process the image to determine the next step in the material retrieval plan.
● Delay in photo capture and image recognition: The processes of taking photos and recognizing images are time-consuming and can be affected by environmental factors (such as lighting, camera quality, and material placement), which reduces both the accuracy and speed of recognition.
3. Insufficient utilization of left and right material tray resources
● The left and right workstations fail to complement each other effectively: Traditional methods do not achieve efficient resource complementarity between the left and right workstations, resulting in separate management of materials. This leads to an imbalanced use of materials during production, increasing the frequency of material replenishment and causing prolonged downtime on the production line.
● The left and right bins cannot share data: Traditional methods fail to fully utilize the material information from both bins, making it impossible for them to complement or adjust their supplies during the picking process. As a result, one bin ends up with excessive surplus while the other is already empty, leading to resource waste.
Xinshida Solution
Scheme advantages
1. Reduce the number of material retrieval operations.
It can calculate the optimal material-picking solution, reducing the number of picking attempts per group (typically from 2 to 3 times), thereby lowering the frequency and time consumption of tray refreshing.
2. Calculate all material retrieval data in one go.
Calculate all data once before material retrieval, eliminating the need for image recognition with each photo. The robotic arm performs continuous material retrieval, saving time. By gaining advance knowledge of the material status on the tray, we can prepare in advance for refreshing operations, ensuring the continuity and stability of assembly work and guaranteeing the smooth operation of the production line.
3. Supports complementary left and right discs
The new method treats the materials on the right tray as an extension of the left tray, thereby improving resource utilization. The complementary strategy is equivalent to increasing the capacity of the material trays, enhancing picking efficiency, reducing the number of operations, and optimizing overall utilization.
Scheme Composition
1. Customer Configuration
• 1 set of ADT-6320E-B08 EtherCAT bus motion control card
• 30 sets of Ω6 EtherCAT bus-type servo drives
• 4 sets of industrial cameras
• 2 sets of AR5520 industrial robots
2. Relevant parameters
• Accuracy: ±0.01 mm
Associated products
ADT-6320E EherCat Bus Control Card
Singlina Ω6-A Servo Drive
AR5520B SCARA robot
Project Results
● Able to transcend departmental boundaries and quickly identify the optimal material-handling path.
● Possesses powerful estimation capabilities; the screening method can accurately calculate the total quantity of material groups that can be obtained in a single step.
● Supports a cross-disc complementary operation mode, further enhancing the overall utilization rate of material trays.
