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Internal Marketing Survey

Swarm intelligence needed for new marketing campaign

Please rate 10 assumptions (only)

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Internal Marketing Survey

What are the most common mistakes when implementing a machine vision system?

Campaign background: Manufacturers increase the level of automation but don’t have the resources to handle machine vision applications. They need to upskill their technical teams to either solve MV applications, or to be able to communicate with machine vision integrators. 

The objective of this campaign is to educate machine vision users with no or little machine vision experience how to deploy and maintain a machine vision application, how to choose a machine vision partner and how to communicate effectively with integrators. Educational content positions Cognex as a partner beyond ‘just’ a vendor of machine vision products.


Your expertise will help us to craft a marketing campaign that addresses pain points of unexperiences machine vision users. Please rate the following 10 assumptions about the most common mistakes, that happen when implementing a machine vision system.

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Internal Marketing Survey

What are the most common mistakes when implementing a machine vision system?

1

Not Fully Defining the Application Requirements

Mistake: Jumping into product selection without a clear understanding of the features that must be inspected, other inspections that are 'nice to have', tolerances, and where in the process the application fits best)
2

Overlooking Lighting and Optics

Mistake: Focusing solely on the camera and software while neglecting the importance of proper lighting, lens selection, and environmental control. External lighting options impact the cost of the total solution and require more space.
3

Underestimating Integration Challenges

Mistake: Assuming the machine vision system will seamlessly integrate with existing automation hardware, control systems, or software. Ignoring space requirements, mounting options, and other physical constraints.
4

Focusing on Cost Over ROI

Mistake: Choosing the cheapest system instead of considering long-term ROI and scalability.
5

Overlooking System Scalability

Mistake: Selecting a vision system that works for the current application but can't scale for future needs (e.g., higher resolution, faster speeds, additional inspections or new product designs).
6

Lack of Training or Support

Mistake: Assuming the team can use and maintain the system without adequate training or ongoing support. Ignoring that people who have been trained on the application, might leave, can be sick or on vacation)
7

Neglecting Environmental Conditions

Mistake: Overlooking the effects of environmental factors like temperature, dust, vibrations, or moisture on the system.
8

Not Accounting for Image Processing Complexity

Mistake: Underestimating the processing power or software sophistication needed for the application (e.g. 3D inspection, line scan, multi-cam).
9

Failure to Test in Real Production Settings

Mistake: Relying on vendor demonstrations or lab tests without evaluating system performance in real factory conditions.
10

Ignoring Maintenance and Support Costs

Mistake: Focusing only on upfront costs without considering long-term maintenance, software updates, or availability of spare parts.
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Internal Marketing Survey
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Now, we would like to ask you to rank the following 'common mistakes'. The most relevant mistake (most often, highest impact) is at the top.

Drag and drop to change the order
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Anything else that comes to mind?

What do you observe when selling to customers with little experience in MV that Marketing could address?