One example method includes creating an ILP model that includes a delay model, an energy model, and a QoS model, and modeling, using the integer linear programming model, a VNF placement problem as an ILP problem, and the modeling includes: using the delay model to identify propagation, transmission, processing, and queuing, delays implied by enabling an instance of the VNF at an edge node to accept a user VNF call; using the energy model to identify energy consumption implied by enabling an instance of the VNF at an edge node to accept a user VNF call; and using the QoS model to identify end-to-end delay, bandwidth consumption, and jitter, implied by enabling an instance of the VNF at an edge node to accept a user virtual network function call. The problem modeled by the ILP model may be resolved by a heuristic method.

In various embodiments, a generative design application generates and evaluates automotive designs. In operation, the generative design application computes a first set of metric values based on a set of metrics associated with design goal(s) and a first set of parameter values for a parameterized automobile model. The generative design application then performs optimization operation(s) on the first set of parameter values based on the first set of metric values to generate a second set of parameter values. Subsequently, the generative design application generates at least one design based on the second set of parameter values that is more convergent with respect to at least one of the design goals than a previously generated design. Advantageously, less time and effort are required to generate and evaluate multiple designs and then optimize those designs relative to more manual prior art approaches.

A systematic approach to constructing process plans for hybrid manufacturing is provided. The process plans include arbitrary combinations of AM and SM processes. Unlike the suboptimal conventional practice, the sequence of AM and SM modalities is not fixed beforehand. Rather, all potentially viable process plans to fabricate a desired target part from arbitrary alternating sequences of pre-defined AM and SM modalities are explored in a systematic fashion. Once the state space of all process plans has been enumerated in terms of a partially ordered set of states, advanced artificial intelligence (AI) planning techniques are utilized to rapidly explore the state space, eliminate invalid process plans, for instance, process plans that make no physical sense, and optimize among the valid process plans using a cost function, for instance, manufacturing time and material or process costs.

Embodiments for tuning parameters to a synthesis program are provided. At least one set of parameter settings for the synthesis program is selected. A plurality of identical synthesis jobs for the at least one set of parameter settings is run in an iteration of the synthesis program. Results of the iteration of the synthesis program are analyzed utilizing a tuning optimization cost function. Combinations of the parameter settings are created based on the analysis. At least one synthesis job for is run each of the combinations of the parameter settings in a subsequent iteration of the synthesis program. The analysis of the results, the creating of the combinations of parameter settings, and the running at the at least one synthesis job for each of the combinations of parameter settings are repeated until an exit criteria has been achieved.

In various embodiments, a generative design application generates and evaluates automotive designs. In operation, the generative design application computes a first set of metric values based on a set of metrics associated with design goal(s) and a first set of parameter values for a parameterized automobile model. The generative design application then performs optimization operation(s) on the first set of parameter values based on the first set of metric values to generate a second set of parameter values. Subsequently, the generative design application generates at least one design based on the second set of parameter values that is more convergent with respect to at least one of the design goals than a previously generated design. Advantageously, less time and effort are required to generate and evaluate multiple designs and then optimize those designs relative to more manual prior art approaches.

A computer-implemented method for designing at least one shaping tool, a computer-implemented method for designing a manufacturing process for manufacturing at least one shaped body, a shaping tool designing system for designing at least one shaped body and a manufacture-designing system for designing a manufacturing process for manufacturing at least one shaped body.

A computer implemented lightweight design method including: a preliminary homogenization step for defining a material model related to an adopted manufacturing material; a subsequent optimization step for finding an optimal distribution of material density within the design domain; and a final post-processing step to find the geometry for manufacturing; wherein the preliminary homogenization step is performed for deriving the material model for a 2D/3D version of a porous material provided with circular/spherical holes in a Hexagonal Close-Packed (HCP) arrangement, and the post-processing step comprises computing position and size of the circular/spherical holes.

The present invention discloses an optimization method for a screen surface dynamic load of a vibrating screen. The method includes the following steps: step 1. selecting design variables, and establishing an experimental matrix; step 2. performing a response curved surface experiment; step 3. establishing two double-objective optimization models and solving the same to obtain two groups of Pareto solution sets, wherein the solution sets respectively represent screening efficiency optimization paths of the vibrating screen under the conditions of a high screen surface dynamic load and a low screen surface dynamic load; and step 4. calculating an optimization space for a screen surface dynamic load under a high screening efficiency. According to the method of the present invention, the screen surface dynamic load can be directly reduced, and the service life of the screen surface and the whole vibrating screen is prolonged.

A method of creating a fabricable segmented design for a physical device is provided. A computing system receives a design specification. The computing system optimizes an initial segmented design based on the design specification to create an improved segmented design. The computing system perturbs the improved segmented design to create a perturbed segmented design. The computing system optimizes the perturbed segmented design to create a second improved segmented design.

A combination of fastening points is obtained by repeating following steps as an optimum value when an evaluation method of a physical quantity acting on a substrate is specified. The steps include: obtaining the physical quantity according to the combination of fastening points; generating a regression model expressing one fastening point candidate by a binary variable; converting the regression model into an Ising model based on the evaluation method; and determining the combination of fastening points by selecting one of fastening points from the fastening point candidate positions using an Ising machine so as to minimize an evaluation value of the Ising model.