In an exclusive interview with ELE Times, Mr. Deep Hans Aroraa, Co-Founder & Director at JSD Electronics, discussed how the company is redefining IoT-enabled manufacturing through multi-layered cybersecurity, AI-driven quality control, and advanced testing methodologies. From embedding secure boot and end-to-end encryption into connected devices, to deploying machine vision and predictive analytics for defect prevention, JSD is committed to delivering reliable, compliant, and future-ready electronics. The conversation also explored the company’s use of digital twins, ERP-MES integration, and embedded software innovations that power smarter, more resilient products across industries. Excerpts:
ELE Times: How are you integrating cybersecurity measures into your IoT-enabled products to ensure data safety and compliance?
Deep Hans Aroraa: At JSD, we integrate multiple layers of cybersecurity into our IoT-enabled products to protect data integrity, confidentiality, and availability while ensuring compliance with industry standards.
Key Measures Implemented:
- Secure Boot – Only authenticated firmware is allowed to run.
- Firmware Signing & Verification – Prevents malicious or unauthorized firmware updates.
- End-to-End Encryption – TLS 1.3 / DTLS for secure data transmission.
- Mutual Authentication – Both device and server authenticate each other before communication.
- VPN or Private APN – Used for sensitive industrial and enterprise deployments.
- Data-at-Rest Encryption – AES-256 encryption for onboard storage and databases.
- API Authentication & Authorization – Implemented via OAuth 2.0 and JWT tokens.
- Cloud IAM (Identity & Access Management) – Restricts access to IoT data.
- Intrusion Detection Systems (IDS) – Specialized for IoT protocols such as MQTT and CoAP.
- Secure OTA Updates – Safely push patches and firmware updates throughout the device lifecycle.
ELE Times: What advanced testing or simulation technologies does JSD use to ensure the reliability of mission-critical devices like medical equipment and GPS systems?
Deep Hans Aroraa: For stable IoT device manufacturing aligned with global quality standards, JSD employs the following advanced testing and simulation technologies:
- Hardware-in-the-Loop (HIL) Testing
- Environmental & Stress Testing (Thermal Cycling, Shock Testing, Vibration, Humidity, and Corrosion Testing)
- RF & Wireless Performance Testing
- Functional Qualification Testing
- Protocol & Interoperability Testing (MQTT, TCP/IP, HTTP, etc.)
- Cybersecurity Penetration Testing
- Power Consumption & Battery Life Simulation
- EMC/EMI Compliance Testing
- Field Trials & Operational Evaluation
ELE Times: In what ways is JSD using data analytics or AI to optimize production lines and improve product quality?
Deep Hans Aroraa: Data plays a vital role in optimizing manufacturing operations. JSD has implemented ERP systems for production and inventory management, along with a Manufacturing Execution System (MES), enabling data capture from multiple sources such as machines, operators, environmental conditions, materials, and quality inspections.
Data Analytics Applications:
- Bottleneck Analysis (Time-Series) – Identify and resolve process slowdowns.
- Predictive Maintenance – Anticipate equipment failures before they occur.
- Process Parameter Optimization – Fine-tune machine settings for maximum efficiency.
- Dynamic Scheduling – Adjust production plans in real-time to changing conditions.
- Energy Optimization – Reduce energy consumption without impacting output.
Quality Improvement with AI:
- AI-Powered Visual Inspection – Detect the smallest defects in real time.
- In-Process Quality Prediction – Forecast potential quality issues before final assembly.
- Defect Root Cause Analysis – Pinpoint exact defect causes.
- Supplier Quality Analytics – Correlate incoming material quality with production outcomes.
These initiatives deliver better insights, higher yields, greater reliability, improved efficiency, and significant cost savings.
ELE Times: How is JSD integrating machine vision systems or AI-driven defect detection into its quality control processes?
Deep Hans Aroraa: JSD Optical Inspection & AI-Driven Quality Control Workflow
- Inward Material Inspection – Optical systems check incoming components for dimensional accuracy, labeling, and surface defects.
- PCBA Solder Paste Inspection (SPI) – Measures solder paste volume, height, and alignment before placement to ensure optimal solder joints.
- Pre-AOI – Verifies part type, polarity, and position after component placement.
- Post-AOI – Detects solder bridging, tombstoning, missing components, and misalignments after reflow soldering.
- Final Product Digital Inspection (PDI) – High-resolution imaging and visual inspection for cosmetic finish, assembly quality, and labeling.
AI-Enhanced Workflow:
- Image Capture – AOI systems record detailed PCB images.
- AI Analysis – Detects solder defects, missing components, and misalignments with high precision.
- Defect Logging – Records in MES with batch and machine data.
- Real-Time Alerts – Flags issues immediately for rework.
- Continuous Learning – Uses stored defect images for AI retraining and root cause prevention.
ELE Times: What role does embedded software development play in JSD’s product strategy, especially for smart connected devices?
Deep Hans Aroraa: Embedded software development is central to JSD’s product strategy, serving as the intelligence that transforms hardware into connected, adaptive, and differentiated products.
It defines core functionality, manages connectivity (Wi-Fi, Bluetooth, Zigbee, LoRa, 5G), and ensures security through secure boot, encryption, authentication, and OTA updates. Embedded software also enables scalability and future-proofing, allowing features and compliance updates without hardware redesign.
Additionally, it powers edge intelligence, processing data locally for faster response and reduced bandwidth, and governs data collection and transmission—critical for analytics, predictive maintenance, and new revenue streams.
ELE Times: How does JSD leverage digital twins or virtual prototyping before moving to full-scale manufacturing?
Deep Hans Aroraa: JSD uses digital twins and virtual prototyping to reduce risk, improve design quality, and accelerate time-to-market by creating virtual replicas for simulation and validation before physical production.
- Design Validation – Identify and fix flaws before building prototypes.
- Process Optimization – Simulate assembly lines and workflows to remove bottlenecks.
- Performance Testing – Model real-world stress, thermal, and EMI conditions.
- IoT-Driven Insights – Use sensor data for predictive improvements.
- Cost & Sustainability – Test materials and processes for efficiency and eco-impact.
- Training – Prepare teams in a simulated environment before production ramp-up.
