PATENT CLAIM ANALYSIS

Application Number: 15936870
Application Type: Utility
Filing Date: 2018-03
Publication Date: 2018-12
Patent Classification: ["700", "009000"]

Abstract:
A scalable industrial data ingestion and analysis architecture integrates and collects data from multiple diverse sources at one or more industrial facilities. Data sources can include plant-level industrial devices and higher-level business systems. The data can be integrated and collected from multiple sources at an on-premise edge or gateway device, which sends the data to event queues on the cloud platform. The data queues orchestrate and store the data on cloud storage, and an analytics layer performs business analytics or other types of analysis on the stored data to produce various outcomes. Similar analytic platforms can also be implemented at the device level, and analytic functions can be scaled between the device level and higher levels in accordance with the scope of a given analytic function.

Claim (Index 16):
The method of  claim 1 , wherein the identifying the performance issue comprises identifying at least one of a risk of producing an excessive amount of product waste, an increase in a number of part rejections, a risk of excessive wear on one or more devices of an automation system, or a risk of a failure of one of the industrial devices.

Metadata:
- Claim Count in Document: 15.0
- Percentile: 90.0
- Lexical Diversity: 1.71795
- Patent Class: 700.0
- Transitional Phrase Type: none
- Component Type: 0
- Foreign Priority: False
- Related Applications: ['14928305', '15923127', '14087873', '13608821', '15278139']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.3786313717536468
- 35 USC 102 Novelty (BERT): 0.5106450966332966
- Combined Prediction Score: 0.3918327442416118
- Mean Citation Score: 201.445994
- Max Citation Score: 226.54193
- Similarity Product: 129.56900017020584

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

Dataset: test