The International Journal of Advanced Manufacturing Technology

Product family assembly line (PFAL) is a mixed-model assembly line on which a family of similar products can be assembled at the same time. Aiming at the balance problem of PFAL, a balancing model for PFAL is established, and simultaneously an improved dual-population genetic algorithm is proposed. Firstly, through the characteristic analysis of PFAL, the tasks on PFAL are divided into three categories, namely the common, optional, and personality tasks. In addition, the correlation between the tasks is mainly considered. In the improved genetic algorithm, minimizing the number of stations, minimizing the load indexes between stations and within each station, and maximizing task-related degree are used as optimization objectives. In the initialization process, a method based on a TOP sorting algorithm is adopted for generating chromosomes. Furthermore, a new decoding algorithm is proposed to make up for the lack of the traditional decoding method, and individuals in the two populations are exchanged. Therefore, the search speed of the algorithm is accelerated, which shows good performance through classic tested problems. Finally, the effectiveness and feasibility of the method were validated by optimizing assembly line balancing of loaders.

Lean manufacturing has been increasingly applied by leading manufacturing companies throughout the world, led by the major automobile manufacturers and their equipment suppliers. The aim of this case study is to show the applicability of lean manufacturing’s body of knowledge to a different environment: a seasonal food industry. Several techniques and analyses such as value stream mapping (VSM), overall equipment efficiency, spaghetti diagrams, work balance, and discrete event simulation were applied in this case study. Some of the improvement ideas resulting from the tools used were tested in the field to corroborate the findings. Finally, the future state VSM was mapped, where most of the improvement ideas identified throughout the project were consolidated. Whether the path to improvement is marked by increased spending on systems and machinery, human capital, or both, engineers and managers in the frontlines of food production recognize that improvement is a quest and not a destination. Although process industries need a special version of lean manufacturing tools, this case study shows how, with slight modification, several tools can be applied to the seasonal traditional craft industry.

The paper discusses the problems of forming parts such as stepped shafts by cross wedge rolling (CWR). In industrial practice, this rolling process is performed at stages, i.e., in several passes, when large cross-sectional reductions are involved. The same can also be done using a different design of this forming process, namely, multi-wedge cross rolling (MWCR), in which the workpiece is simultaneously formed by several pairs of tools (wedges). This paper compares the above two methods with respect to forming a drive shaft. Wedge tools used in both forming processes are described, and the numerical results of the simulations performed to verify the adopted solutions are reported. The results demonstrate that the MWCR method offers more advantages than the classical CWR technique. Consequently, MWCR is then verified in experimental tests. The experimental results confirm that parts such as stepped shafts can be formed by the MWCR method.

As typical ablation-resistant materials, carbon fiber–reinforced ceramic matrix composites (CMCs) are widely used as hot-end components such as rocket launcher nozzles. Nevertheless, their characteristics of anisotropic and hard-brittle bring processing challenges. Rotary ultrasound–assisted machining (RUM) is an effective machining method for hard-brittle materials. In this paper, we established a single abrasive grit trajectory model and elucidated the trajectory characteristics of the grits under ultrasonic-assisted side grinding (UASG) and ultrasonic-assisted end grinding (UAEG). Then the effects of longitudinal ultrasonic vibration on the grinding force, and surface quality in UASG and UAEG of 2.5D Cf/SiC composites were investigated by the single-factor test. Finally, the grinding mechanism under the two processing methods was revealed. The experimental results showed that the longitudinal vibration in the two machining methods has different effects on the grinding force and surface roughness. After the application of longitudinal vibration, the reduction of grinding force in the side grinding process was the largest. However, the reduction of surface roughness in the end grinding process was the largest, which was 35.6%. For the removal of each phase of 2.5D Cf/SiC composites, the brittle fracture, fiber debonding, and breakage of the matrix could be reduced after applying ultrasonic vibration in both processing methods.

A triangulation-based laser displacement sensor using the diffuse reflection light has a strong practical advantage in its robustness against the tilting of the object surface to the sensor’s sensitive direction. On the other hand, it is often subject to higher-frequency noise-like measurement error in scanning operations. This error is caused by the movement of the speckle in the reflected laser beam spot with the scanning operation. This paper first discusses how the dual-view triangulation, using two image sensors aligned symmetrically about the laser beam axis, can reduce the scanning noise in principle. Then, its inherent limitation is discussed. Since different points on the target surface cast the specular reflection to each image sensor, the influence of the sensor’s lateral movement cannot be canceled by comparing the reflected spot’s displacement on each image sensor. This issue can be observed clearer when measuring a surface of a less random surface profile. It is experimentally validated.

Owing to its excellent physical and chemical properties, such as high temperature resistance, corrosion resistance, and low density, optical glass is widely used in high-tech fields such as aviation, aerospace, and national defense; however, the grinding force during the processing of optical glass seriously affects the surface quality. Therefore, in the present paper, a mathematical model of the grinding force of diamond wheels with the ordered arrangement of abrasive grains on optical glass materials is established. The influences of the grinding wheel landform layout parameters and processing technology on the grinding force are discussed. The results of theoretical analysis and experimental research show that the ordered arrangement of abrasive grains can effectively reduce the grinding force. The values predicted by the model are in good agreement with the experimental results, indicating that the established mathematical model can provide theoretical guidance for the optimization of parameters in the processing process.

This paper aims to develop a fuzzy-based solution approach to address a machine-loading problem of a flexible manufacturing system (FMS). The proposed solution methodology effectively deals with all the three main constituents of a machine loading problem, viz. job sequence determination, operation machine allocation and the reallocation of jobs. The main objectives of the FMS loading problem considered here are minimisation of system imbalance and maximisation of throughput; the constraints to be satisfied are the available machining time and tool slots. An analytical argument has been provided to support the membership function related to the operation machine allocation vector. Computational results revealed the superiority of the proposed algorithm over other heuristics when it is tested on a standard data set adopted from literature. A new class of petri net model called the “Extended neuro fuzzy petri net” is constructed to capture clearly the various details of the machine loading problem which can be further extended to learn from experience and perform inferences so that truly intelligent system characteristics can be realised.

When the car suddenly collides, the webbing bunching phenomenon will occur at the upper guide ring (D-ring) of the height adjuster of the seat belt, causing serious damage to the human chest by local positive pressure. In this paper, finite element method is used to calculate lateral displacement of seat belt. The BP neural network training method was used to fit the relationship between the displacement response and the random parameters, and the reliability function was established. The reliability and reliability sensitivity of random parameters were calculated by first-order second-moment method, and the influence rule of belt guide ring and belt parameters on reliability was obtained, which provided a theoretical basis for the parameter reliability design of safety belt guide ring.