IIoT for Process Control
Cristian works in Metso Group since 2006 is Brazilian and have 18 years working with Industrial Automation. Actually is in charge of Performance Solutions for Europe & LatinAmerica Markets. large experience in process optimization and intelligent maintenance in Pulp & Paper, Oil & Gas, Mining, Petrochemical, Metals Cristian Moraes Sales Manager Europe and Latin America 2
Overview What is IIoT? Why consider it? Application of IIoT to process control Examples: What can you do today? Practical considerations
What is IIoT? IIoT = Industrial Internet of Things = The application of IoT to Manufacturing Devices Connections IoT = The internetworking of smart devices to exchange data Microsoft s high-level description of IoT services History Analytics Devices Connections History Analytics Presentation Presentation
What are the Things? 5
Do you have IoT in your plant? Devices Connections History Analytics Presentation Control loops & processes Smart instruments, valves, etc. Not-so-smart instruments, valves, etc. Augmented by context Field Networks Fieldbus HART DCS/PLC OPC xml Historian AMS ODBC/SQL Business/Cloud Gateways MQTT Plant-based historians Laboratory information management systems Computerized maintenance management Vendor data Offline analysis Home-grown tools Platforms with limited tools Vendor solutions Solutiondependent tools Back to DCS or HMI Display anywhere
Does IIoT require the cloud? Regular IoT Industrial IoT On Prem IoT
How to extract the potential? Devices Connections History Analytics Presentation Control loops & processes Smart instruments, valves, etc. Not-so-smart instruments, valves, etc. Field Networks Fieldbus HART DCS/PLC OPC xml Historian AMS ODBC/SQL Plant-based historians Laboratory information management systems Computerized maintenance management Offline analysis Home-grown tools Platforms with limited tools Solutiondependent tools Back to DCS or HMI Augmented by context Business/Cloud Gateways MQTT Vendor data Vendor solutions Display anywhere
Examples: IIoT for process control Instrument health Devices Analytics Control loops & processes Smart instruments Not-so-smart instruments Augmented by context Noise Failure Availability Range errors Spiking
Examples: IIoT for process control Valve health Devices Analytics Control loops & processes Sizing Smart instruments Stiction Not-so-smart instruments Augmented by context Excess travel Air consumed Spiking Steps on a ladder confirms stiction Automated priority setting Automated diagnosis
Examples: IIoT for process control Loop tuning Devices Analytics Control loops & processes Smart instruments Not-so-smart instruments Augmented by context Variance Need tuning? Model Error Interaction Fully automated tuning recommendations
Examples: IIoT for process control Root cause analysis Devices Analytics Control loops & processes Smart instruments Not-so-smart instruments Augmented by context Interactions Strength Time shift Root cause Model
Example: Targeting process-specific analytics Reported as the number one issue Diagnosis: Flow cycling occasionally Further analysis: Valve sticking due to chemical build-up Change operating procedure: schedule line flush according to triggered reporting
What is the benefit of IIoT for process control? Leverages process data Leverages engineering time Improved control Reduced cost of operation Improved maintenance planning Increased production Improved stability / operation Improved quality Results depend upon where you focus the tools
Getting started What you don t need. 100% Smart Instruments Full Sensor Network Infrastructure Gateways Parallel Networks Tons of IT Knowledge Common Architecture Staffing Million-dollar budget Massive engineering study
Getting started What you do need. Some justification A goal Some connectivity Historian OPC Small amount of IT Support Training Software tools Tracking and follow-up
Goals and Justifications How bad are your Things? 30% of controllers in manual 30% of loops with horrible tuning 20-40% oscillating 30% of valves with mechanical issues How is it affecting your plant? 50% increase in process variability 0.5% - 10% energy efficiency 1% - 10% production 0.5% - 5% chemical consumption Worse nobody knows 17
Your next steps Test your situation Sample of 20-100 controllers What % in manual? What % oscillating? Develop justification What data do you already have available? Historian OPC Smart device data Look at tools Start with on-premises Solution Form the team Install software Training Low hanging fruit Flat-liners Wild tuning Noise issues Damaged valves Day-to-Day What to watch Follow-up Management KPIs Reviews Document value
Questions
Thank you. 20