INTERNET OF THINGS IN STEEL MANUFACTURING

Transcription

1 INTERNET OF THINGS IN STEEL MANUFACTURING Computer Applications Technology Committee Meeting, 9th Oct 2014 Presented by HCL Technologies

2 Agenda 1 Definition 2 Significance of IoT 3 Making a Steel Plant Smart 4 Modeling How IoT can help 5 Big Data Analytics How IoT can help 6 Cloud & SaaS 7 IoT & MES 8 IoT Framework 9 Challenges in Implementing IoT 2

3 Definition IoT is enabler for digitizing Manufacturing to be highly efficient and productive. It includes Using intelligent devices, equipment to produce assets; a cloud-based infrastructure for data processing big data storage capable of addressing a complex value chain; a combination of descriptive, predictive and prescriptive analytics and software to support asset and system optimization; Timelines 3

4 Significance of IoT Smart Manufacturing is the targeted New Normal US s SMLC & Germany s Industry 4.0 Every Major Vendor offers Remote monitoring services Automation to substitute ageing skilled work force 4

5 Making a Steel Plant Smart Implement Condition monitoring/predictive Analytics Each Machine is like an Individual The process automation data is not enough for diagnosing such complex machinery as a plate rolling mill. Example System & Causes of Hydraulic system in Hot Rolling Plant 5

6 Making a Steel Plant Smart Interoperability among systems & equipment 6

7 Making a Steel Plant Smart Plant Operations Management from Mobile Devices Accessories on mobile phones Intelligent Data acquisition devices Mobile Workflow Management In near Future Google Glass 7

8 Making a Steel Plant Smart Wireless Interoperability Control System, Mobile Devices Ease of Remote Management Track & Trace logistics solutions RFID Overall, the Ability to log all activities in a plant either by humans or machines for analysis 8

9 Modeling How IoT helps Many models used in Steel Operations - e.g. Sinter plant - Ore bed distribution in Sinter Plant Blast Furnace Burden Distribution Model Basic Oxygen Furnace Steel Bath & Slag models Models provide accurate predictive information leading to energy savings IoT Engines Packages for Genetic Algorithm Abundant past data for model creation R can be used for Modeling-solving differential equations desolve, ReacTran CARET package in R ideal for modeling Fitment of existing models becomes very easy. 9

10 Big Data Analytics How IoT helps Dynamic Rescheduling using IoT Hot Charging MES do not have vision of upstream units 10

11 Big Data Analytics How IoT helps Pattern Recognition Constant Risk monitoring based on past data Video Analytics on Cloud Thermal Imaging of refectories, High-speed video captures roughing mill operation for analysis Complex Event Processing (CEP) Data Stream Analysis e.g. Alert when sinter size exceed 5% deviation in 10 minute timeframe Microsoft StreamInsight, SQLStream open source 11

12 Cloud & SaaS Performance and Availability Guaranteed Unlimited, almost inexpensive data storage Multi Tenanted Architecture Pay only for what is used Subscription Model Gold, Silver, Bronze Services offered Analytics as a Service Storage as a Service Applications as a Service 12

13 Cloud & SaaS Select List of Providers of Machine Learning as Service Name Microsoft Azure Machine Learning Yottamine Analytics Zementis, Inc Sight Machine Ayasdi SkyTree Services Based on Azure platform, MS offers standard R and their research division developed Algorithms provides machine learning (SVM) based predictive models in the cloud. Pricing is based on usage. offers predictive models as a fully hosted service through Amazon Elastic Compute Cloud (EC2). merges machine vision and big data to control quality. provides a mathematical framework for analysis of complex, multivariate datasets Successfully deployed algorithms for preventive Maintenance 13

14 ML Studio in MS Azure 14

15 IoT & MES MES is specific to 1 plant, IoT is plant wide Power of IoT is on the Cloud, Analysis Services, Pay as you Use Periodic Application change Remote Monitoring of equipment Large Historian Data Analysis 15

16 IoT Framework 16

17 Challenges in IoT Deployment Cyber security Can affect any equipment Apprehensions of Cloud Security Making old equipment smart Reliable Internet connection scalability, security, availability and inexpensive Changing Managers/Operation Mindset Training See Tangible Benefits 17

18 Q&A

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