PATENT CLAIM ANALYSIS

Application Number: 15984104
Application Type: Utility
Filing Date: 2018-05
Publication Date: 2018-09
Patent Classification: ["419", "PCA001"]

Abstract:
This invention teaches a quality assurance system for additive manufacturing. This invention teaches a multi-sensor, real-time quality system including sensors, affiliated hardware, and data processing algorithms that are Lagrangian-Eulerian with respect to the reference frames of its associated input measurements. The quality system for Additive Manufacturing is capable of measuring true in-process state variables associated with an additive manufacturing process, i.e. those in-process variables that define a feasible process space within which the process is deemed nominal. The in-process state variables can also be correlated to the part structure or microstructure and can then be useful in identifying particular locations within the part likely to include defects.

Claim (Index 16):
A non-transitory computer readable storage medium configured to store instructions that, when executed by a processor of an additive manufacturing system, cause the additive manufacturing system to carry out steps that include:\n depositing a layer of metal material on a build plane; melting a region of the layer of metal material to form a part using a heat source that scans across the region of the layer of metal material; monitoring the heat source with a first optical sensor that follows a path along which the heat source scans the region to provide a first dataset and with a second optical sensor having a fixed field of view to provide a second dataset; comparing data from the first and second datasets with a known-good range from a baseline dataset to determine whether one or more portions of the part may include a manufacturing defect; and in response to the comparison of the first and second information sets indicating one or more portions of the part may include a manufacturing defect, adjusting the additive manufacturing operation.

Metadata:
- Claim Count in Document: 29.0
- Percentile: 93.0
- Lexical Diversity: 1.56757
- Patent Class: 419.0
- Transitional Phrase Type: none
- Component Type: 0
- Foreign Priority: False
- Related Applications: ['14832691', '15282822', '14995183', '15276452', '15408690']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.7151684246844712
- 35 USC 102 Novelty (BERT): 0.5350751730832353
- Combined Prediction Score: 0.6971590995243475
- Mean Citation Score: 226.545134
- Max Citation Score: 359.48215
- Similarity Product: 301.2024165518672

Labels:
- Claim Label 101: 0
- Claim Label 102: 1
- Claim Label 103: 0
- Claim Label 112: 1
- Combined Label: 0
- Label 101 Adjusted: 0

Dataset: test