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Lawa Data By Cheng Zhang 9th,March,2012

Lawa Data By Cheng Zhang 9th,March,2012. Cheng’s personal info. Current role: MCAD&PLM Competitive Strategy Specialist Tenure: 4 years PTC Impact Participated in MCAD&PLM competitive intelligence webcast training for sales force quarterly.

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Lawa Data By Cheng Zhang 9th,March,2012

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  1. Lawa Data By Cheng Zhang 9th,March,2012

  2. Cheng’s personal info • Current role: MCAD&PLM Competitive Strategy Specialist • Tenure: 4 years • PTC Impact • Participated in MCAD&PLM competitive intelligence webcast training for sales force quarterly. • Initiated and ran competitive benchmark analysis of Competitors’ new released MCAD products. • Heavily involved “Beat SolidWorks Program” initiated by sales operation • Pre-PTC Experience • Intern at R&D Department of Shanghai machinery company (June ’07- March ’08) • Assistant at Flying Shear Balance Study team, BaoSteel (Aug ‘06 – March ’07) • Education • Shanghai University of Science and Technology (Masters in Mechanical Engineering) Cheng Zhang Chris Dodge More info please refer to http://about.me/chengzhang Pungke&Lawa is a project I run with my Partners in my spare Time. It aims to offers better tool or platform for engineers to builds products Incompleted websites:Pungke PROPRIETARY & CONFIDENTIAL – not for distribution

  3. - What’s lawa • - Why lawa • - Why semantic technology • lawa data classification • - CAD data • - Business/Processing data • - Functionality • Future strategy • - Dynamic documents • - BI What’s & Why lawa

  4. What’s & Why lawa What is lawa • lawa focus on engineering data management(design and manufuture) and will march on BI in future. • Unlike traditional data management, we will leverage on semantic technology and decentralization ideology to serve customer Why lawa? • Expensive software and hardware to centralize and syn everything. • Software easy of use is problematic which impede engineers’ efficiency. • No money in advance means customers will never lose money

  5. Why Semantic web technology • Semantic technologies provide the basis for a new way to deliver solutions that help drive innovation and improved decision making. • Manufacturing domain oriented ontologies provide an effective way of extracting greater value from complex data by linking and connecting disparate data together in helpful and meaningful ways that improve decision making. • lawa want to deploys Semantic Technology in a cloud environment via flexible and granular vertical apps that address specific data related challenges in manufacturing companies. In the session, we will present examples of manufacturing domain-oriented and upper ontologies that help improve innovation and decision making using lawa semantic technology apps.

  6. What’s & Why lawa • - What’s lawa • - Why lawa • - Why semantic technology • lawa data classification • - CAD data • - Business/Processing data • - Functionality • Future strategy • - Dynamic documents • - BI

  7. lawa data classification What is CAD data? • CAD data has proprietary format and heterogeneous - 3D(Pro/e, SolidWorks,NX), 2D(AutoCAD), ECAD(mentor,protel) • CAD data hasrelative complex relationships with each other - Assembly/Parts/drawing(装配,零件，工程图) - parts family table（零件表） - complicated relationship like upstream/downstream etc(各类CAD文件有上下游，父子关系等) • CAD data will associate with business document with different formats - Requirement analysis. - BOM - Processing card(工艺卡片) - After-sale service document

  8. What’s & Why lawa • - What’s lawa • - Why lawa • - Why semantic technology • lawa data classification • - CAD data • - Business/Processing data • - Functionality • Future strategy • - Dynamic documents • - BI

  9. Future plan (dynamic document) • Data Access: Combine data from databases,spreadsheets and documents from any source across the enterprise and the web • Intelligence: • Enable end users to create flexible dashboards to analyze and report on any data • Operational Action: • Create customized rules that automatically trigger alerts and workflows

  10. Future plan (BI) • Search Application Demo: Discovery for Design & SourcingLearn how designers and buyers in manufacturing enterprises can make better and informed decisions on new designs, engineering changes and address spend and risk reduction across the supply chain. The Discovery for Design & Sourcing solution combines data from PLM, supply chain and ERP systems to bridge the gap between engineering and sourcing in your enterprise.

  11. Competitive SWOT Analysis S Strengths W Weaknesses O Opportunities T Threats

  12. Panel discussion • Questions: • What’s structured and unstructured(semi-structured) • Data? • How to connect CAD document with other unlinked • Data(like word,pdf)?

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