The rise of the engine remanufacturing industry has resulted in increased possibilities of energy conservation during the remanufacturing process, and scheduling could exert significant effects on the energy performance of manufacturing systems. However, only a few studies have specifically addressed energy-efficient scheduling for remanufacturing. Considering the uncertain processing time and routes and the operation characteristics of remanufacturing, we used the crankshaft as an illustrative case and built a fuzzy job-shop scheduling model to minimize the energy consumption during remanufacturing. An improved adaptive genetic algorithm was developed by using the hormone modulation mechanism to deal with the scheduling problem that simultaneously involves parallel machines, batch machines, and uncertain processing routes and time. The algorithm demonstrated superior performance in terms of optimal value, run time, and convergent generation in comparison with other algorithms. Computational results indicated that the optimal scheduling scheme is expected to generate 1.7 kW∙h of energy saving for the investigated problem size. In addition, the scheme could improve the energy efficiency of the crankshaft remanufacturing process by approximately 5%. This study provides a basis for production managers to improve the sustainability of remanufacturing through energy-aware scheduling.
Advanced manufacturing processes such as additive manufacturing offer now the capability to control material placement at unprecedented length scales and thereby dramatically open up the design space. This includes the considerations of new component topologies as well as the architecture of material within a topology offering new paths to creating lighter and more efficient structures. Topology optimization is an ideal tool for navigating this multiscale design problem and leveraging the capabilities of advanced manufacturing technologies. However, the resulting design problem is computationally challenging as very fine discretizations are needed to capture all micro-structural details. In this paper, a method based on reduction techniques is proposed to perform efficiently topology optimization at multiple scales. This method solves the design problem without length scale separation, i.e., without iterating between the two scales. Ergo, connectivity between space-varying micro-structures is naturally ensured. Several design problems for various types of micro-structural periodicity are performed to illustrate the method, including applications to infill patterns in additive manufacturing.
Remanufacturing route optimization is crucial in remanufacturing production because it exerts a considerable impact on the eco-efficiency (i.e., the best link between economic and environmental benefits) of remanufacturing. Therefore, an optimization model for remanufacturing process routes oriented toward eco-efficiency is proposed. In this model, fault tree analysis is used to extract the characteristic factors of used products. The ICAM definition method is utilized to design alternative remanufacturing process routes for the used products. Afterward, an eco-efficiency objective function model is established, and simulated annealing (SA) particle swarm optimization (PSO) is applied to select the manufacturing process route with the best eco-efficiency. The proposed model is then applied to the remanufacturing of a used helical cylindrical gear, and optimization of the remanufacturing process route is realized by MATLAB programming. The proposed model’s feasibility is verified by comparing the model’s performance with that of standard SA and PSO.
In accordance with the requirement of manufacturing dies quickly and economically, a hybrid forming method of stamping dies for automobile panels is proposed. The method combines digital patternless casting and high-power laser cladding. An experimental study is conducted on the hybrid forming process and its trial production and application in the manufacturing of stamping dies for typical panels. Results prove that the laser cladding layer exceeds HRC60 (Rockwell hardness) and thus meets the production efficiency requirement of automobile dies. The rate of defects is well controlled. Compared with traditional technology, this technology has remarkable advantages and advancement.
Only a few studies have been conducted on the flow behavior of the novel BTW1/Q345R bimetal, which is widely used in coal equipment. In this work, compression tests were conducted on BTW1/Q345R bimetal at a temperature range of 950 °C–1200 °C and strain rates of 0.05, 0.5, 5, and 15 s‒1 by using a Gleeble-3800 thermomechanical simulator. A constitutive equation was validated by referring to the Arrhenius equation during the characterization of hot workability. The computed apparent activation energy of the BTW1/Q345R bimetal was 360 kJ/mol, and processing maps under different strain conditions were drawn. Analysis of the stress-strain relationship revealed that work hardening exerted a dominant effect on the thermal deformation of the BTW1/Q345R bimetal. The processing maps predicted that the optimal processing interval will increase with strain. Results showed that thermal deformation of the BTW1/Q345R bimetal should proceed when the temperature range varies from 1182 °C to 1200 °C and the strain rate interval is from 4.2 to 15 s‒1.
A timing decision-making method for predecisional remanufacturing is presented. The method can effectively solve the uncertainty problem of remanufacturing blanks. From the perspective of reliability, this study analyzes the timing decision-making interval for predecisional remanufacturing of mechanical products during the service period and constructs an optimal timing model based on energy consumption and cost. The mapping relationships between time and energy consumption are predicted by using the characteristic values of performance degradation of products combined with the least squares support vector regression algorithm. Application of game theory reveals that when the energy consumption and cost are comprehensively optimal, this moment is the best time for predecisional remanufacturing. Used engine blades are utilized as an example to demonstrate the validity and effectiveness of the proposed method.
Lattice structures have numerous outstanding characteristics, such as light weight, high strength, excellent shock resistance, and highly efficient heat dissipation. In this work, by combining experimental and numerical methods, we investigate the compressive behavior and energy absorption of lattices made through the stereolithography apparatus process. Four types of lattice structures are considered: (i) Uniform body-centered-cubic (U-BCC); (ii) graded body-centered-cubic (G-BCC); (iii) uniform body-centered-cubic with z-axis reinforcement (U-BCCz); and (iv) graded body-centered-cubic with z-axis reinforcement (G-BCCz). We conduct compressive tests on these four lattices and numerically simulate the compression process through the finite element method. Analysis results show that BCCz has higher modulus and strength than BCC. In addition, uniform lattices show better energy absorption capabilities at small compression distances, while graded lattices absorb more energy at large compression distances. The good correlation between the simulation results and the experimental phenomena demonstrates the validity and accuracy of the present investigation method.
This study examines roll stability control for vehicles with an active roll-resistant electro-hydraulic suspension (RREHS) subsystem under steering maneuvers. First, we derive a vehicle model with four degrees of freedom and incorporates yaw and roll motions. Second, an optimal linear quadratic regulator controller is obtained in consideration of dynamic vehicle performance. Third, an RREHS subsystem with an electric servo-valve actuator is proposed, and the corresponding dynamic equations are obtained. Fourth, field experiments are conducted to validate the performance of the vehicle model under sine-wave and double-lane-change steering maneuvers. Finally, the effectiveness of the active RREHS is determined by examining vehicle responses under sine-wave and double-lane-change maneuvers. The enhancement in vehicle roll stability through the RREHS subsystem is also verified.
The theoretical and technological achievements in the damage mechanism and evaluation model obtained through the national basic research program “Key Fundamental Scientific Problems on Mechanical Equipment Remanufacturing” are reviewed in this work. Large centrifugal compressor impeller blanks were used as the study object. The materials of the blanks were FV520B and KMN. The mechanism and evaluation model of ultra-high cycle fatigue, erosion wear, and corrosion damage were studied via theoretical calculation, finite element simulation, and experimentation. For ultra-high cycle fatigue damage, the characteristics of ultra-high cycle fatigue of the impeller material were clarified, and prediction models of ultra-high cycle fatigue strength were established. A residual life evaluation technique based on the “b-HV-N” (where b was the nonlinear parameter, HV was the Vickers hardness, and N was the fatigue life) double criterion method was proposed. For erosion wear, the flow field of gas-solid two-phase flow inside the impeller was simulated, and the erosion wear law was clarified. Two models for erosion rate and erosion depth calculation were established. For corrosion damage, the electrochemical and stress corrosion behaviors of the impeller material and welded joints in H2S/CO2 environment were investigated. KISCC (critical stress intensity factor) and da/dt (crack growth rate, where a is the total crack length and t is time) varied with H2S concentration and temperature, and their variation laws were revealed. Through this research, the key scientific problems of the damage behavior and mechanism of remanufacturing objects in the multi-strength field and cross-scale were solved. The findings provide theoretical and evaluation model support for the analysis and evaluation of large centrifugal compressor impellers before remanufacturing.
The scheduling of parallel machines and the optimization of multi-line systems are two hotspots in the field of complex manufacturing systems. When the two problems are considered simultaneously, the resulting problem is much more complex than either of them. Obtaining sufficient training data for conventional data-based optimization approaches is difficult because of the high diversity of system structures. Consequently, optimization of multi-line systems with alternative machines requires a simple mechanism and must be minimally dependent on historical data. To define a general multi-line system with alternative machines, this study introduces the capability vector and matrix and the distribution vector and matrix. A naive optimization method is proposed in accordance with classic feedback control theory, and its key approaches are introduced. When a reasonable target value is provided, the proposed method can realize closed-loop optimization to the selected objective performance. Case studies are performed on a real 5/6-inch semiconductor wafer manufacturing facility and a simulated multi-line system constructed on the basis of the MiniFAB model. Results show that the proposed method can effectively and efficiently optimize various objective performance. The method demonstrates a potential for utilization in multi-objective optimization.