Digitisation Hype, Trend or Reality?

Transcription

1 Industrie Business in the Internet of Things June 30th, 2016 Ralf Bucksch Business Unit Executive Technical Sales Digitisation Hype, Trend or Reality? John Cohn, Fellow at IBM, 2

2 Basic Principles for Industrie 4.0 Manufacturer independent integration Decreased effort of integration and control Green production Standardisation of production: IT technology vs special field-bus Connectivity from idea to recycling Customer individual, lot-size 1 Realtime, event based control Product controlled manufacturing 3 Digitisation from a different perspective 61% Business Model Advanced predictive analytics analy Cyber security Real-time sensors 50% Products and Services 88% Customer Loyalty Explosion of mobile devices Infrastructure optimisation (cloud computing) Enterprise Social Media Source: Frankfurter Allgemeine Zeitung July 21st

3 Enterprise Innovation Integration of new era- and core systems YESTERDAY TODAY, INNOVATION IS DISCRETE AND DISPARATE EMERGENT, INTEGRATED SYSTEMS FOR ENTERPRISE INNOVATION Mission Critical Mobile Cloud Innovative Core Operations Social Big Data & Security of Insight of Insight Enterprise Enterprise Innovation Innovation of of of of Record Record Engagement Engagement Enabled by Cloud Pervasive Security Intelligence 40% of IT hires are recruited primarily for business skills. (IDC) 60% of IT spend is funded by line of business. (IDC) 80% of IT initiatives will be decided by line of business by (IDC) 5 Industrie 4.0 New business models - innovative and disruptive Collaboration Cloud Horizontal Integration Value Networks INTELLIGENT Big Data & INTERCONNECTED vertical Integration Security INSTRUMENTED Internet of Things and M2M (embedded) Development The digital advantage: 6 Rules, Events, mathematical Optimisation Mobile 9% Revenue 26% GP 8% Corporate Value Source: MIT Sloan Study

4 Innovation and Disruption itunes and ipod Digitised content platform Fitbit vs. WeightWatchers Wearable / Internet of Things platform 7 Uber Material goods and services platforms airbnb Disrupt or be disrupted Quality Minimum customer need Sustaining innovation Disruptive innovation Time Source Sogeti Rome Rome 2013

5 9 25 gigabytes of data per hour is generated by a connected car. 90% of cars will be connected by quintillion bytes of data generated daily by connected machines. The Data Challenge 80 million wearable health devices will be available by exabytes of healthcare data generated by devices in Increasing to 2,314 exabytes in There will be 28 times more sensorenabled devices than people by the year megabytes of data per second generated by every human being on the planet by Data attract more data Compute must move to data Health data will grow 99% Insurance data will grow 94% Utilities data will grow 99% Manufacturing data will grow 99% Data Data curation leads to optimal value 88% unstructured. 84% unstructured. 84% unstructured. 82% unstructured. 90% 3x 60% 2017 New IT platforms will emerge at the edge 10

6 Roads Soil Weather Land 11 Un-curated Diverse sources, resolutions, gaps, data types, update frequencies and uncertainty levels Curated Creates an integrated up-to-date view of layered spatio-temporal data with industry-specific analytics The era of Cognitive Business Understand Reason Learn Adapt and make sense of all data; read text, see images and hear natural speech with context Interpret information, organise it and offer explanations of what it means, with rationale for the conclusions Accumulate data and derive insight at every interaction, perpetually 12

7 The difference of and Cognitive Addresses predefined problems Provides accurate and definitive answers Handles information with known semantics Interacts in formal digital means (e.g. commands, screens) with humans + Cognitive Addresses ambiguous problems Provides answers with a margin of error Interacts in natural language with humans Handles information without explicitly knowing semantics 13 IoT will evolve to be more open and decentralised Before 2005 Today 2025 and beyond Closed and centralised IoT networks Open access IoT networks, centralised cloud Open access IoT networks, distributed cloud 14

8 IoT in the Blockchain 15 Leading in the next era of computing Symbiotic Cognitive Platforms Advanced Dialogue & Reasoning Neurosynaptic Brain-inspired Computing Hybrid Cloud Personality Curation at Scale Physical Exascale Data-centric Advanced Image Recognition Quantum Computing Ad Hoc Personalized Learning 0-18 months 18 months - 3 years years 16

9 Ralf Bucksch Business Unit Executive Technical Sales IBM DACH IBM Deutschland GmbH Wilhelm-Fay-Strasse Frankfurt Mobile Lead! Don t follow. Human brain: 100 billion neutrons 100 trillion synapses About 176,000 times more efficient than a modern CPU running the same brain-like workload. 18

10 Blockchain explained Party A s Records Incident Counter-party records API-integrations Bank records Party C s Records Auditor records Party B Records Problem - Difficult to monitor asset ownership and transfers in a trusted business network Inefficient, expensive, vulnerable 19 Blockchain explained Party A s Records Counter-party records Bank records Party C s Records Auditor records Party B Records Participants have multiple shared ledgers NOTE : Participants same as before 20 Solution shared, replicated, permissioned ledger Consensus, provenance, immutability, finality

11 IoT Prototype Solution Overview coexist Asset Management Mobile CRM/ERP cooperate HMI SPSS & GW Flexible Automation API IBM IoT Cloud Computing Environment SPSS & GW Saftey within MRK API API SPSS & GW Quality Control Data HMI API Track & Trace UI / Dashboard HMI Structured and unstructured data streams data flow (vertical integration) collaborate 21 material and data flow (horizontal integration) IoT Prototype Incoming parts Manufacturing Quality Control Outgoing parts Sensor environment connected to the IBM IoT Cloud 22