Innovations in Manufacturing And the impact on South Africa. November 2018

Transcription

1 Innovations in Manufacturing And the impact on South Africa November 2018

2 The Industry 4.0 Process Demystifying the Realm of a Future Process M2M Smart Products + Smart Services Virtualization Mobility Smart Systems Robotics Analytics Demand-driven Synchronized Enterprise Open-Innovation Clusters Smart Dynamic Supply Chain Networks Cyber-physical Agile Collaboration Networks Digital Infrastructure Platform Innovative Consumer Delivery Servitization Models Lifecycle Support The vision of an advanced ecosystem with new innovations such as cyber-physical production, distributed manufacturing, industry convergence and social innovation, will form the basis for transformation in the manufacturing landscape. The success of adoption of Industry 4.0 systems will be governed by ROI guarantees. Technology enablers of Industry 4.0 will require a solid Business Case for enduser adoption. Source: Frost & Sullivan

3 Digital Factories - The Four Functional Facets Key building blocks across the manufacturing value chain Industry Convergence (IT OT) The cross-pollination of ideas, technologies and processes between the worlds of information technology, operational technology and telecommunication will form the crux of the fourth industrial revolution Services 2.0 Exploring newer avenues for service innovations, such as cloud-based service platforms and evaluating potential for new profit centers; Opportunity analysis for ICT technology in services Supply Chain Evolution The dawn of the future factory is set to disrupt existing supply chain networks; Digitalization and increased connectivity is set to disrupt and realign existing valuechain networks in the future The Industry 4.0 Business Ecosystem The advent of advanced ICT technologies will promote new interrelationships and interdependencies giving way to unexpected business collaborations and partnerships in the future

4 Summary of Recent Developments- Where Manufacturers are? Data harmonisation from disparate factory assets is the weakest link in digital factory discussions today Digital Factories: Manufacturer Expectations Digital Factories: Areas of Concern Modularized Mass Personalization Ambiguity in Value-add Capital Intensive and Unclear ROI Reduced Total Cost of Ownership New Service Models Security & Safety Agile Supply Chain Networks Risk of Cyber Threats Data Harmonisation We see a number of interesting digital platforms; but we are now forced to build a singular platform that can help unify all other platforms. This is a challenge - A German Automotive Supplier It s easy to measure, easy to quantify, and also it s easy to implement, so it s a system. But the problem is that there are different software companies, different hardware makers, and it s very difficult to implement -- A leading industrial machine builder

5 Emerging Services Roadmap Services 2.0: The Supplier s New Paradigm With the trend of servitization, end-users' emphasis on reduced TCO will drive the need for new service models at the supplier end Functional Core Understanding process, product expertise for leverage (a) Services 2.0: Vector of Business Transitions in the Service Landscape (b) Partner Collaboration Forging relationships for advanced ICT capabilities, including networking, communication and analytics Acquire (c) Delivery Innovation Evolving new business approaches for client delivery and value-creation Strong platform for traditional industry vendors Need for reinventing product design and architectures Beginning of the shift from product-based to process-based value proposition Organic and Inorganic transitions in Industrial markets New gateway for commercial ICT vendors in the industrial stage New-found demand for regional Sis/VARs Dawn of new business propositions supporting enduser need for reduced TCO Entry of Banking and Financial functions supporting service models/propositions Services 2.0: Service Evolution in Future of Manufacturing End-user perception growing in value Service becomes the foundation of new business models Ecosystem Services Service Partnerships Plant Services Service Outsourcing Asset Services Service as a Strategy Product Services Service as an Option

6 ARTIFICIAL INTELLIGENCE OTHER COGNITIVE TECHNOLOGIES (Speech Recognition, Robotics, Natural Language Processing etc.) DATA BIG DATA COGNITIVE Defining Cognitive Technologies Understanding the capabilities of artificial intelligence and other cognitive technologies in manufacturing COGNITIVE / ARTIFICIAL INTELLIGENCE : The science and engineering involved in developing intelligent machines. Empowers machines to perform tasks that are normally possible only by humans. MACHINE LEARNING DEEP LEARNING New answers to known questions Known answers to known questions New answers to new questions New answers to known questions 1950s 1980s 2000 & Beyond MACHINE LEARNING (ML): A branch of AI that enables machines to learn on their own without explicit programming. ANALYTICS MACHINE LEARNING DEEP LEARNING: A sub-branch of ML, the future of ML in manufacturing. Enables machines to learn on their own through a set of complex machine algorithms. Source: Frost & Sullivan

7 CONNECTIVITY INDUSTRIAL CLOUD Value Chain Ecosystem for Cognitive Manufacturing Emerging stakeholders in AI ecosystem that have the potential to shape the future of manufacturing SENSOR TECHNOLOGY IOT MIDDLEWARE PLATFORM AI ECOSYSTEM IN MANUFACTURING COGNITIVE TECHNOLOGY CYBER SECURITY BIG DATA ANALYTICS INDUSTRIAL AUTOMATION Sample list of companies in no particular order Source: Frost & Sullivan