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Digital Manufacturing and Design Innovation Institute

  1. 1. Digital Manufacturing and Design Innovation Institute William P. King wpk@Illinois.edu "I’m here to announce that we’re building Iron Man… Not really. Maybe. It’s classified." —President Obama
  2. 2. $320 MILLION $70 million cooperative agreement with the U.S. DOD and matching $250 million from industry, academia, government and community partners. 6 OF THE TOP 20 Engineering schools in the country, with more than 12% of all engineering & computer science students graduating annually in the U.S. 220,000 Partners, and more, ready to connect with the more than 185 small and medium sized businesses that have joined already. MORE THAN 315 Local, regional, and national organizations, community colleges, and MEP networks have committed their support. The Partnership 500+ Companies Committing to participate.
  3. 3. HISTORICAL MANUFACTURING • Linear process through design, make, and deliver • Commoditization of labor
  4. 4. TODAY’S MANUFACTURING • Materials: Rising costs and supply constraints • Production Overcapacity: reduced profitability • Labor: Increasing costs globally, skills gap • Outsourcing: separation of designers and makers has slowed innovation • Barriers for Sharing Data and Information: technology, skills, incentives, security, trust, IP, standards
  5. 5. FUTURE MANUFACTURING • Digital link between design and fabrication • Connected machines, factories, and supply chains • Transparency into supplier factories • Data aggregation, analysis, and action across the product lifecycle • Leverage the power of data analytics and networks to do more with existing resources
  6. 6. Manufacturing already generates more data than any other sector Petabytes Manufacturing Government Bankin g Communications and Media Retai l Professional Services Securities and Investment Services Healthcar e Educatio n Insurance Transportation Wholesal e Utilitie s Resource Industries Consumer and Recreational Services Constructio n 424 397 336 276 273 256 245 166 116 87 207 375 773 776 911 1,812 Annual new data stored by sector, 2010 1 Discrete manufacturing constitutes 1072 petabytes; Process manufacturing 740 petabytes SOURCE: IDC; McKinsey Global Institute analysis
  7. 7. WHAT IS DIGITAL MANUFACTURING? END OF LIFE REUSE RECYCLE END OF LIFE REUSE RECYCLE 11001011 PRODUCT LIFECYCLE AFTER-SALES SERVICE AFTER-SALES SERVICE 110100100100011110110101011110111110 SELL & DELIVER SELL & DELIVER 10101101101000010100100100101111011111010101111011111010111110 1111 FAFBABRRICIACTAETE FAFBABRRICICATAETE FAFBABRRICICATAETE QQUUALAILFIYFY 01010100110101010110110101010010010010100100100011110101010111101111101011111011111010 ASASSESMEMBBLELE 10110110101010101000001101101110110110110101010010100100101111010100100011110101011110111110101111101111101011111011 FAFBABRRICICATAETE 000100101010111101010100110101100100111101101000100100011010101011011010101000101010110110101101001111011111010111110111110101111101111101011 DEDSEISGIGNN 101111011010011110111011010111011001110110010110100100011010101011011010101001001000111101010010100100100011110101111111101111101011111011111010111110111110101111101111 101011111 DATA ACROSS THE PRODUCT LIFECYCLE DATA INFORMATION DECISIONS VALUE
  8. 8. Utilization of high performance computing to model materials, products and processes to enable “design with manufacturing in mind”. INTELLIGENT MACHINING (IM) ADVANCED ANALYSIS (AA) Integration of smart sensors and controls to enable equipment to automatically sense and understand current production environment in order to conduct “self-aware manufacturing”. THREE FOCUS AREAS ADVANCED MANUFACTURING ENTERPRISE (AME) Information systems integration throughout the product lifecycle. Digital links between design and fabrication. Smart factory and supply chain management. OPEN SOURCE PLATFORM CYBER PHYSICAL SECURITY DIGITAL COMMONS Meet industry and national An open source software platform that enables data aggregation, analysis, and action. needs for security, trust, and IP protection within the manufacturing environment. CYBER PHYSICAL DMDII Technology Thrust Areas
  9. 9. DMDII Guiding principles A B C D E F Start with the business need: Entire strategy is focused on how the application of advanced manufacturing technologies can solve specific business problems (i.e., “market pull” versus “technology-push”) Build and cultivate a diverse, distinctive, industry-led team: Assembled collaborative & committed team of advanced manufacturing firms across sectors, large & small, public-private. Flexible models to allow everyone to participate. Co-create the value proposition & strategy: Enlist the industry partners to define the strategy, operating model, project approach to build buy-in along the way Build an aligned industry roadmap: identifying a common set of problems across partnership, and aligning on an industry technology and project roadmap Bias to action… and creating demand: place a premium on speed and efficiency in launch and operation, getting to tangible impact soon through demonstration projects, which show what is possible and create demand for broader adoption Self-sufficiency through impact: doing the above will yield a high-value institute, that will create value – not just from membership fees, but from value it creates
  10. 10. Despite the recognition of importance for digital design and manufacturing, most organizations feel they lack the necessary capabilities 14% 81% Organizations with "high" digital capability today Participants indicating digital ops is a critical driver of future competitiveness
  11. 11. We surveyed decision-makers on where value will come from and their current level of maturity ▪ The survey leverages a detailed library of ~100 potential drivers of value along the value chain… as well as prompting for additional levers New business creation Product develop-ment Sourcing Production Supply chain Service End-of-life/ disposal Example Drivers ▪ Tracking and vis-ualization for the "reverse logistics“ supply chain for part disposal ▪ Predictive analytics for field main-tenance ▪ Real time product use/tracking in the field ▪ Real-time data collection/ analysis & operator feedback ▪ Advanced quality con-trol/ analysis for process optimization ▪ Supplier identifica-tion & selection ▪ Cost trans-parency ▪ Contract compliance ▪ Collabora-tive innova-tion, i.e., crowd-sourcing ▪ Advanced modeling and simula-tion tools ▪ “Smart” products that send/ receive data during use ▪ New service business to leverage data ▪ Joint plann-ing and forecasting ▪ Inventory & working capital optimization ▪ Customer demand-sensing For each step of the value chain (with particular depth in manufacturing production), the tool identifies a. The most important areas of opportunity in your organization b. Current organizational maturity c. Current improvement projects underway
  12. 12. Value will be derived across the full ‘value chain’ Importance rankings from New business creation Sourcing Capital Quality @ Cyber security Marketplaces and web-platforms & resource produc-tivity End-of-life/ Disposal Produc-tion Product develop-ment and R&D Supply chain manag-ement Service survey results High Med Low SOURCE: McKinsey survey of ~170 digital design and manufacturing leaders, DMDI
  13. 13. Value will be derived across the full ‘value chain’ “Where is the greatest value going to be derived along the value chain after implementation of digital manufacturing solutions?” 31 Little/no value Considerable 45 39 32 38 31 38 35 36 29 27 30 30 18 49 33 29 35 24 27 19 21 19 23 19 14 12 4 -6 -11 -5 -12 -17 -23 -20 -24 -23 -24 -27 -26 -36 -32 -40 -37 -10 -7 -12 -12 -13 -17 -12 -18 -12 -17 -13 -35 Product design & development Production (operations) Production (capital productivity) New "digital" business innovation Research & discovery Supply chain management Service Resource productivity & sustainability Operations strategy & management Collaboration platform Human capital Risk management Sourcing End-of-life/disposal Modest Significant Product design, operations, capital productivity, R&D, and supply chain management were highlighted as areas of greatest value
  14. 14. Successful digital leaders anchor their digital strategy back to clear sources of value Revenue improvement Higher product availability/up-time Profit business drivers Cost reduction Product innovation & customer satisfaction Time to market Revenue expansion of existing Manufacturing & supply chain costs (labor, material, overhead, G&A) Product quality Delivery and service performance Higher capital utilization Improved asset utilization Reduced equipment investment Increased inventory turnover Fixed capital Working capital Improved cash-to-cash cycle For the processes and capabilities that drive each branch, measures of improvement include: • Efficiency • Effectiveness • Speed • Agility (ability to change for upside benefit or downside protection) • Risk profile
  15. 15. Little/no importance Important Very important Most critical Digital is starting a paradigm shift: from operations as a cost & execution vehicle… to also an engine for innovation & growth “From a business metric perspective (e.g., cost, revenue), how important a driver can digital design & mfg be in creating value in each of these areas?” 45 31 30 38 44 36 42 27 39 35 17 30 24 12 -17 -18 -27 -26 -15 Operations agility -4 Revenue expansion of existing business Product quality -4 -31 -23 -5 -7 -12 -5 -14 Product innovation Time to market for new products Cost (manufacturing, supply chain, capital) Service levels Revenue & Growth drivers Conventional cost and quality drivers
  16. 16. Organizations realize that technology creates no value…on its own Capability Dimensions Clear strategy, plan to drive competitive advantage Cascade strategy into a well-resourced plan, with aligned metrics & accountability Skills and structure to develop solution and extract value Devices, apps and platforms to deliver Digital initiatives Information assets and associated management
  17. 17. Example DMDII Projects bring together a collection of partners to solve a real problem, with tangible impact... “market pull” rather than “technology push” Sample of potential applied research projects Sample impact Real-time shop floor advanced analytics 1 Intelligent machine ‘plug & play’ solution 2 Next-gen product & process design 3 Reduce rework and labor costs by up to 30%; $1MM over the life of the vehicle per hour saved in production Reduce current 50% scrap rate by half Reduce total system cost by 10-15%; accelerate time to market • Team: Two top 5 US Defense companies, one leading European aerospace company, two Top 20 engineering schools • Bring mobile computing and advanced analytics to shop floor decision-making, allowing real-time adjustments to complex vehicle system assembly • Team: Two major global industrial conglomerates, industry-leading software company, two major manufacturing research universities • Develop ‘plug & play’ hardware/software solution for adaptive machining ̶ Allows machines to adjust based on unique shape of each cast/blank part ̶ Interoperable across CNC machines • Team: Major global aerospace company, Top 3 aeronautical engineering school, state-Federal research partnerships • Design refresh of helicopter engine; 2 core innovations ̶ Advanced analytics and modeling software: compare as designed, as made, as assembled, as serviced data ̶ Collaboration software: real-time exchange & co-design
  18. 18. Sources of value from digital tech – voices of manufacturing leaders “What will be the most important drivers of future value from digital design and manufacturing?” • “Next generation product design with ability to simultaneously model and optimize for: • Manufacturability and reliability • Affordability through lifecycle (including production and maintenance post-sale) • Reduce design/purchasing risk by testing technology earlier and cheaper” • “Moving to a growth vs. cost story: • A new era post-commoditization with suppliers driving to the next level of supplier collaboration • Move from cost-focus to: • New product introduction focus • Speed to market focus • Rapid prototyping and virtual testing” • Connected customers with digitally enabled products, sharing data with manufacturers in real-time drives: • Proactive steps to address potential quality issues • Opportunities for new business models (e.g., selling services) • Informs marketing of key trends to react to • “Manufacturing feedback loops back to design: • Make-design link established • 3D design capability reducing cost in the make-design link and improve quality • Product performance data feeds new product innovation” • “Ability to adapt to key system perturbations • Improved macro forecasting • Downtime reduction between product families • Respond to changes in customer preferences • Reduced design/manufacturing constraints” • “Big data definition/standards, new interoperable plat-forms, analytics, & best practice standards), to drive: • Production efficiency • Response time to customer feedback (from years/months  months/days)” • “Ability to change/improve agility: • Reduce non-value added change/rework • Execute value-add changes quickly • Allow for more experimentation • Proactive measurement/adaptability”
  19. 19. DMDII Facility to Open February 2015

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  • bin95

    Apr. 1, 2015
  • ElenaKoskurOgly

    Nov. 25, 2015

Announced earlier this year, the Digital Manufacturing and Design Innovation Institute (DMDII) is a Chicago-based manufacturing hub that will bring together public, educational and private interests to accelerate innovation and reduce development time and costs. Learn how all manufacturing will benefit from the research and development based at this digital lab.


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