Industrial IoT (IIoT) & Sensor Data Basics
Industrial IoT projects fail in a predictable order: instrument everything, build a dashboard, discover nobody changes any decision because of it, quietly stop looking. The projects that work start from a decision somebody wants to make better and instrument backwards from there. This day covers the technology honestly, from sensor to dashboard, and spends the first module on the question that determines whether the rest is worth doing.
Programme Agenda
Starting From the Decision
Identifying a decision currently made on instinct or on a monthly report, and working backwards to what would have to be measured to improve it. Rejecting the use case that produces a nice chart and no change.
Sensors and What They Measure
Temperature, vibration, pressure, flow, current, and machine state. Accuracy against precision, sampling rate, placement, and the environmental ratings a plant floor demands.
Getting Data Off the Equipment
Reading from PLCs and existing control systems, retrofitting sensors to machines with no digital interface, and the industrial protocols involved. Gateways and protocol conversion.
Connectivity
Wired, industrial wireless, and cellular options compared on reliability, cost and the practical realities of a metal-heavy environment. Bandwidth, and why sending everything is usually the wrong design.
Edge and Cloud
What should be processed at the machine, what belongs in a central platform, and the latency, cost and resilience factors that decide. Buffering for the connection that will drop.
Data Quality and Context
A sensor reading without context is nearly useless. Timestamps and clock synchronisation, units, asset identity, and the metadata that lets you compare two machines. Detecting a sensor that has failed reading plausible values.
Storage and Visualisation
Time series data and why it is stored differently, retention and downsampling, and dashboards that support a decision rather than display everything available.
Security and Rollout
Keeping an IIoT deployment from becoming a route into the control network, and rolling out from a pilot to a line without the pilot's shortcuts becoming permanent.
Learning Outcomes:
Select a use case starting from a decision rather than from available sensors
Choose sensor types, sampling rates and placement appropriate to the measurement
Extract data from PLCs and retrofit sensors to equipment without interfaces
Compare connectivity options for an industrial environment
Decide what to process at the edge and what to send centrally
Attach the context and metadata that make readings comparable
Store and visualise time series data in a way that supports decisions
Deploy without creating a path into the control network
Duration: 1 Day (8 Hours)
Training Hours: 9:00 AM to 5:00 PM
Level: Beginner
Training Mode: Physical, Online, or Hybrid
HRD Corp SBL-KHAS Claimable
Certificate of Completion included
Frequently Asked Questions
More in Manufacturing and Industry 4.0
- Digital Twin and Smart Factory Concepts · All levels, 1 day
- Robotics and Automation Awareness · Beginner, 1 day
- Lean and Six Sigma (Yellow and Green Belt) · Beginner, 2 days
- Predictive Maintenance and Condition Monitoring · All levels, 1 day