Injection molding of plastic optical lenses prevails over many other techniques in both efficiency and cost; however, polymer shrinkage during cooling, high level of uneven residual stresses, and refractive index variations have limited its potential use for high precision lens fabrication. In this research, we adopted a newly developed strong graphene network to both plano and convex fused silica mold surfaces and proposed a novel injection molding with graphene-coated fused silica molds. This advanced injection molding process was implemented in the molding of polymer-based plano-concave lenses resulting in reduced polymer shrinkage. In addition, internal residual stresses and refractive index variations were also analyzed and discussed in detail. Meanwhile, as a comparison of conventional injection mold material, aluminum mold inserts with the same shape and size were also diamond machined and then employed to mold the same plano-concave lenses. Finally, a simulation model using moldex3d was utilized to interpret stress distributions of both graphene and aluminum molds and then validated by experiments. The comparison between graphene-coated mold and aluminum mold reveals that the novel injection molding with carbide-bonded graphene-coated fused silica mold inserts is capable of molding high-quality optical lenses with much less shrinkage and residual stresses with a more uniform refractive index distribution.

Cu-based brake pads applied in high-speed railway trains containing Ni-coated graphite flake and uncoated graphite flake were fabricated by powder metallurgy. The braking properties of the brake pads were investigated by a scaled down testing apparatus with the pad-on-disk configuration under various braking speeds and braking pressures. Compared with the brake pads containing uncoated graphite flake (designated GF), the brake pads containing Ni-coated graphite flake (designated NGF) exhibits a similar braking performance at lower braking speed and pressure. However, NGF shows more stable friction coefficient, lower linear wear loss, and lower maximum temperature during the braking process at worse braking conditions, e.g., 350 km/h, 1.5 MPa. The Ni-coating on the surface of Ni-coated graphite can transfer the mechanical bonding between copper and graphite to diffusion bonding so that there is a stronger interface bonding between copper and Ni-coated graphite. Further, the multiple linear regression analyses reveal that the mean friction coefficient of NGF is more sensitive to braking pressure than braking speed because of the better thermal resistance of NGF, while the mean friction coefficient of GF and the linear wear loss are mainly affected by braking speed.

Localized rapid heating process utilizing carbide-bonded graphene-coated silicon molds is a high-efficiency and energy-saving technique for high-volume fabrication of polymer optics. The graphene coating is used as a rapid heating element because of its high thermal conductivity and low electrical resistivity. However, the optical property of molded polymer and its dependence on process conditions such as heat transfer have not been thoroughly investigated. In this research, finite element method (FEM) simulation was utilized to interpret temperature changes of the graphene coating and heat transfer between graphene and polymethylmethacrylate (PMMA) in localized rapid heating. Experiments were then carried out under different voltages to validate the numerical model. In addition, refractive index variation of the PMMA lens resulting from nonuniform thermal history in molding was demonstrated by simulation modeling as well. Finally, wavefront variation of a PMMA lens molded by localized rapid heating was first studied using an FEM model and then verified by optical measurements with a Shack–Hartmann wavefront sensor (SHWFS). The wavefront variation in a PMMA lens molded by conventional method was also measured. Compared with conventional molding process, localized rapid heating is shown to be a possible alternative for better optical performance with a much shorter cycle time.

Cloud manufacturing is an emerging novel business paradigm for the manufacturing industry. In cloud manufacturing, distributed manufacturing resources are encapsulated into services and aggregated in a cloud manufacturing platform. Through centralized service management, cloud manufacturing is capable of dealing with multiple requirement tasks simultaneously. The ability to deal with multiple tasks at the same time is an important characteristic that distinguishes cloud manufacturing from the previous networked manufacturing models such as manufacturing grid. When it comes to multiple tasks in cloud manufacturing, a critical issue is how to schedule massive services to complete them with shortest makespan, lowest cost, and highest quality, etc. In order to facilitate the research on this issue, we in this paper propose a model for multitask-oriented service composition and scheduling in cloud manufacturing, in which key factures of cloud manufacturing such as service orientation, involvement of logistics, and dynamical change of service availability are taken into account. New concepts such as service efficiency, enterprise capability, and task workload are introduced, and various types of times including service time, logistics time, and waiting time are analyzed in detail. Moreover, this model can be conveniently extended by incorporating new elements such as task constraints, task priority, and continuous task arrival. An example that motivates the current model is presented. Simulation experiments with different numbers of tasks are performed to demonstrate the feasibility of the model.