In an exclusive interview with ELE TIMES, Deep Hans Aroraa, co-founder and director of JSD Electronics, discussed how to redefine IoT-enabled manufacturing through multi-layer cybersecurity, AI-driven quality control, and advanced testing methods. From end-to-end encryption to connected devices with secure boot and end-to-end encryption to deploying predictive analytics for machine vision and defect prevention, JSD is committed to providing reliable, compliant, and future-ready electronics. The conversation explored the use of digital twin twins, ERP-MES integration, and embedded software innovations that enhance smarter and more resilient products across the industry. excerpt:
ELE TIMES: How do you integrate cybersecurity measures into IoT-enabled products to ensure data safety and compliance?
Deep Hans Arora: JSD integrates multiple cybersecurity into IoT-enabled products to ensure industry standard compliance while protecting data integrity, confidentiality and availability.
Main measurements implemented:
- Secure Boot – Only authenticated firmware can run.
- Firmware Signature and Verification – Prevents malicious or incorrect firmware updates.
- End-to-end encryption – TLS 1.3/DTL for secure data transmission.
- Mutual Authentication – Both the device and the 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 and Authorization – Implemented via OAUTH 2.0 and JWT tokens.
- Cloud IAM (ID and Access Management) – Restricts access to IoT data.
- Intrusion Detection System (IDS) – Specializes in IoT protocols such as MQTT and COAP.
- Secure OTA updates – safely press patch 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 such as medical devices and GPS systems?
Deep Hans Arora: For stable IoT device manufacturing to meet global quality standards, JSD employs the following advanced test and simulation technologies:
- Hardware in the Loop (HIL) Test
- Environmental and stress tests (thermal cycling, shock tests, vibration, humidity, corrosion tests)
- RF & Wireless Performance Test
- Functional qualification test
- Protocol and interoperability testing (MQTT, TCP/IP, HTTP, etc.)
- Cybersecurity penetration test
- Power consumption and battery life simulation
- EMC/EMI Compliance Test
- Field trials and operational evaluation
ELE TIMES: How does JSD use data analysis or AI to optimize production lines and improve product quality?
Deep Hans Arora: Data plays a key role in optimizing manufacturing operations. JSD implemented an ERP system for production and inventory management, allowing data capture from multiple sources, including machines, operators, environmental conditions, materials, and quality inspections, along with the Manufacturing Execution System (MES).
Data Analysis Application:
- Bottleneck Analysis (time series) – Identifies and resolves process slowdowns.
- Predictive Maintenance – Predict equipment failures before it occurs.
- Optimize Process Parameters – Fine-tune machine settings for maximum efficiency.
- Dynamic Scheduling – Adjust production plans to change in real-time.
- Energy Optimization – Reduce energy consumption without affecting the output.
Quality improvements through AI:
- AI-equipped visual inspection – detects the smallest defects in real time.
- In-process Quality Prediction – Predict potential quality issues before final assembly.
- Root Cause Analysis of Defects – Identify the exact cause of the defect.
- Supplier Quality Analysis – Correlates the quality of the material that comes in with production results.
These initiatives offer better insights, higher yields, greater reliability, greater efficiency and significant cost savings.
ELE TIMES: How does JSD integrate machine vision systems or AI-driven defect detection into the quality control process?
Deep Hans Arora: JSD Optical Inspection and AI-Driven Quality Control Workflow
- Inward-facing material inspection – The optical system checks input components for dimension accuracy, signage, and surface defects.
- PCBA Solder Paste Inspection (SPI) – Measure solder paste volume, height and alignment prior to placement to ensure optimal solder joints.
- Pre-AOI – Verifies part type, polarity and position after component placement.
- Post AOI – Detects solder bridging, gravestones, missing components, and misalignment after reflow soldering.
- Final Product Digital Inspection (PDI) – High-resolution imaging and visual inspection for cosmetic finishing, assembly quality, and labeling.
ai-enhanced workflow:
- Image Capture – The AOI system records detailed PCB images.
- AI Analysis – Highly accurate detection of solder defects, missing components, and misalignment.
- Defect Logging – Recording of MES using batches and machine data.
- Real-time alerts – Flag issues immediately for rework.
- Continuous Learning – Uses defect images stored in AI retraining and root cause prevention.
ELE TIMES: What role does JSD's product strategy play in particular the role of embedded software development for smart connected devices?
Deep Hans Arora: Embedded software development is at the heart of JSD's product strategy and acts as intelligence that transforms hardware into connected, adaptive, differentiated products.
Define core features, manage connectivity (Wi-Fi, Bluetooth, Zigbee, Lora, 5G) and ensure security through secure boot, encryption, authentication, and OTA updates. Embedded software allows for scalability and future prevention, allowing for functionality and compliance updates without hardware redesign.
Additionally, it processes data locally for edge intelligence, faster response and reduced bandwidth, and manages data collection and transmission. Analytics, predictive maintenance, and new revenue streams.
ELE TIMES: How does JSD utilize digital twin or virtual prototyping before moving to full-scale manufacturing?
Deep Hans Arora: JSD uses digital twins and virtual prototyping to accelerate time to market by reducing risk, improving design quality, and creating virtual replicas for simulation and verification before physical production.
- Design Verification – Identify and fix defects before building a prototype.
- Process Optimization – Simulate assembly lines and workflows to remove bottlenecks.
- Performance Testing – Real-world stress, heat, and EMI conditions for the model.
- IoT-driven insights – Use sensor data for prediction improvements.
- Cost and Sustainability – Test materials and processes for efficiency and environmental impact.
- Training – Prepare your team in a simulated environment before production ramp up.
