AWS IoT Device Defender vs. IFS Applications

We have used AWS IoT Device Defender to safeguard our client's IoT senors placed in a manufacturing unit for implementing Industry 4.0 solutions. Its machine learning and automation capabilities have ensured that we get alerts whenever something abnormal or spike in a particular metric is detected which lets us sleep at night. Didn't find any scenario where it is less suited.

Order to cash processes and scenario are implemented natively in IFS. An HR module exists for career management also (objectives, comportments, training, mobility) but may be improved in terms of workflow validation (e.g. training to validate by a manager) or reporting.

Incentivized

• software is having an easy interface
• prevents malicious data inflow/outflow from the AWS resources
• collect data from different devices
• generating alerts in case of any threshold.
• Unique identity per device

• It supports the web version in most later versions.
• It provides various mobile versions of the applications as mobile apps to cater various areas.
• IFS Applications allows easy configurations of the application without going for costly customization.
• It covers almost every areas of an industrial company so any other third party applications are minimum.
• It allows safer and easier built-in options for integrations capabilities.

Incentivized

• Support to more range of Application vulnerabilities
• Data Management can be richer
• Limited Computing Power at times

• Handling massive volumes of data can be improved.

Incentivized

The system is very difficult to use, overly complex, and difficult to learn. It also has limitations that are hard to overcome.

We have been unable to get answers to our questions, solutions to our problems, and they don't seem interested in working in the construction industry.

IFS Applications is based on Agile Technology which allows organizations to reconfigure user interface as per user requirements and make it user-friendly. Other applications are lagging on many fronts like User Interface, Online help document availability, Implementation methodology, and post-implementation expenses.

• It's ML part which is already trained and on the top of that we can add our own model to define device behaviors to monitor traffic and set the upmost security.

• Reporting is now centralized and managed. Previously, reports were outside the information systems and there was a risk of incoherence.
• Accounting controls are now in place on the overall processes, including production, which helped the company to reduce closing periods or to produce more easily official mandatory accounting files yearly.
• Interfaces between the CRM forecast tool and IFS helped to keep the tools in sync, and to decrease the processing times prior to production launch.

Incentivized