4 Challenges of Implementing AI for IoT with JD Edwards

While AI and IoT technologies offer significant benefits to manufacturers when integrated with ERP systems like JD Edwards, several challenges must be addressed for successful implementation. Having an experienced team of experts to shepherd you through the process is a must-have.

Here are four challenges you may encounter while implementing AI with your IoT and JD Edwards.

Data Infrastructure Requirements

AI-implemented IoT devices track various parameters and performance in a warehouse and generate massive volumes of varied sensor data. Manufacturers need to not only collect this data (significant data collection/warehousing) but also store it securely. Setting up the necessary data infrastructure, like cloud data lakes, to store and analyze this "big data" requires upfront investment.

Data storage/databases and transfer

Traditional databases cannot handle at scale the volume of sensor-generated data. Choosing the right database solution (TinyDB, SQLite, or MariaDB for edge devices, potentially MariaDB for central storage) is crucial. Additionally, with limited device storage (limitations of data retention), data transfer and cloud storage become vital aspects to consider.

Data communication/connectivity

Manufacturing floors are a symphony of machines, each potentially from different vendors with their own communication protocols. This creates a "Tower of Babel" situation, where data formats and languages vary between sensors (multiple supported devices), databases (TinyDB, SQLite, or MariaDB), and even communication methods (ethernet, wireless, Bluetooth). Reconciling these discrepancies requires significant effort to ensure seamless data transfer and prevent overwritten data.

Data Standards/Protocols

Data collected from various sources needs to be standardized for the AI to understand it effectively. Data standards and protocols become an issue to some extent due to the multi-vendor support driven by the variety of devices used. Establishing data protocols ensures consistent communication and eliminates the risk of field cross reference errors. Standardization is essential for the smooth flow of data and information.

Data synchronization across devices, databases, and JD Edwards becomes paramount. Inconsistencies between real-time sensor data and JD Edwards records can lead to inaccurate insights and disrupted workflows. Ensuring data sync allows the AI to make informed decisions based on a unified view of the manufacturing ecosystem.

Data Security and Privacy

With sensitive customer and production data involved, implementing measures to protect information during use and storage against both internal and external threats is paramount but challenging. While significant, addressing these challenges opens the door to maximizing asset uptime, compliance, and overall equipment effectiveness through proactive maintenance powered by AI-driven IoT insights.

Orchestrating data flows and actions between IoT sensors, AI/ML platforms, ERP modules like JD Edwards, and other technical systems requires careful coordination. Legacy systems may limit integration options.

Device Diversity

The IoT device and sensor space isn’t as standardized as one might expect. A variety of options exist and different manufacturers select varying devices, even within their own ecosystem, to best suit their various cost and capacity needs. This diversity and the lack of standardization across smart equipment poses integration difficulties. Ensuring connectivity and data transfer compatibility across systems is complex.

Third-party support

It’s also important to consider the third-party support for those various devices. Unless you move to a single device type across the board, you will need to accommodate each device, and thereafter, have multiple supported devices in your space. The expertise required to navigate this complex integration might not always reside in-house. Third-party support can be invaluable for manufacturers looking to bridge the gap between AI, IoT, and JD Edwards. Finding the right partner ensures a smoother implementation process and ongoing technical support.

Elevate Your Future

Implementing AI with IoT and JD Edwards is a continuous process. New challenges may emerge as technology evolves, and manufacturers must be prepared to adapt. By acknowledging these complexities and embracing a collaborative approach, manufacturers can unlock the true potential of this technological symphony and orchestrate a smarter, more efficient future for their operations.

ERP Suites can help you achieve your goals with AI, the IoT and JD Edwards. Drop us a line here and we can take you through our AI workshop, to put your AI and IoT journey in motion.