Question 1

Have you programmed a PLC for a production line? Describe a specific project - which programming language did you choose (Ladder, FBD, ST) and why?

Accepted Answer

Structure around a specific project: (1) System description - PLC type (Siemens S7, Allen-Bradley, Mitsubishi), industry (food, electronics, textile), (2) Language choice rationale: Ladder is familiar to maintenance engineers from relay logic; ST for complex logic and calculations; FBD for control loops, (3) Technical challenges and how solved, (4) Measurable outcomes (OEE increase, downtime reduction). Candidates with real Vietnam experience often work with electronics factories (Samsung, LG, Intel) or food manufacturers (Vinamilk, Masan). Probe further on how they handled PLC communication with SCADA or MES systems.

Question 2

The company wants to deploy SCADA across 5 factories in different provinces. How would you design the SCADA architecture to ensure real-time monitoring and data security?

Accepted Answer

Design by layer: (1) Field Level - PLCs, sensors, RTUs at each factory, (2) Control Level - local SCADA server at each site, OPC-UA communication, (3) Supervisory Level - central server (on-premise or cloud) aggregating data from all sites, historian database, (4) Network - VPN or MPLS between sites, DMZ architecture to isolate OT network from IT network, (5) Security: air-gapping for critical systems, patch management for OT. The most important point is separating OT (Operational Technology) and IT networks - a basic security requirement many engineers overlook. Ask about redundancy and disaster recovery if the WAN connection goes down.

Question 3

How do you understand Industrial IoT (IIoT)? Describe how you would connect a legacy CNC machine (no network interface) into an IIoT system to monitor OEE.

Accepted Answer

Retrofitting approach: (1) Hardware layer - attach external sensors (vibration, current clamp to detect spindle state, proximity sensor for part counting) + Edge gateway (Raspberry Pi, Moxa, Advantech), (2) Connectivity - MQTT protocol from edge to cloud, (3) Cloud/platform - AWS IoT Core or Azure IoT Hub, (4) OEE calculation - Availability (uptime), Performance (actual vs. target speed), Quality (good parts/total parts), (5) Real-time dashboard. OEE (Overall Equipment Effectiveness) is the most important KPI in manufacturing. Strong candidates know OEE = Availability × Performance × Quality and will discuss that measuring Quality realistically may require a vision system.

Question 4

Have you worked with industrial robots (KUKA, ABB, Fanuc)? Explain the difference between online and offline robot programming and when you would use each.

Accepted Answer

Compare both methods: Online - program directly on the robot via teach pendant, suitable when high precision is needed for specific positions (welding, simple pick-and-place), robot stops production during programming; Offline - use simulation software (RobotStudio for ABB, KUKA Sim) on a computer, no production impact, can optimize path before deploying, requires precise calibration when transferring to the real robot. Probe further on calibration experience - this is the hardest part of offline programming. Strong candidates will mention TCP (Tool Center Point) calibration and workcell calibration to ensure the virtual model matches reality.

Question 5

What is a PID controller and have you tuned PID for a real system? Describe your tuning process and common problems you encountered.

Accepted Answer

Explain P-I-D: Proportional (immediate response to current error), Integral (accumulates past error to eliminate steady-state error), Derivative (predicts error trend to reduce overshoot). Real tuning process: Start with P-only, increase Kp until oscillation, add D to reduce oscillation, add I last to eliminate offset. Or Ziegler-Nichols method. Common problems: integral windup, noise amplification from Derivative. This is a foundational question that clearly reveals who understands theory vs. who has actually tuned in practice. Look for mentions of integral windup and how to handle it (anti-windup), and why the D term is often disabled in many real systems due to noise sensitivity.

Question 6

How is Industry 4.0 being applied in Vietnamese factories? Based on your observations, what is the biggest challenge Vietnamese factories face in implementation?

Accepted Answer

Describe Vietnam's reality: (1) FDI factories (Samsung, Intel, Foxconn) implement I4.0 following parent company standards - MES, AGV, vision inspection; (2) Vietnamese SMEs are still at Industry 2.0-3.0 stage; (3) Challenges: lack of OT/IT integration engineers, legacy equipment dominates the floor, high investment cost vs. thin margins, limited data literacy at management level. This question assesses understanding of the Vietnamese manufacturing context, not textbook I4.0 theory. Candidates with real experience will mention the skill gap and the reality that many Vietnamese SMEs lack the scale to justify I4.0 ROI.

Question 7

Have you designed an automated quality control system? Describe a specific case study, including how you determined acceptable defect rates and handled false positives.

Accepted Answer

Case study structure: (1) Type of defect to detect (dimensional, visual, presence/absence), (2) Inspection method: machine vision (camera + lighting + AI), laser measurement, CMM; (3) Threshold determination: Cpk capability study, AQL (Acceptable Quality Level) per standard, (4) False positive handling: high FP rate hurts throughput, need to balance sensitivity and specificity, (5) Line integration: reject chute, operator alert, MES data logging. Look for candidates who understand the trade-off between false positives (good parts rejected, costly) and false negatives (bad parts pass through, dangerous to the customer). This is a business decision, not just a technical one.