PMO Smart Ports Conference Tehran, 27. Feb Electrification, Automation and Digitalization G. Fischer, Siemens AG

Transcription

1 PMO Smart Ports Conference Tehran, 27. Feb Electrification, Automation and Digitalization G. Fischer, Siemens AG Restricted Siemens AG 2018 siemens.com/cranes

2 Objective & Outline Objective Outline The Iranian Smart Port Conference is organized to refine and domesticate the Smart Port concept for further developments in Iranian ports, and to identify the systems, technologies, and professionals who are capable to contribute towards these developments in the national and international level. Electrification - Terminal smart power supply - Crane drive system (motor, drives) - Modernization Automation - Terminal layouts - Modular automation - Congestion management Digitalization - Crane management system Page 2

3 Electrification, Automation and Digitalization Productivity Drivers Technological drivers Computing power Communication Sensors Virtualization Cloud computing Digitalization Digital Enterprise Integrated Engineering and Integrated Operations Different initiatives, e.g., Industrie 4.0 Industrial Internet Consortium (IIC) Made in China Electrification Automation Industry Perfect interaction of all components along the life cycle Industry Electrical power wherever and whenever Page 3 Time

4 Electrification in Ports Along the Value Chain Quay Transfer Area Stack Rail/Road Terminal Gate Loading/ unloading vessel Horizontal transport Stack shuffling/ storage Rail Road Interchange Gate entry/exit automation Hinterland transport Ship to Shore cranes Hybrid straddle carriers Battery powered AGV (A)RMG, (A)E-RTG Reefers e-un-/loading Smart Buildings e-highway Rail Electrification Electrified TTs e-vehicle charging infrastructure LED/LEP Lighting High Voltage Renewables Storage technology Medium-voltage switchgear and protection Transformer Low-voltage panels with protection and metering Network Management and Control Systems Port electrical distribution network Page 4

5 Energy Management for the Container Terminal Energy Management globally across all sites Port Site Integration of distributed energy resources Intelligent forecasts Energy Management Data for port ecosystem Integration of storage Integration onshorepower supply Benefits Transparency Billing Efficiency improvements (Predictive) Asset Management Optimized energy mix Flexibility for increasing electrification Integration new power demand e-mobility of cargo handling Intelligent reefer energy management Optimized Power Quality Load Management Optimal voltage & frequency conditions for operation Reduction of CO 2 -emissions systematic energy efficiency towards zero emissions operations Power quality & Energy efficiency Charging e-cargo Handling Reefer Energy Management Page 5

6 Reefer Energy Management Benefits Peak power shaving Hold-off reefer power-on during peak power demand periods Gradual recovery after black-out Avoid regeneration Turn-on reefers during crane regeneration Reefer-specific control Priorisation as per reefer content Billing on-demand Page 6

7 Sinamics S120 Crane Drives RTG STS Critical data: Insulation resistance monitoring Inverter temperature Peak current Booksize Cabinet Page 7

8 Simotics Crane Duty Motors Critical data: Motor temperature - Hoist, trolley, boom hoist: PT Gantry: PTC (3 warning, 3 tripping) Vibration Trolley/boom: SIMOTICS SD 1LE5 Hoist: SIMOTICS FD Gantry: SIMOTICS DP 1PC13 Page 8 Detail of analog temperature sensor in motor stator

9 Automated Container Terminal End Loading Internal horizontal transport Stack perpendicular to quay In general 2 portal cranes per stack Transfer zone at the end of the stack Short travelling quay to yard High stacking density Seperation of internal and external traffic Yard cranes will predominantly have to gantry travel Road trucks Page 9 Majority of container throughput being import/export

10 Automated Container Terminal Side Loading Waterside trucklane for internal horizontal transport Stacks parallel to quay In general 2 cantilever cranes per stack Transfer zone parallel to stack Variable HT travel distance High stacking density No seperation of internal and external traffic Less gantry travel yard cranes Landside trucklane for road trucks only Page 10 Majority of container throughput being transshipment

11 Automated Terminal Smart Data Sharing Terminal operating system (e.g. Opus) Data exchange bus/message broker Equipm. Mgt. Equipm. Mgt. Block management system Equipm. Mgt. Equipm. Mgt. STS cranes TT/SC/ AGV HT interface Yard cranes TT/SC/ AGV Truck Rail Water-side Horizontal Transport Storage yard Horizontal Transport Gate Page 11

12 Data Sharing Truck ETA Challenge: Prediction of truck ETA Page 12

13 Data Sharing Truck ETA Page 13

14 Data Sharing Truck ETA Page 14

15 Simocrane Automation Modules Page 15

16 Simocrane Automation Modules Remote/soft landing at target pos Hoist down to above target Auto trajectory to vessel target position Auto land on lashing platform Auto trajectory to lashing platform Insert twistlocks Hoist up to safe height Vessel loading Above deck TT operation Unlock Lock Hoist to safe height Identify TT HT cycle Position TT OCR Auto trajectory to truck lane Remote landing on container Identify container Page 16

17 SIPG Yangshan DT STS Shanghai International Port Group Yangshan Terminal Double Trolley STS using Simocrane SC with semi-automatic trajectory Page 17

18 Modernization Simovert - Sinamics Remove existing noise filters Modernization options 1. Replace chassis onsite 2. Replace drive cabinets 3. Partly replacement Advantages of the concept: Keep existing cubicles Keep existing cabling to motors and cable No main mechanical work required (remove E-house roof, cubicle mountings, etc ) Minimum downtime low costs upgrade only what s important Harvest spare parts for remaining cranes Replace Masterdrives chassis by Sinamics S120 chassis Page 18

19 Modernization Simovert - Sinamics Update PLC program Update CMS CU320-2 Sinamics technology Masterdrive technology Scope: - Replace Masterdrive chassis/cabinets by Sinamics S120 chassis/cabinets - Update PLC <->Sinamics communications - Integrate Crane functions in new system - Update PLC program - Update CMS system (if possible) - Integrate any add-on features for productivity and safety improvement (sway control, truck positioning, TPS, LCPS, etc.. Page 19

20 Crane Management System Managing of information Alarm Logging Performance Data Replay Functionality Condition Monitoring Alarm message system Relevant performance data generation for further KPI calculation; Record all performed operations Fast recording - analog signals - binary signals Diagnosis - fault diagnosis - root cause analysis Operational excellence key figures Replay - all data - chronological order Detect time-critical switching states Page 20

21 Crane Management System Simocrane CMS & RCMS High availability on RCMS (redundancy on databasis Process Historian) Web-based architecture From data to information management (smart data) Connectivity to cloud / MindSphere (OPC UA) Multi-distributed system Page 21

22 SIMOCRANE CMS and Big Data CMS Cloud for Industry MindSphere WebClients CMS CMS Powerful Data Storage Data Pre-processing KPI Structured Data CMS Microsoft SQL Microsoft SQL Ms. Excel Process Historian (redundant) RCMS V4.4 Performance Monitoring Predictive Maintenance CMS Big Data Reports Page 22 Container Terminal SIMOCRANE RCMS Distribution of information RCMS Clients

23 Data Pre-Processing and Data Correlation SIMOCRANE RCMS Container Terminal Data Processing SIMOCRANE Analyzer Tool Fault Message CMS Data Storage Pre-processing Data Correlation Screen 1 CMS Microsoft SQL Microsoft SQL Replay Screen 2... CMS CMS Process Historian (redundant) & Condition Monitoring Screen 3 Data comparison in the background I/O points retrieve process Automatic filtering of data... Crane Topology Manager View CMS Big Data Page 23 Screen 10 Faults correlation with crane data

24 Condition Monitoring via Local CMS Digital Crane Finger Print RCMS CMS - Monitoring of crane components in time / frequency domain - Large amount of data over time (1 hour = 1 mil. measuring points) - Digital fingerprint of the crane Page 24

25 Crane Management System Data Presentation Data Modeling and Analysis Replay Data management Data integration Logging Databank Process Logging Alarm Logging Fast Traces Replay Functionality Page 25

26 Key Performance Indicators Berth productivity = Gross berth productivity = Gross crane productivity = Container moves Quay length Gross container moves Time Gross container moves Time * Crane Gross crane productivity target: 40 gmph state-of-the art: gmph Optimization: - analysis of cycle time - semi automatic operation - sway & skew control - profile scanning - truck positioning - remote control interface Page 26

27 Conclusion Quay Transfer Area Stack Rail/Road Terminal Gate Loading/ unloading vessel Horizontal transport Stack shuffling/ storage Rail Road Interchange Gate entry/exit automation Hinterland transport Electrification & smart use of energy Motor & drives equipment monitoring Smart upgrade of obsolete equipment Data sharing between water-side, yard, gate Minimal equipment use through optimization Maximize availability through predictive maintenance KPI calculation & monitoring Page 27