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Last Updated: Apr 26, 2025 | Study Period: 2023-2030
A pattern match sensor detects the shape, brightness, and orientation of a part to determine if the pattern matches what the sensor was taught.Pattern match sensors are used to confirm the presence of a part and differentiate parts by comparing their patterns.
The AI provides reliable detection even in situations when the part position is inconsistent or reflections are unstable.
This pattern match sensor does not struggle where conventional sensors fail. Setup is also quick and simple with just the press of a button.
The AI Series can be used for a wide variety of applications. Examples include spring presence, label misalignment, screw tap presence, capacitor direction determination, and felt presence.
In addition, the AI Series is capable of performing these detections over an area, which prevents errors due to variations in position or vibrations of targets.
After an image is registered, the target's brightness and shape are used to automatically determine which target features should be inspected during operation.
This image-based method provides stable detection of targets that are difficult to handle when using conventional sensors with light intensity-based detection.
The aftermath of COVID-19 pandemic on the organizations operating in the vertical, stating challenges and restraints like variations in supply chain, changes in consumer preferences, and imbalances experienced in business operations.
It also suggests multiple action plans to stay afloat amid this turbulence and generate strong revenues in the ensuing years.
The Global Pattern Matching Sensor Market accounted for $XX Billion in 2022 and is anticipated to reach $XX Billion by 2030, registering a CAGR of XX% from 2023 to 2030.
A major provider of 3D scanning and inspection solutions, LMI Technologies (LMI), is happy to announce the Gocator 6.1 software's official release.
With the groundbreaking addition of high precision 6DoF alignment and 3D mesh data generation for advanced shape measurement on 360o surface scans (using multi-sensor systems), a new 2D contour-based part and feature locator with Surface Pattern Matching, a GoHMI SDK toolkit for creating Gocator-to-factory operator interfaces, as well as a number of other smart 3D technology capabilities that improve automated quality inspection in the context of IIoT, are all included in this release.
Sl no | Topic |
1 | Market Segmentation |
2 | Scope of the report |
3 | Abbreviations |
4 | Research Methodology |
5 | Executive Summary |
6 | Introduction |
7 | Insights from Industry stakeholders |
8 | Cost breakdown of Product by sub-components and average profit margin |
9 | Disruptive innovation in the Industry |
10 | Technology trends in the Industry |
11 | Consumer trends in the industry |
12 | Recent Production Milestones |
13 | Component Manufacturing in US, EU and China |
14 | COVID-19 impact on overall market |
15 | COVID-19 impact on Production of components |
16 | COVID-19 impact on Point of sale |
17 | Market Segmentation, Dynamics and Forecast by Geography, 2023-2030 |
18 | Market Segmentation, Dynamics and Forecast by Product Type, 2023-2030 |
19 | Market Segmentation, Dynamics and Forecast by Application, 2023-2030 |
20 | Market Segmentation, Dynamics and Forecast by End use, 2023-2030 |
21 | Product installation rate by OEM, 2023 |
22 | Incline/Decline in Average B-2-B selling price in past 5 years |
23 | Competition from substitute products |
24 | Gross margin and average profitability of suppliers |
25 | New product development in past 12 months |
26 | M&A in past 12 months |
27 | Growth strategy of leading players |
28 | Market share of vendors, 2023 |
29 | Company Profiles |
30 | Unmet needs and opportunity for new suppliers |
31 | Conclusion |
32 | Appendix |