Network & Connectivity: How can manufacturers ensure robust, scalable, and secure network connectivity across diverse environments that often include both legacy machinery and modern IIoT devices?
Interoperability & Protocol Conversion: What strategies can companies implement to achieve seamless interoperability among devices using different communication protocols, and how can they effectively manage protocol conversion without sacrificing performance?
Asset Tracking, Asset Condition Monitoring & Device Management: What are the best practices for integrating asset tracking and condition monitoring systems to enhance device management processes and ensure operational continuity?
Predictive Quality, Performance & Production Management: How to leverage IIoT to predict and improve quality and performance in production management, and what challenges must they overcome to implement these systems effectively?
Predictive Maintenance: What technologies and approaches are essential for developing accurate predictive maintenance systems, and how can manufacturers integrate these into their existing operations without major disruptions?
Cybersecurity & IoT/OT Security: What are the key challenges in securing IoT and OT networks, and what new technologies or practices can provide effective defense mechanisms?
Industrial Edge Computing: What role does edge computing play in processing IIoT data, and what are the major hurdles in deploying and maintaining robust edge computing solutions in an industrial setting?
IIoT Platforms & IIoT Cloud: What are the main considerations for selecting an IIoT platform, particularly regarding cloud versus on-premise solutions, and how do these choices affect scalability and integration with existing IT infrastructure?
IT/OT Integration/Fusion: How to achieve IT / OT systems convergence, what are the significant barriers to integration, and how can organizations effectively address them to streamline processes and enhance data utilization?
AI/ML/Robotics: How can artificial intelligence and machine learning be integrated effectively into IIoT systems to enhance automation and decision-making processes, and what are the key challenges in training AI models with the data generated from industrial environments?
Digital Twin: What are the critical factors for successfully implementing digital twin technology in manufacturing, and how to overcome the challenges associated with creating and maintaining accurate and real-time digital replicas of physical assets?