This paper proposed an innovative approach to oblique worm drive by introducing a specific inclination angle. The investigation focused on the meshing performance of oblique ZA worm drive by varying the crossed axis angle. The meshing geometric models of oblique ZA worm drive are deduced, and the derivation of the lubrication angle along with the induced normal curvature calculation formula are proposed. The tooth-face contact conditions for different worm gears with various inclination angles are analyzed, and lubrication angles and induced normal curvatures are presented. To verify the numerical analysis, a simulation analysis was conducted for the oblique ZA worm drive with an inclination angle of 10°, and the results confirmed the conclusions drawn from the numerical analysis. A comparative test was performed between the transmission efficiency of the oblique and standard ZA worm drive reducer. The results demonstrated that the oblique ZA worm drive exhibited strengthened transmission efficiency and load carrying capacity.

Harmonic drives are critical components in robotic joints, and the hobbing accuracy of flexspline tooth profiles is essential for the transmission accuracy and operational stability of harmonic drives. The objective of this study is to propose an analysis method for the hobbing accuracy of flexspline tooth profiles. Firstly, a synthetic volumetric error model considering both geometric errors and thermal deformations was established based on the multi-body system theory. This model demonstrates the correlation between individual errors of the hobbing machine tool components and the spatial machining accuracy. Furthermore, the kinematic relationship of flexspline hobbing was established. Through kinematic analysis, it is concluded that the radial position deviation of the hob along the Y direction in the hobbing coordinate system directly affects the machining accuracy of the flexspline tooth profile. This deviation leads to variations in the tooth thickness of the flexspline tooth profile. Finally, theoretical tooth thickness deviations of the flexspline tooth profiles were predicted. Actual measurements of the flexspline tooth profiles were conducted, obtaining measured tooth thickness deviations. The measured values were smaller than the theoretical values, indicating the correctness of the established synthetic volumetric error model and the effectiveness of the proposed analysis method for evaluating the hobbing accuracy of flexspline tooth profiles. This research provides valuable technical references for error tracing and compensation in the gear hobbing process.

Behind production scheduling lies a trade-off between the comprehensive modeling of production system constraints and quick schedule provision. To realize mass customization, this trade-off must be addressed, requiring a model comprehensive enough for the automation of high-mix production yet quick in adapting to the dynamics of the production system. In this context, we propose a practical approach in which Flexible Job Shop Scheduling with Tool Switching Constraints, offering a model capable of representing a wide range of high-mix productions and Quantum Annealing are combined. The resulting schedules are demonstrated to be competitive, in terms of quality and computation time, are superior when compared with those obtained using Dispatching rules or Python MIP, respectively.

Customers' emotional needs, also called Kansei demands, have become one of the most focuses in new product development (NPD). With the rapid growth of the Internet of Things, customers are pleased to share their emotional experience and preference for products through an online platform. However, how to excavate customers' potential real needs in massive online reviews is the key to NPD. In order to better recognize and satisfy customers' emotional needs, this study proposes to explore the Kansei attraction of online products in combination with text mining and Kano model. Firstly, text mining technology extracts useful Kansei information from massive customer online reviews data. Then Kano model investigates the interaction between product Kansei and customer satisfaction, determines the Kansei attractive quality that greatly enhances customer satisfaction, and successfully predicts the future trend of products. These emotional qualities provide valuable references for enterprises, and designers can derive corresponding product design features based on them, which will improve the success rate of new product launches. A case study of extracting slow juicer's online reviews from Amazon.com is used to demonstrate the feasibility of the method and the results also can be extended to other NPD.

In the production line of film rolls, defects such as cracks, wrinkles, and contaminations in the film may occur and lead to a large manufacturing loss. To prevent manufacturing loss due to defects, various methods to inspect films have been developed and employed. However, they are mostly surface inspection methods and thus are not applicable to the film-winding process where defects not visible from the surface may occur inside the film roll. In this study, we proposed a non-destructive inspection of film-winding conditions using optical coherence tomography (OCT). OCT is a three-dimensional structural imaging technique with a microscale spatial resolution based on low coherence light interferometry and will be applicable to the inspection at the film-winding process via three-dimensional visualization of in-roll structures. In order to test the feasibility of the proposed method, we applied OCT to film roll samples made of commonly used films, a polyethylene terephthalate film, a polypropylene film, and a polyethylene film, and visualized their in-roll structures. The experimental results demonstrated that OCT can clearly visualize in-roll structures to inspect the presence and types of defects and can detect air gap sizes inside film rolls quantitatively, suggesting the potential utility of OCT applied to the inspection at the film-winding process in the production line of film rolls.

With the popularity of smart manufacturing, data-driven fault diagnosis methods for rolling bearings have been extensively studied in recent years. Existing rolling bearing fault diagnosis method has problems such as low precision and poor generalization ability when diagnosing multi-working condition bearings. In actual industrial scenarios, bearings usually operate under different operating conditions, causing differences in the probability distribution of the vibration data. Considering existing problem, this article proposes a diagnostic method of Inception ResNet Network (TL-IResnet) based on feature transfer learning. First, we utilize the Inception network to derive multiple scales of features from the original vibration signal. This enhances the capacity for feature expression in the model, and addresses the over-fitting issue in the deep model. Then the residual network is used to carry out deep learning on the fused multi-scale features to improve the residual network's ability to pay attention to important information, the self-attention mechanism is integrated into the residual network, and a new residual network structure is proposed. Finally, the maximum mean difference (MMD) is employed in output layer to measure the degree to which the probability distribution differs between the source and target domains to enhance the ability of model to transfer knowledge and complete the task of diagnosing the bearing of a machine. TL-IResnet is evaluated using the bearing dataset from Case Western Reserve University (CWRU) and the gearbox dataset from Southeast University. Experimental results demonstrate that TL-IResnet has a strong capacity to generalize information in addition to a high degree of accuracy under different conditions of operation, and has certain advantages over existing fault diagnosis methods.

While machining spiral bevel gear by forming method, the stability of cutting force acts a significant element affecting tool wear and machining performance. Based on the actual tooth-cutting situation, the calculation model of multi-blade cutting force is set up, and a new method to improve the machining precision of the tooth surface by using equal cutting force machining is put forward herein. Using the principle of forming method and the established machining model, the real-time tool-tip height is calculated, and the cutting area calculation formula is derived. The dynamic cutting force during multi-blade cutting is calculated by adopting the bevel-cutting model. Taking the cutting area at the most cutting force as the target cutting area, calculating equal cutting area is achieved by calculating the real-time feed rate, thereby achieving equal cutting force feed, and finally the calculation and improvement of cutting force during the machining of spiral bevel gears by the forming method are realized.

Mechanical buckling of a switch or button produces an attractive sensation of touch; however, a method to optimize the haptic pleasantness caused by buckling has not been established and well demonstrated. In this study, we optimized a popping elastic dome toy that provides pleasant haptic sensations when pushed or buckled. Toys with different physical parameters were manufactured following the Box-Behnken design, and their comfort was evaluated by the users. The design parameters that maximize haptic pleasantness were determined using the response surface method. The optimally designed popping toy was equally as comfortable as the best one in the initial specimen set. Further, haptic pleasantness was found to be largely determined by the ease of pushing and haptic feel at the moment of buckling. This approach is expected to improve the haptic sensations of various commercial products such as mechanical switches.

Rotate vector (RV) reducers are typical deceleration elements that moderate and increase torsion. They are widely applied in industrial robots and automatic machinery with the superiorities of compact structure, high precision, and overload resistance performance. However, the RV reducers also have disadvantages, such as low bearing capacity and short service life. As the core drive mechanism in an RV reducer, the bearing capacity for a cycloid-pin gear drive system directly affects the performance of the entire deceleration system. Therefore, the bearing capacity of an RV reducer should be improved by increasing the capacity of a cycloid-pin gear. In this paper, the design of a cycloid-pin gear is optimized to improve its bearing capacity. The tooth profile equations for cycloid gear and the meshing gap are derived based on the gear meshing principle. The bearing capacity for cycloid-pin gear is modeled by combining the contact strength theory with the multi-tooth contact bearing analysis. The effects of eccentricity, the radius of pin tooth distribution circle, pin teeth number, pin tooth radius, cycloid thickness, modification value of moved distance and equidistance on total volume, contact stress, and torsional stiffness are systematically researched. Then, a single-, double-, and three-objective optimization model is proposed based on the load-bearing capacity for cycloid-pin gear by taking these three factors as the objective function. Moreover, the parameters are optimized with the genetic algorithm, and the analyses for three optimizations are compared and discussed. The theoretical models are confirmed by the simulation analysis through ANSYS software. The results show that the bearing capacity for the cycloid-pin gear system can be largely enhanced after optimization.

The thermal issue of spindles for machining centers is still fundamentally unresolved. Thermal problems due to increased temperature of the spindle shaft lead to thermal displacement of the tool axis and an increase in friction torque, consequently imposing restrictions on spindle speed. To solve this issue, the mainstream method is to predict the temperature rise of the spindle shaft and compensates the thermal displacement that occurs there. However, when developing spindles for machining centers with higher precision and higher speed, it is necessary to take fundamental countermeasures against the temperature rise of the spindle shaft. In order to implement this countermeasure, it is necessary to clarify the phenomenon by measuring how the temperature of the spindle shaft changes due to changes in the spindle speed, and by measuring the temperature of the shaft during high speed rotation. In this paper, it was experimentally confirmed how the shaft temperature changes when a machining center spindle is rotated up to a D_mn value of 1.53×10⁶ mm/min. The results of measuring the spindle shaft temperature revealed that the temperature of the rotor was 2 to 8 K higher than the temperature of the bearing, and there was no positive correlation with the spindle speed. Furthermore, the proposed temperature measurement for the spindle shaft is believed to be applicable to other spindles used in machining tool, serving as an effective method for thermal issue.

With the global trend of electrification and the development of high-speed motor technology, the demand for high-speed reducers has been greatly promoted. As we all know, traction drive has certain inherent advantages in high-speed transmission. Therefore, this paper takes an asymmetric loading multi-roller planetary traction drive reducer as the research object. First, the kinematics and mechanics of the reducer are analyzed theoretically. Secondly, an equivalent simulation model is established according to its unique loading principle. In addition, the kinematic characteristics of the mechanism and the contact forces of its key components are obtained through mechanical simulation. The results show that the maximum relative error between the kinematic simulation value and the theoretical value of the reducer is 0.14%, the mean absolute percentage error (MAPE) of each contact force simulation value and the theoretical value is less than 5%, which verifies the effectiveness of the loading mechanism and the correctness of the theoretical analysis. Finally, the reducer transmission test rig was designed and built, and the advantages of precision transmission were verified by testing its actual speed ratio and repeated positioning accuracy.

Variability in the features produced by microfabrication processes, as well as uncertainty in some material properties, may cause a significant deviation in the performance of micromachines within the same fabrication run. Based on an estimation of the expected process variations, the design of such devices can be optimised to achieve the design goals, even under this uncertainty. Learning from previous works on the design of microresonators, we formulate this design problem as a case of chance-constrained optimisation and expand it to a general case where both the dynamic sensitivity ought to be maximised and the natural frequency should be close to a given target. Constraints to ensure a safe operation under both static and dynamic conditions are included by means of penalty functions. We implement the ‘Sample-Average Approximation’ (SAA), known in the field of stochastic programming, to solve the problem with a single-objective genetic algorithm (CMA-ES), requiring only a numerical evaluation of the objective function—no computation of its gradient is required nor a specific analytic form. We apply this optimisation strategy to the design case of an ultrasonic transducer—‘lateral CMUT’—, using optical measurements of trench variability to estimate process variations in a hypothetical design. Comparison of different optimisation results reveals that the implementation of SAA enables the choice of a more conservative design that meets the targets in spite of variability in its features.

The rapid development of automation technology in recent years has led to extensive research on how machines can replace human labor. However, many manufacturing companies may find the costs of smart production prohibitively high, while flexible manual production can result in higher profits. According to reports on the burden of disease in different countries, upper limb musculoskeletal disorders (UL-WMSDs) are the most prevalent occupational disease in industrialized countries, and they account for a significant portion of compensation. These disorders are often linked to the working environment, intensity, and duration of work. In this paper, the OCRA (Occupational Repetitive Action) index method is employed to assess the biomechanical risks associated with repetitive movements of the upper limb, and mathematical models were developed to automatically estimate the force, posture, and repetitive elements in this method. This paper proposes the OCRA index model for ergonomics based on the optimal switching problem when the processing time follows either an exponential or a generally distributed pattern. Finally, based on the switching model, numerical experiments were conducted in a medium-high action frequency scenario in order to evaluate the effect of speed changes on the OCRA index before and after switching. The experimental results enable us to find the optimal combination of the processing speed and the reference process k to minimize the total processing time in a safe ergonomic risk range.

Though high surface quality is expected in die and mold machining, machined surfaces often need to be polished to improve their quality after machining. One of the main reasons for the deterioration of the machined surface is the tool paths generated for ball-end milling. Variation in tool center points in the feed direction may occur even in tool paths that are generated using a commercial computer-aided manufacturing (CAM) system. The variation often causes a lack of uniformity on the machined surface. However, it is difficult for unskilled operators to estimate the machined surface prior to machining. Therefore, there is a need for a method for evaluating variation in tool center points that does not depend on the skills of operators. In this study, to achieve high surface quality, a novel method for evaluating variation in tool center points is devised for the free-form surfaces of dies and mold. An appearance indicator is introduced to quantify the degree of non-uniformity of the machined surface and derive an evaluation index. The effectiveness of the proposed method is verified by conducting machining experiments using different tool paths. The tool radius and pick feed are changed to confirm correspondence between the obtained surface quality and the derived evaluation index. The machining experiments successfully demonstrate that the proposed evaluation method can be used to improve surface quality.

In this paper, we consider a parcel delivery scheduling problem of minimizing the total duration for a truck-drone distribution system to serve a given set of customers. The single carrier truck plays the role of a mobile depot of multiple identical drones, and the drones with unit capacity perform the last-mile delivery from the carrier truck to each customer. An ordered set of truck stops for launching/retrieving drones is also given, and it constitutes a fixed route of the carrier truck. For the last-mile delivery of a drone to a customer, the launching stop and the retrieving stop of the drone must be the same. We newly introduce an integral parameter of access grade to an underlying parcel delivery model in order to obtain a flight time bound for each customer. By the flight time bound as a threshold, the given set of truck stops is partitioned into two disjoint subsets, namely sets of nearer stops and of farther stops. The carrier truck is required to choose a stop from the set of nearer stops for launching a drone to each customer. The access grade of nearer stops yields a generalized parcel delivery model, since it involves the case with a sufficiently large bound on the flight time as the underlying parcel delivery model with no access restriction to truck stops. In this paper, we first review an integer programming (IP) formulation of the underlying parcel delivery model, and then we modify it into the generalized version with the access grade of nearer stops. We also conduct numerical experiments to demonstrate the solution quality of the generalized version by utilizing an IP solver, and report the results.

For recent decades, product-service system (PSS), an integration of products and services, has become a promising business mode for traditional manufacturing firms to upgrade their business instead of only selling products. However, after the 2000s, more and more attention has been paid to the upgradability of this system. It is worried that the enlarged life cycle of services could not enlarge the life of the business. Although most services and products are designed to satisfy customers for a longer time, some customers are reluctant to keep using PSS until the end of their physical life due to the changing social and technical factors. With this consideration, the concept of upgradable PSS (UPSS), a type of PSS that could predict future change and plan upgrades in advance is proposed to maintain the satisfaction of stakeholders. To date, it is found that the current UPSS is still in a conceptual stage, which lacks detailed and normative methods to ensure the identification and refinement process of requirements towards upgradable PSS are effective because of the knowledge and subjective limitations. This paper introduces an upgradable Product-Service System (PSS) design method based on time-axis design and Knowledge Acquisition in automated Specification (KAOS). This method could enable designers to anticipate future changes in stakeholders’ value propositions and refine future requirements into rational upgradable solutions for PSS. The proposed method begins by introducing the concept of time-axis-based design, providing designers with support in identifying future changes across different temporal dimensions. Based on the grasped change in future, the modified KAOS is proposed to support designers in identifying the PSS characteristics to realize stakeholders’ expectations and understandably show the structure of PSS. To verify the effectiveness, the authors have adopted a case study of primary school furniture system design. For future research, a developed solution-generation technique is expected.

Rotary vector (RV) reducers are a common type of transmission device, and their transmission accuracy is crucial for many applications. Among them, the return difference (in other words, the reverse clearance of the reducer is called return error) is an important factor affecting the transmission accuracy of the reducer. The transmission return difference of the RV reducer refers to the lag of the output shaft angle when the input shaft rotates in reverse. Currently, research on geometric return difference does not consider the direction of cycloidal wheel tooth profile modification and manufacturing and installation errors on return difference. Therefore, this study establishes an accurate geometric return difference model considering manufacturing and installation errors and conducts simulation based on automatic dynamic analysis of mechanical systems (ADAMS). The dynamic return difference of the RV reducer under actual working conditions was simulated by automatic dynamic analysis of mechanical systems, and the overall hysteresis curve of the system was obtained using a transmission error test bench. The results showed that manufacturing and installation errors significantly impacted the transmission return difference of the reducer, and reducing these errors could improve transmission accuracy. This research provides an important basis for tolerance design of transmission systems and has important significance for improving the transmission accuracy of reducers.

Aiming at the sensitivity of installation errors caused by the complete conjugated tooth surface of cycloidal bevel gear, a method of tooth surface mismatch design which only modified the pinion cutter along two directions was proposed. Firstly, the cutter head structure of cycloidal bevel gear and the tooth surface forming process of generating gear were analyzed, and the tooth surface equations of cuter and generating gear were deduced, and the complete conjugated principle of tooth surface was analyzed. Secondly, the calculation method of processing parameters for the complete conjugated tooth surface was established, and the pinion cutter parameters along two directions modification were solved, and the equation of cutter blade edge with circular arc modification was derived. Based on the position and motion relationship between the cutter head and workpiece, the basic mathematical model of cycloidal bevel gear by generating method was established, therefore the theoretical tooth surface equation of workpiece was derived. On this basis, the numerical solution of tooth surface was studied, and the flow chart of loaded tooth contact analysis of cycloidal bevel gear with finite element method was established by using the ABAQUS software. Taking a pair of cycloidal bevel gear as an example, the tooth contact analysis and loaded tooth contact analysis were carried out, and the influence laws of installation errors on loaded tooth contact area and loaded transmission error were analyzed. The simulation results showed that after pinion cutter modification there formed the crown mismatch relationship along tooth length and tooth profile direction between the gear and pinion tooth surface, and the shapes of loaded tooth contact area and loaded transmission error curves had only little changes under the installation errors, which indicated that the two directions modification of pinion cutter can reduce the sensitivity of tooth surface meshing performance to the installation errors.