Minerals Introduction to Digitalisation

Transcription

1 Minerals Introduction to Digitalisation Siemens AG 2017 siemens.com/mining

2 The Digital (r)evolution Siemens has been at the forefront since the beginning of the Industrial Revolution 1 st Industrial Revolution 2 nd Industrial Revolution 3 rd Industrial Revolution 4 th Industrial (r)evolution Digitalization Automation Water & Steam Electrification Digitalization is still being defined Page 2

3 Fundamental drivers in Cement Industry Urbanisation Process HSSE Costs Output Increasing population and developing countries Unbalanced regional supply and consumption Standardized Process Distributed location of the operation plants according to consumption Health, Safety and Security Awareness of environmental care Lack of skilled talents at remote areas CAPEX efficiency OPEX reduction Standardization Increasing output Asset Efficiency & Reliability Production and Resources efficiency Widely distributed operations especially in remote areas with insufficient industrial infrastructure Increase productivity and output by optimized processing Long plant lifecycles Continuous, safe, secure and reliable operations Page 3

4 What is Digitalization? What can we do with Digitalization? With today s technology it is possible DIGITALIZATION What if this technology helps us to to collect huge amount of data to transfer huge amount of data to store huge amount of data to analyze huge amount of data solve our pain points in cement industry increase our plant availability and decrease costs increase efficiency in our plants Page 4

5 A Managed Condition Monitoring Service increasing the plant availability Comprehensive Service Contracts Page 5

6 Next generation Management Information Systems platforms for aggregating, relating, and presenting operational and business data Page 6

7 Comos Integrated Plant Engineering software platform Page 7

8 Siemens Unique Value Proposition together with Partners Domain know-how Portfolio and Analytics Applications know-how = Integrated Solutions for Minerals Industry Page 8

9 Digitalization a joint journey together with our partners and customers From data Visualization and recommendations Increase availability of components to value Data analysis and simulation Optimize energy consumption Secure data storage and transmission Improve cybersecurity Data collection Maximize process efficiency Page 9

10 Overland Conveyor Simulation Model Development Customer Solution Rio Tinto Australia Gove-site C system representation Productivity study for 1900 TPH Objective : Formulate methodologies and design solutions for ramping up tonnage in conveyor from 1500 TPH to 1900 TPH. Investigate ways for increasing production to 1900tph by : Combination of loading rate / speed that consumes the least amount of motor power, simulating effects on the conveying system Investigate largest losses, e.g. Idler width/spacing and rotating mass Customer Benefits Definition of best way to increase the capacity of the conveyor belt Prediction of possible critical areas on the conveying system during operation Page 10

11 Minerals Digital Architecture Concept Siemens AG 2017 siemens.com/mining

12 Minerals Digital Architecture Concept Enterprise Performance Improvement PLM applications, collaborative CAE platforms, analytics tools/cloud applications Corporate Systems ERP applications, executive dashboarding Customer Relationship Management Enterprise Resource Planning Operational Intelligence Full operations transparency 5 Business plan and strategy 6 Common layer Operations Management Level Enterprise Operations Management MOM/MES applications Virtual Modelling and Augmented Reality Material Flow Simulation Fleet and Logistics Optimization DUMMY Overall Operational Improvement 1 Monthly Closure Material Movement Tracking Expedition/Shipment Management Advanced Planning and Scheduling Power Grid Simulation Big Data Analytics Geo-statiscal Analytics Dynamic Production Planning R&D (New Processes and Materials development) DUMMY DUMMY Consolidated Multi Plants Data 2 Data Reconciliation Maintenance Management Inventory / Raw Materials Management Performance Analysis Material Processing/ Ore Beneficiation Quality Management Stockyard Management HSE Management Water Balance Operational Level Local Operational Improvement 3 Multisource Data Collection 7 Synchronized Execution Plan 8 Mine and Plant Simulation Engineering Input 9 Multiphysics Simulation (CFD/DEM) Predictive Maintenance Improvement Project 10 Advanced Process Control (APC) Consolidated Shop Floor Data 4 Operational Database Control Level Automation and expert mining systems Geographical InfoSystem (GIS) Drill and Blast DB Mobile Mine Dispatching Power and Utilities Manager Process Analyzer Asset Management (MRO) Engineering Database CAD/CAE platforms, EDM Geological Mapping and Modelling 3D Process Plant Model Strategic Mine Planning As built data F As is data Geo-scanning Point-cloud Laboratory Historian (LIMS) Process Historian (PIMS) Process Control Field Level Smart sensors, IoT devices Weighbridge Systems (Scalier) Train and Ship Dispatching Geotechnical Mapping and Modelling 2D Multidisciplinary Engineering Medium Term Mine Planning Power Supply Industrial Identification Wearables Drive Systems Condition Monitoring Field Devices Mine Planning and Design Construction and Assembly Commissioning and Start Up 1 E.g. planning, advisement; 2 E.g. production points, logistics infrastructure, stock availability; 3 E.g. set-point, configuration, training, inspection plan); 4 E.g. process data, equipment health; 5 E.g. Real-time production KPIs, stock availability per site; 6 E.g. sales orders/forecast, operational targets; 7 E.g. Pit-to-port, multisite, multisystem; 8 E.g. Control command, schedule, work instruction, training plan; 9 E.g. process and equipment design and datasheet; 10 E.g. conceptual model, innovation program, R&D output Page 12

13 Customer Press Release on value of Digitalization MES for Vale Brazil, considered the biggest MES Project in the world 05/18/2017 Vale estimates saving more than USD 70 million with innovation Developed in partnership with Chemtech, the new system is being implemented in the iron and manganese ore mines in Brazil Vale, in partnership with Chemtech, is implementing a new management system for iron and manganese ore units of the company in Brazil, replacing 17 other systems that were being used. Overall, 38 mines, plants and warehouses will have the new system, called Vale Production Management - Mining (GPV- M). The implementation has been completed in 20 units of Minas Gerais, Maranhão and Pará. This initiative will provide more than USD 70 million in savings until Source: Vale Internet Newsroom _than_usd_70_million_with_innovation_&s=innovation Technology&rID=1007&sID=4 Page 13

14 Where do the Savings in VALE Project come from? Customer Feedback (right column % of total savings, snap-shot) Increased availability and performance Improved system s stability and performance, reducing operational and compliance risks 20% Improved productivity and consistency for reporting and tracking the mining chain Agility and cost avoidance in rollout for new operations Process mgmt. and KPIs standardized and centralized in a single database, improving production visualization and allowing benchmarking 40% of cost avoidance in rollout projects. Flexibility and agility to deploy new operations 20% 10% Technology cost reduction 60% cost cutting in support costs (licences, infrastructure and service) 40% Improve asset utilization Use timely and more reliable information on production, quality and assets to take better decisions and improve asset utilization 10% On Track. Measure depends on full program implementation Confirmed Page 14