1. Introduction
With the rapid development of industrial automation technology, industrial robots have become one of the important means to improve production efficiency, reduce costs, and optimize product quality [
1,
2]. Industrial robots can perform a variety of heavy, repetitive, and precise tasks, such as assembly, welding, painting, handling, etc., greatly enhancing the flexibility and automation level of production lines [
3]. Among various industrial robots, the selective compliance assembly robot arm (SCARA) is widely used due to its simple structure, small footprint, fast movement speed, and high positioning accuracy. It is particularly employed in the semiconductor manufacturing industry to execute point-to-point tasks that require strict operation accuracy [
4,
5].
SCARA can be divided into two categories based on the driving method: direct-drive SCARA and indirect-drive SCARA. The servo motion system in the indirect-drive SCARA relies on the use of permanent magnet synchronous motors (PMSMs) combined with reducers or mechanical transmission mechanisms like screw rods for high-precision position control [
6]. However, inherent mechanical issues in the transmission mechanism, such as gear meshing, clearance, and friction, significantly decrease the positioning accuracy of motion control [
7]. Moreover, the overall reliability of the motion system is reduced due to the cumulative impact of fatigue damage on the mechanical transmission mechanisms. Contrastingly, the direct-drive SCARA directly connects the load to the motor, eliminating the intermediary mechanical transmission mechanism, thus avoiding the abovementioned mechanical issues [
8]. While the direct-drive SCARA boasts advantages such as compact design, no transmission gap, and high positioning accuracy, it also loses the decoupling characteristics of the mechanical transmission structure. It intensifies the dynamics coupling issues among the various structures, leading to complex drive current waveforms during motion and presenting irregular output torque characteristics. The unsteady torque results in motor overheating, which severely affects the lifetime of the motor.
The key factor limiting the lifetime of a motor is its insulation system. Statistics show that approximately 30% of motor failures are related to the winding insulation [
9]. For a low-voltage PMSM used in an SCARA, local discharges are not allowed during operation, so thermal stress is the main aging mechanism affecting the insulation structure system of the motor [
10]. When the motor operates under overheating conditions, the heat expansion of the insulation material produces defects, easily leading to insulation breakdowns and causing motor interruption [
11]. According to the Arrhenius law, for every 8 to 10 °C rise in temperature, the insulation lifetime will be halved [
12]. While effective thermal management of the motor can be achieved through methods like optimizing cooling design and providing effective cooling approaches, these measures are not conducive to the lightweight and refined design of robotic arms. Therefore, establishing a rational reliability assessment model is a more effective method. Carrying out reliability assessments and lifetime prediction of the motor insulation system can effectively improve the operating efficiency of the motor, reducing the economic loss and maintenance costs caused by equipment failures.
Traditional reliability assessment techniques aim to obtain failure data and are often plagued by extensive test cycles and high costs. Especially for long-lifetime, high-reliability products such as motor insulation systems, even under more severe stress levels to accelerate the degradation of insulation, it is challenging to gather sufficient failure data to establish a reliability model [
13]. However, the failure of the insulation system is generally associated with several dielectric parameters such as insulation resistance, insulation capacitance, breakdown voltage, and dielectric loss factor. These parameters can all be used to characterize the degree of insulation aging [
14,
15,
16]. Therefore, reliability assessment models based on insulation aging diagnostic parameters have received extensive attention. By collecting accelerated degradation data from tests carried out at stress levels higher than normal operating levels, the degradation trajectory of the product is captured using curve fitting [
17], stochastic processes [
18], neural networks [
19], etc., and product lifetime is predicted based on pre-=set thresholds. Due to its excellent computational properties and strong interpretability, the Wiener process is particularly suited to the degradation process of motor insulation structures under thermal stress, thus improving the precision of reliability assessment [
18].
Aiming at the issue of internal temperature rise in PMSMs due to complex drive currents and irregular output torque when executing typical point-to-point tasks in direct-drive SCARA robotic arms [
20], a reliability assessment model under thermal stress is proposed. Firstly, kinematic and dynamic models of the direct-drive SCARA are established, and from the general trajectory planning method, the motion curve to complete a given motion task is obtained and the required torque for the motor is derived. Since thermal stress is identified as the main aging stress for the insulation system of low-voltage PMSM, accelerated thermo-aging tests were conducted on typical insulation materials. A reliability assessment model is established by modeling the degradation path based on the stochastic process model and the Arrhenius model. Finally, a temperature field analysis of the motor is performed and the highest temperature is taken as the reference temperature for the reliability assessment of the motor.
The main content of this paper is as follows.
Section 2 establishes the kinematics and dynamics models of the SCARA.
Section 3 designs and conducts accelerated thermal aging tests on insulation structures, and a motor insulation reliability model under thermal stress is established based on the Wiener process.
Section 4 conducts a case study on a typical SCARA operating condition, analyzing its output torque, temperature field, and reliability.
Section 5 summarizes the entire article.
5. Conclusions
For the typical movement tasks of a direct-drive SCARA, the operating condition of the PMSM during the task is investigated, and an evaluation method for the motor reliability considering thermal stress as the main aging factor is proposed. By establishing the kinematics and dynamics models for the SCARA, the output torque curve required by the motor is calculated. Accelerated thermal aging tests are conducted for insulation material, and an accelerated degradation model is established for the aging data based on the Wiener process and Arrhenius equation. From this, the reliability function of the motor is derived. Using the CFD method, the temperature field distribution of the motor is simulated based on its structure and operating condition. With the highest temperature as the reference, the motor reliability is analyzed. The research results show that, in a typical point-to-point task of SCARA, the motor can operate for 102,623 h continuously under a reliability requirement of 99%.
The reliability evaluation of a motor can enrich the understanding of its long-term performance and provide a crucial reference for improving the overall reliability of the robotic arm, thus reliably supporting industrial automated production. However, there are still some issues that deserve further research. The multistress lifetime models can be developed to achieve more comprehensive lifetime prediction for practical applications by considering the effects of electrical, mechanical, and environmental aging on insulation. In addition, if the motor is subjected to thermal shocks caused by temperature jumps during operation, it is more appropriate to establish a degradation model considering the shock process to describe the insulation aging process, which can reach a more accurate lifetime prediction. The lifetime prediction of electrical machines in the scheduled operation is also an interesting topic for further research.